Current Search: Robotics (x)
Pages
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Title
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Modeling and Compensation for Efficient Human Robot Interaction.
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Creator
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Paperno, Nicholas, Behal, Aman, Haralambous, Michael, Boloni, Ladislau, University of Central Florida
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Abstract / Description
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The purpose of this research is to first: identify the important human factors to performance when operating an assistive robotic manipulator, second: develop a predictive model that will be able to determine a user's performance based on their known human factors, and third: develop compensators based on the determined important human factors that will help improve user performance and satisfaction. An extensive literature search led to the selection of ten potential human factors to be...
Show moreThe purpose of this research is to first: identify the important human factors to performance when operating an assistive robotic manipulator, second: develop a predictive model that will be able to determine a user's performance based on their known human factors, and third: develop compensators based on the determined important human factors that will help improve user performance and satisfaction. An extensive literature search led to the selection of ten potential human factors to be analyzed including reaction time, spatial abilities (orientation and visualization), working memory, visual perception, dexterity (gross and fine), depth perception, and visual acuity of both eyes (classified as strongest and weakest). 93 participants were recruited to perform six different pick-and-place and retrieval tasks using an assistive robotic device. During this time, a participants Time-on-Task, Number-of-Moves, and Number-of-Moves per minute were recorded. From this it was determined that all the human factors except visual perception were considered important to at least one aspect of a user's performance. Predictive models were then developed using random forest, linear models, and polynomial models. To compensate for deficiencies in certain human factors, the GUI was redesigned based on a heuristic analysis and user feedback. Multimodal feedback as well as adjustments in the sensitivity of the input device and reduction in the robot's speed of movement were also implemented. From a user study using 15 participants it was found that certain compensation did improve satisfaction of the users, particularly the multimodal feedback and sensitivity adjustment. The reduction of speed was met with mixed reviews from the participants.
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Date Issued
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2016
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Identifier
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CFE0006370, ucf:51504
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0006370
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Title
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Learning robotic manipulation from user demonstrations.
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Creator
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Rahmatizadeh, Rouhollah, Boloni, Ladislau, Turgut, Damla, Jha, Sumit Kumar, University of Central Florida
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Abstract / Description
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Personal robots that help disabled or elderly people in their activities of daily living need to be able to autonomously perform complex manipulation tasks. Traditional approaches to this problem employ task-specific controllers. However, these must to be designed by expert programmers, are focused on a single task, and will perform the task as programmed, not according to the preferences of the user. In this dissertation, we investigate methods that enable an assistive robot to learn to...
Show morePersonal robots that help disabled or elderly people in their activities of daily living need to be able to autonomously perform complex manipulation tasks. Traditional approaches to this problem employ task-specific controllers. However, these must to be designed by expert programmers, are focused on a single task, and will perform the task as programmed, not according to the preferences of the user. In this dissertation, we investigate methods that enable an assistive robot to learn to execute tasks as demonstrated by the user. First, we describe a learning from demonstration (LfD) method that learns assistive tasks that need to be adapted to the position and orientation of the user's head. Then we discuss a recurrent neural network controller that learns to generate movement trajectories for the end-effector of the robot arm to accomplish a task. The input to this controller is the pose of related objects and the current pose of the end-effector itself. Next, we discuss how to extract user preferences from the demonstration using reinforcement learning. Finally, we extend this controller to one that learns to observe images of the environment and generate joint movements for the robot to accomplish a desired task. We discuss several techniques that improve the performance of the controller and reduce the number of required demonstrations. One of this is multi-task learning: learning multiple tasks simultaneously with the same neural network. Another technique is to make the controller output one joint at a time-step, therefore to condition the prediction of each joint on the previous joints. We evaluate these controllers on a set of manipulation tasks and show that they can learn complex tasks, overcome failure, and attempt a task several times until they succeed.
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Date Issued
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2017
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Identifier
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CFE0006908, ucf:51686
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0006908
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Title
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The Perception and Measurement of Human-Robot Trust.
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Creator
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Schaefer, Kristin, Hancock, Peter, Jentsch, Florian, Kincaid, John, Reinerman, Lauren, Billings, Deborah, Lee, John, University of Central Florida
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Abstract / Description
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As robots penetrate further into the everyday environments, trust in these robots becomes a crucial issue. The purpose of this work was to create and validate a reliable scale that could measure changes in an individual's trust in a robot. Assessment of current trust theory identified measurable antecedents specific to the human, the robot, and the environment. Six experiments subsumed the development of the 40 item trust scale. Scale development included the creation of a 172 item pool. Two...
Show moreAs robots penetrate further into the everyday environments, trust in these robots becomes a crucial issue. The purpose of this work was to create and validate a reliable scale that could measure changes in an individual's trust in a robot. Assessment of current trust theory identified measurable antecedents specific to the human, the robot, and the environment. Six experiments subsumed the development of the 40 item trust scale. Scale development included the creation of a 172 item pool. Two experiments identified the robot features and perceived functional characteristics that were related to the classification of a machine as a robot for this item pool. Item pool reduction techniques and subject matter expert (SME) content validation were used to reduce the scale to 40 items. The two final experiments were then conducted to validate the scale. The finalized 40 item pre-post interaction trust scale was designed to measure trust perceptions specific to HRI. The scale measured trust on a 0-100% rating scale and provides a percentage trust score. A 14 item sub-scale of this final version of the test recommended by SMEs may be sufficient for some HRI tasks, and the implications of this proposition were discussed.
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Date Issued
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2013
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Identifier
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CFE0004931, ucf:49634
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0004931
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Title
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A MOBILE ROBOTIC COMPUTING PLATFORM FOR THREE-DIMENSIONAL INDOOR MAPPING AND DATABASE BUILDING.
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Creator
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McCoig, Kenneth, Schiavone, Guy, University of Central Florida
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Abstract / Description
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There are several industries exploring solutions to quickly and accurately digitize unexplored indoor environments, into useable three-dimensional databases. Unfortunately, there are inherent challenges to the indoor mapping process such as, scanning limitations and environment complexity, which require a specific application of tools to map an environment precisely with low cost and high speed. This thesis successfully demonstrates the design and implementation of a low cost mobile robotic...
Show moreThere are several industries exploring solutions to quickly and accurately digitize unexplored indoor environments, into useable three-dimensional databases. Unfortunately, there are inherent challenges to the indoor mapping process such as, scanning limitations and environment complexity, which require a specific application of tools to map an environment precisely with low cost and high speed. This thesis successfully demonstrates the design and implementation of a low cost mobile robotic computing platform with laser scanner, for quickly mapping with high resolution, urban and/or indoor environments using a gyro-enhanced orientation sensor and selectable levels of detail. In addition, a low cost alternative solution to three-dimensional laser scanning is presented, via a standard two-dimensional SICK proximity laser scanner mounted to a custom servo motor mount and controlled by external microcontroller. A software system to control the robot is presented, which incorporates and adheres to widely accepted software engineering guidelines and principles. An analysis of the overall system, including robot specifications, system capabilities, and justification for certain design decisions, are described in detail. Results of various open source software algorithms, as it applies to scan data and image data, are also compared; including evaluation of data correlation and registration techniques. In addition, laser scanner mapping tests, specifications, and capabilities are presented and analyzed. A sample design for converting the final scanned point cloud data to a database is presented and assessed. The results suggest the overall project yields a relatively high degree of accuracy and lower cost over most other existing systems surveyed, as well as, the potential for application of the system in other fields. The results also discuss thoughts for possible future research work.
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Date Issued
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2004
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Identifier
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CFE0000313, ucf:46317
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0000313
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Title
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NONLINEAR ESTIMATION AND CONTROL FOR ASSISTIVE ROBOTS.
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Creator
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Wang, Zhao, Behal, Aman, University of Central Florida
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Abstract / Description
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In this thesis, we document the progress in the estimation and control design of a smart assistive robot arm that can provide assistance during activities of daily living to the elderly and/or users with disabilities. Interaction with the environment is made challenging by the kinematic uncertainty in the robot, imperfect sensor calibration, limited view of angle as well as the fact that most activities of daily living are generally required to be performed in unstructured environments. For...
Show moreIn this thesis, we document the progress in the estimation and control design of a smart assistive robot arm that can provide assistance during activities of daily living to the elderly and/or users with disabilities. Interaction with the environment is made challenging by the kinematic uncertainty in the robot, imperfect sensor calibration, limited view of angle as well as the fact that most activities of daily living are generally required to be performed in unstructured environments. For monocular visual systems, range (or depth) information is always crucial for target modeling and system control design. In the first part of my thesis, a novel and effective method is developed to estimate the range information in perspective vision systems by observing the 2-D image information and known motion parameters. We have considered the presence of noise in the image space measurements and kinematic uncertainty in the motion parameters. Simulation and experiment results show the advantage of our algorithm in comparison with other approaches. In the second part of the thesis, Lyapunov-based design techniques are utilized to propose a 2.5D visual servoing controller which stabilizes the robot end-effector pose while satisfying practical constraints on the sensing and the actuation. First, a nominal feedback controller is introduced which is then modified through an optimization-based approach in order to satisfy the constraints related to limited camera field-of-view and size of actuation. In the absence of actuator constraints, the proposed control law yields semi-global asymptotic (exponential) stability. When actuator constraints are introduced, the result is local asymptotic stability with known bounds on the region of attraction. Simulation and experimental results demonstrate the effectiveness of the proposed control methodology.
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Date Issued
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2011
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Identifier
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CFE0003889, ucf:48755
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0003889
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Title
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Modified System Design and Implementation of an Intelligent Assistive Robotic Manipulator.
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Creator
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Paperno, Nicholas, Behal, Aman, Haralambous, Michael, Sukthankar, Gita, Boloni, Ladislau, Smither, Janan, University of Central Florida
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Abstract / Description
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This thesis presents three improvements to the current UCF MANUS systems. The first improvement modifies the existing fine motion controller into PI controller that has been optimized to prevent the object from leaving the view of the cameras used for visual servoing. This is achieved by adding a weight matrix to the proportional part of the controller that is constrained by an artificial ROI. When the feature points being used are approaching the boundaries of the ROI, the optimized...
Show moreThis thesis presents three improvements to the current UCF MANUS systems. The first improvement modifies the existing fine motion controller into PI controller that has been optimized to prevent the object from leaving the view of the cameras used for visual servoing. This is achieved by adding a weight matrix to the proportional part of the controller that is constrained by an artificial ROI. When the feature points being used are approaching the boundaries of the ROI, the optimized controller weights are calculated using quadratic programming and added to the nominal proportional gain portion of the controller. The second improvement was a compensatory gross motion method designed to ensure that the desired object can be identified. If the object cannot be identified after the initial gross motion, the end-effector will then be moved to one of three different locations around the object until the object is identified or all possible positions are checked. This framework combines the Kanade-Lucase-Tomasi local tracking method with the ferns global detector/tracker to create a method that utilizes the strengths of both systems to overcome their inherent weaknesses. The last improvement is a particle-filter based tracking algorithm that robustifies the visual servoing function of fine motion. This method performs better than the current global detector/tracker that was being implemented by allowing the tracker to successfully track the object in complex environments with non-ideal conditions.
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Date Issued
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2015
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Identifier
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CFE0005681, ucf:50180
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0005681
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Title
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INTEGRATION OF COMMUNICATION CONSTRAINTS INTO PHYSIOCOMIMETICSWARMS VIA PLACEMENT OF LOCATION BASED VIRTUAL PARTICLES.
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Creator
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Haley, Joshua, Wiegand, R. Paul, University of Central Florida
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Abstract / Description
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This thesis describes a change to the Physiocomimetics Robotic Swarm Control framework that implements communication constraints into swarm behavior. These constraints are necessary to successfully implement theoretical applications in the real world. We describe the basic background of swarm robotics, the Physiocomimetics framework and methods that have attempted to implement communications constraints into robotic swarms. The Framework is changed by the inclusion of different virtual...
Show moreThis thesis describes a change to the Physiocomimetics Robotic Swarm Control framework that implements communication constraints into swarm behavior. These constraints are necessary to successfully implement theoretical applications in the real world. We describe the basic background of swarm robotics, the Physiocomimetics framework and methods that have attempted to implement communications constraints into robotic swarms. The Framework is changed by the inclusion of different virtual particles at a global and local scale that only cause a force on swarm elements if those elements are disconnected from a swarm network. The global particles introduced are a point of known connectivity and a global centroid of the swarm. The local particles introduced are the point of last connectivity and a local centroid. These particles are tested in various simulations and the results are discussed. The global particles are very effective at insuring the communication constraints of the swarm, but the local particles only have partial success. Additionally, some observations are made about swarm formations and the effect of the communication range used during swarm formation.
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Date Issued
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2011
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Identifier
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CFH0003812, ucf:44747
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFH0003812
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Title
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AUTONOMOUS ROBOTIC AUTOMATION SYSTEMWITH VISION FEEDBACK.
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Creator
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Rosino, Jeffery, Qu, Zhihua, University of Central Florida
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Abstract / Description
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In this thesis, a full design, development and application of an autonomous robotic automation system using vision feedback is performed. To realize this system, a cylindrical manipulator configuration is implemented, using a personal computer (PC) based PID controller from National Instruments. Full autonomous control will be achieved via a programmable human machine interface (HMI) developed on a PC using Borland C++ Builder. The vision feedback position control is accomplished using an...
Show moreIn this thesis, a full design, development and application of an autonomous robotic automation system using vision feedback is performed. To realize this system, a cylindrical manipulator configuration is implemented, using a personal computer (PC) based PID controller from National Instruments. Full autonomous control will be achieved via a programmable human machine interface (HMI) developed on a PC using Borland C++ Builder. The vision feedback position control is accomplished using an ordinary "off-the-shelf" web camera. The manuscript is organized as follows; After Chapter 1, an introduction to automation history and its role in the manufacturing industry, Chapter 2 discusses and outlines the development of the robotic kinematics and dynamics of the system. A control strategy is also developed and simulated in this chapter. Chapter 3 discusses color image processing and shows the development of the algorithm used for the vision feedback position control. Chapter 4 outlines the system development, which includes the hardware and software. Chapter 5 concludes with a summary, and improvement section. The process used as a basis for the design and development of this thesis of this thesis topic was constructed from a manual capacitor orientation check test station. A more detailed definition and objective is presented in the introduction.
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Date Issued
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2004
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Identifier
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CFE0000277, ucf:46220
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0000277
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Title
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Nonlinear Control Synthesis for Facilitation of Human-Robot Interaction.
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Creator
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Ding, Zhangchi, Behal, Aman, Pourmohammadi Fallah, Yaser, Haralambous, Michael, Boloni, Ladislau, Xu, Yunjun, University of Central Florida
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Abstract / Description
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Human-robot interaction is an area of interest that is becoming increasingly important in robotics research. Nonlinear control design techniques allow researchers to guarantee stability, performance, as well as safety, especially in cases involving physical human-robot interaction (PHRI). In this dissertation, we will propose two different nonlinear controllers and detail the design of an assistive robotic system to facilitate human-robot interaction. In Chapter 2, to facilitate physical...
Show moreHuman-robot interaction is an area of interest that is becoming increasingly important in robotics research. Nonlinear control design techniques allow researchers to guarantee stability, performance, as well as safety, especially in cases involving physical human-robot interaction (PHRI). In this dissertation, we will propose two different nonlinear controllers and detail the design of an assistive robotic system to facilitate human-robot interaction. In Chapter 2, to facilitate physical human-robot interaction, the problem of making a safe compliant contact between a human and an assistive robot is considered. Users with disabilities have a need to utilize their assistive robots for physical interaction during activities such as hair-grooming, scratching, face-sponging, etc. Specifically, we propose a hybrid force/velocity/attitude control for our physical human-robot interaction system which is based on measurements from a force/torque sensor mounted on the robot wrist. While automatically aligning the end-effector surface with the unknown environmental (human) surface, a desired commanded force is applied in the normal direction while following desired velocity commands in the tangential directions. A Lyapunov based stability analysis is provided to prove both convergence as well as passivity of the interaction to ensure both performance and safety. Simulation as well as experimental results verify the performance and robustness of the proposed hybrid force/velocity/attitude controller in the presence of dynamic uncertainties as well as safety compliance of human-robot interactions for a redundant robot manipulator.Chapter 3 presents the design, analysis, and experimental implementation of an adaptive control enabled intelligent algorithm to facilitate 1-click grasping of novel objects by a robotic gripper since one of the most common types of tasks for an assistive robot is pick and place/object retrieval tasks. But there are a variety of objects in our daily life all of which need different optimal force to grasp them. This algorithm facilitates automated grasping force adjustment. The use of object-geometry free modeling coupled with utilization of interaction force and slip velocity measurements allows for the design of an adaptive backstepping controller that is shown to be asymptotically stable via a Lyapunov-based analysis. Experiments with multiple objects using a prototype gripper with embedded sensing show that the proposed scheme is able to effectively immobilize novel objects within the gripper fingers. Furthermore, it is seen that the adaptation allows for close estimation of the minimum grasp force required for safe grasping which results in minimal deformation of the grasped object.In Chapter 4, we present the design and implementation of the motion controllerand adaptive interface for the second generation of the UCF-MANUSintelligent assistive robotic manipulator system. Based on usability testingfor the system, several features were implemented in the interface thatcould reduce the complexity of the human-robot interaction while alsocompensating for the deficits in different human factors, such as WorkingMemory, Response Inhibition, Processing Speed; , Depth Perception, SpatialAbility, Contrast Sensitivity. For the controller part, we designed severalnew features to provide the user has a less complex and safer interactionwith the robot, such as `One-click mode', `Move suggestion mode' and`Gripper Control Assistant'. As for the adaptive interface design, wedesigned and implemented compensators such as `Contrast Enhancement',`Object Proximity Velocity Reduction' and `Orientation Indicator'.
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Date Issued
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2019
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Identifier
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CFE0007798, ucf:52360
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0007798
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Title
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Conceptualization and Fabrication of a Bioinspired Mobile Robot Actuated by Shape Memory Alloy Springs.
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Creator
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Richardson, Lietsel, Das, Tuhin, Pal, Sudeshna, Huang, Helen, University of Central Florida
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Abstract / Description
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This work is an experimental study and fabrication of design concepts to validate the feasibility of smart materials and their applications in bio-inspired robotics. Shape-Memory Alloy (SMA) springs are selected as the smart material actuators of interest to achieve locomotion in the proposed mobile robot. Based on a previous design of the robot, this work focuses on both implementing a new locomotion concept and reducing size and weight of the previous design, both using SMA based actuators....
Show moreThis work is an experimental study and fabrication of design concepts to validate the feasibility of smart materials and their applications in bio-inspired robotics. Shape-Memory Alloy (SMA) springs are selected as the smart material actuators of interest to achieve locomotion in the proposed mobile robot. Based on a previous design of the robot, this work focuses on both implementing a new locomotion concept and reducing size and weight of the previous design, both using SMA based actuators. Objectives are met in consideration of the conceptual mechanics of circular robot locomotion. The first prototype is a variation of the original design. It consists of a soft, rubber outer shell with three intrinsically attached diametric SMA springs that deform the outer shell during contraction and relaxation. The springs were provided with electrical current in patterns to produce deformation needed to generate momentum and allow the robot to tumble and roll. This design was further improved to provide more stability while rolling.The second design concept is a modification of our previous design leading to reduction in size and weight while maintaining essentially the same mechanism of locomotion. In this case, the SMA springs were externally configured between the end of equi-spaced spokes and the circular core. Upon actuation, the spokes function as diametrically translating legs to generate locomotion. These design concepts are fabricated and experimented on, to determine their feasibility, i.e. whether rolling/tumbling motion is achieved. The scope of the project was limited to demonstration of basic locomotion, which was successful. Future work on this project will address the design of automatic control to generate motion using closed-loop sensor-based actuation.
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Date Issued
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2019
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Identifier
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CFE0007524, ucf:52589
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0007524
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Title
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COVERAGE PATH PLANNING AND CONTROL FOR AUTONOMOUS MOBILE ROBOTS.
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Creator
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balakrishnan, mohanakrishnan, Guo, Yi, University of Central Florida
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Abstract / Description
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Coverage control has many applications such as security patrolling, land mine detectors, and automatic vacuum cleaners. This Thesis presents an analytical approach for generation of control inputs for a non-holonomic mobile robot in coverage control. Neural Network approach is used for complete coverage of a given area in the presence of stationary and dynamic obstacles. A complete coverage algorithm is used to determine the sequence of points. Once the sequences of points are determined a...
Show moreCoverage control has many applications such as security patrolling, land mine detectors, and automatic vacuum cleaners. This Thesis presents an analytical approach for generation of control inputs for a non-holonomic mobile robot in coverage control. Neural Network approach is used for complete coverage of a given area in the presence of stationary and dynamic obstacles. A complete coverage algorithm is used to determine the sequence of points. Once the sequences of points are determined a smooth trajectory characterized by fifth order polynomial having second order continuity is generated. And the slope of the curve at each point is calculated from which the control inputs are generated analytically. Optimal trajectory is generated using a method given in research literature and a qualitative analysis of the smooth trajectory is done. Cooperative sweeping of multirobots is achieved by dividing the area to be covered into smaller areas depending on the number of robots. Once the area is divided into sub areas, each robot is assigned a sub area for cooperative sweeping.
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Date Issued
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2005
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Identifier
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CFE0000641, ucf:46497
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0000641
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Title
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Interactive Perception in Robotics.
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Creator
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Baghbahari Baghdadabad, Masoud, Behal, Aman, Haralambous, Michael, Lin, Mingjie, Sukthankar, Gita, Xu, Yunjun, University of Central Florida
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Abstract / Description
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Interactive perception is a significant and unique characteristic of embodied agents. An agent can discover plenty of knowledge through active interaction with its surrounding environment. Recently, deep learning structures introduced new possibilities to interactive perception in robotics. The advantage of deep learning is in acquiring self-organizing features from gathered data; however,it is computationally impractical to implement in real-time interaction applications. Moreover, it can be...
Show moreInteractive perception is a significant and unique characteristic of embodied agents. An agent can discover plenty of knowledge through active interaction with its surrounding environment. Recently, deep learning structures introduced new possibilities to interactive perception in robotics. The advantage of deep learning is in acquiring self-organizing features from gathered data; however,it is computationally impractical to implement in real-time interaction applications. Moreover, it can be difficult to attach a physical interpretation. An alternative suggested framework in such cases is integrated perception-action.In this dissertation, we propose two integrated interactive perception-action algorithms for real-time automated grasping of novel objects using pure tactile sensing. While visual sensing andprocessing is necessary for gross reaching movements, it can slow down the grasping process if it is the only sensing modality utilized. To overcome this issue, humans primarily utilize tactile perceptiononce the hand is in contact with the object. Inspired by this, we first propose an algorithm to define similar ability for a robot by formulating the required grasping steps.Next, we develop the algorithm to achieve force closure constraint via suggesting a human-like behavior for the robot to interactively identify the object. During this process, the robot adjuststhe hand through an interactive exploration of the object's local surface normal vector. After the robot finds the surface normal vector, it then tries to find the object edges to have a graspable finalrendezvous with the object. Such achievement is very important in order to find the objects edges for rectangular objects before fully grasping the object. We implement the proposed approacheson an assistive robot to demonstrate the performance of interactive perception-action strategies to accomplish grasping task in an automatic manner.
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Date Issued
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2019
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Identifier
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CFE0007780, ucf:52361
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0007780
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Title
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The Effect of Videogame Play on Robotic Surgery Skill Acquisition.
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Creator
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Tanaka, Alyssa, Hughes, Charles, Kincaid, John, Cendan, Juan, Smith, Roger, University of Central Florida
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Abstract / Description
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Robotic surgery uses innovative technology to transcend a surgeon's skills when performing complex procedures. Currently, the only FDA approved robotic system is Intuitive's da Vinci Surgical System. While this system offers many advantages over other minimally invasive techniques, it also introduces a need for specialized training. Virtual reality simulators have emerged as valuable tools for standardized and objective robotic surgery skill training and assessments. In recent years, the idea...
Show moreRobotic surgery uses innovative technology to transcend a surgeon's skills when performing complex procedures. Currently, the only FDA approved robotic system is Intuitive's da Vinci Surgical System. While this system offers many advantages over other minimally invasive techniques, it also introduces a need for specialized training. Virtual reality simulators have emerged as valuable tools for standardized and objective robotic surgery skill training and assessments. In recent years, the idea of using video game technology in surgical education for laparoscopy has also been explored; however few have attempted to make a connection between video game experience and robotic surgical skills. Thus, the current study aims to examine the performance of video gamers in a virtual reality robotic surgery simulator. Furthermore, the video gamers' performance was compared to that of medical students, expert robotic surgeons, and (")laypeople.(") The purpose of this study is to examine the hypothesis that video gamers acquire perceptual and psychomotor skills through video game play, similar to those used by robotic surgeons.Subjects completed a demographic questionnaire and performed three computer-based perceptual tests: a Flanker compatibility task, a subsidizing task, and a Multiple Object Tracking test. Participants then performed two warm-up exercises on the Mimic dV-Trainer to familiarize themselves with the system and eight trials of two core exercises to test their skills. After completing all trials, participants completed a post-questionnaire regarding their experience with the system.Expert video gamers (n=40), medical students (n=24), laypeople (n=42) and expert robotic surgeons (n=16) were recruited. Medical students and gamers were significantly faster than experts in the Flanker Task. The experts were significantly slower than the all other groups in the subsidizing task. Experts scored significantly higher, were significantly more efficient, and were significantly faster than laypeople, medical students, and gamers in the first trial of Ring (&) Rail 1 and Suture Sponge. In trial eight of Ring (&) Rail 1, experts scored significantly higher and were more efficient than laypeople. Experts were also significantly faster than all other groups. Experts scored significantly higher than laypeople and gamers in trial Suture Sponge. Experts were significantly more efficient and significantly faster than all other groups. Contrary to prior literature in laparoscopy, this study was unable to validate enhanced abilities of video gamers in a robotic surgery simulator. This study does further demonstrate that the transfer of skills developed through video game play is relevant to the surgical technique. This may be due to the differences of the systems and how the users interact within them. In a society where video games have become an integral past time, it is important to determine the role that video games play in the perceptual and psychomotor development of users. These findings can be generalized to domains outside of medicine that utilize robotic and computer-controlled systems, speaking to the scope of the gamers' abilities and pointing to the capacity within these systems.
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Date Issued
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2015
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Identifier
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CFE0006010, ucf:51002
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0006010
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Title
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Human-Robot Interaction For Multi-Robot Systems.
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Creator
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Lewis, Bennie, Sukthankar, Gita, Hughes, Charles, Laviola II, Joseph, Boloni, Ladislau, Hancock, Peter, University of Central Florida
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Abstract / Description
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Designing an effective human-robot interaction paradigm is particularly important for complex tasks such as multi robot manipulation that require the human and robot to work together in a tightly coupled fashion. Although increasing the number of robots can expand the area that therobots can cover within a bounded period of time, a poor human-robot interface will ultimately compromise the performance of the team of robots. However, introducing a human operator to the team of robots, does not...
Show moreDesigning an effective human-robot interaction paradigm is particularly important for complex tasks such as multi robot manipulation that require the human and robot to work together in a tightly coupled fashion. Although increasing the number of robots can expand the area that therobots can cover within a bounded period of time, a poor human-robot interface will ultimately compromise the performance of the team of robots. However, introducing a human operator to the team of robots, does not automatically improve performance due to the difficulty of teleoperating mobile robots with manipulators. The human operator's concentration is divided not only amongmultiple robots but also between controlling each robot's base and arm. This complexity substantially increases the potential neglect time, since the operator's inability to effectively attend to each robot during a critical phase of the task leads to a significant degradation in task performance.There are several proven paradigms for increasing the efficacy of human-robot interaction: 1) multimodal interfaces in which the user controls the robots using voice and gesture; 2) configurable interfaces which allow the user to create new commands by demonstrating them; 3) adaptive interfaceswhich reduce the operator's workload as necessary through increasing robot autonomy. This dissertation presents an evaluation of the relative benefits of different types of user interfaces for multi-robot systems composed of robots with wheeled bases and three degree of freedom arms. It describes a design for constructing low-cost multi-robot manipulation systems from off the shelfparts.User expertise was measured along three axes (navigation, manipulation, and coordination), and participants who performed above threshold on two out of three dimensions on a calibration task were rated as expert. Our experiments reveal that the relative expertise of the user was the key determinant of the best performing interface paradigm for that user, indicating that good user modeling is essential for designing a human-robot interaction system that will be used for an extended period of time. The contributions of the dissertation include: 1) a model for detecting operator distraction from robot motion trajectories; 2) adjustable autonomy paradigms for reducing operator workload; 3) a method for creating coordinated multi-robot behaviors from demonstrations with a single robot; 4) a user modeling approach for identifying expert-novice differences from short teleoperation traces.
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Date Issued
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2014
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Identifier
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CFE0005198, ucf:50613
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0005198
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Title
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Influence of Task-Role Mental Models on Human Interpretation of Robot Motion Behavior.
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Creator
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Ososky, Scott, Jentsch, Florian, Shumaker, Randall, Fiore, Stephen, Lackey, Stephanie, University of Central Florida
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Abstract / Description
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The transition in robotics from tools to teammates has begun. However, the benefit autonomous robots provide will be diminished if human teammates misinterpret robot behaviors. Applying mental model theory as the organizing framework for human understanding of robots, the current empirical study examined the influence of task-role mental models of robots on the interpretation of robot motion behaviors, and the resulting impact on subjective ratings of robots. Observers (N = 120) were exposed...
Show moreThe transition in robotics from tools to teammates has begun. However, the benefit autonomous robots provide will be diminished if human teammates misinterpret robot behaviors. Applying mental model theory as the organizing framework for human understanding of robots, the current empirical study examined the influence of task-role mental models of robots on the interpretation of robot motion behaviors, and the resulting impact on subjective ratings of robots. Observers (N = 120) were exposed to robot behaviors that were either congruent or incongruent with their task-role mental model, by experimental manipulation of preparatory robot task-role information to influence mental models (i.e., security guard, groundskeeper, or no information), the robot's actual task-role behaviors (i.e., security guard or groundskeeper), and the order in which these robot behaviors were presented. The results of the research supported the hypothesis that observers with congruent mental models were significantly more accurate in interpreting the motion behaviors of the robot than observers without a specific mental model. Additionally, an incongruent mental model, under certain circumstances, significantly hindered an observer's interpretation accuracy, resulting in subjective sureness of inaccurate interpretations. The strength of the effects that mental models had on the interpretation and assessment of robot behaviors was thought to have been moderated by the ease with which a particular mental model could reasonably explain the robot's behavior, termed mental model applicability. Finally, positive associations were found between differences in observers' interpretation accuracy and differences in subjective ratings of robot intelligence, safety, and trustworthiness. The current research offers implications for the relationships between mental model components, as well as implications for designing robot behaviors to appear more transparent, or opaque, to humans.
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Date Issued
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2013
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Identifier
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CFE0005391, ucf:50457
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0005391
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Title
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THE IMPACT OF MENTAL TRANSFORMATION TRAINING ACROSS LEVELS OF AUTOMATION ON SPATIAL AWARENESS IN HUMAN-ROBOT INTERACTION.
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Creator
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Rehfeld, Sherri, Jentsch, Florian, University of Central Florida
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Abstract / Description
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One of the problems affecting robot operators' spatial awareness involves their ability to infer a robot's location based on the views from on-board cameras and other electro-optic systems. To understand the vehicle's location, operators typically need to translate images from a vehicle's camera into some other coordinates, such as a location on a map. This translation requires operators to relate the view by mentally rotating it along a number of axes, a task that is both...
Show moreOne of the problems affecting robot operators' spatial awareness involves their ability to infer a robot's location based on the views from on-board cameras and other electro-optic systems. To understand the vehicle's location, operators typically need to translate images from a vehicle's camera into some other coordinates, such as a location on a map. This translation requires operators to relate the view by mentally rotating it along a number of axes, a task that is both attention-demanding and workload-intensive, and one that is likely affected by individual differences in operator spatial abilities. Because building and maintaining spatial awareness is attention-demanding and workload-intensive, any variable that changes operator workload and attention should be investigated for its effects on operator spatial awareness. One of these variables is the use of automation (i.e., assigning functions to the robot). According to Malleable Attentional Resource Theory (MART), variation in workload across levels of automation affects an operator's attentional capacity to process critical cues like those that enable an operator to understand the robot's past, current, and future location. The study reported here focused on performance aspects of human-robot interaction involving ground robots (i.e., unmanned ground vehicles, or UGVs) during reconnaissance tasks. In particular, this study examined how differences in operator spatial ability and in operator workload and attention interacted to affect spatial awareness during human-robot interaction (HRI). Operator spatial abilities were systematically manipulated through the use of mental transformation training. Additionally, operator workload and attention were manipulated via the use of three different levels of automation (i.e., manual control, decision support, and full automation). Operator spatial awareness was measured by the size of errors made by the operators, when they were tasked to infer the robot's location from on-board camera views at three different points in a sequence of robot movements through a simulated military operation in urban terrain (MOUT) environment. The results showed that mental transformation training increased two areas of spatial ability, namely mental rotation and spatial visualization. Further, spatial ability in these two areas predicted performance in vehicle localization during the reconnaissance task. Finally, assistive automation showed a benefit with respect to operator workload, situation awareness, and subsequently performance. Together, the results of the study have implications with respect to the design of robots, function allocation between robots and operators, and training for spatial ability. Future research should investigate the interactive effects on operator spatial awareness of spatial ability, spatial ability training, and other variables affecting operator workload and attention.
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Date Issued
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2006
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Identifier
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CFE0001468, ucf:47102
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0001468
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Title
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MODERATORS OF TRUST AND RELIANCE ACROSS MULTIPLE DECISION AIDS.
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Creator
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Ross, Jennifer, Szalma, James, University of Central Florida
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Abstract / Description
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The present work examines whether user's trust of and reliance on automation, were affected by the manipulations of user's perception of the responding agent. These manipulations included agent reliability, agent type, and failure salience. Previous work has shown that automation is not uniformly beneficial; problems can occur because operators fail to rely upon automation appropriately, by either misuse (overreliance) or disuse (underreliance). This is because operators often face...
Show moreThe present work examines whether user's trust of and reliance on automation, were affected by the manipulations of user's perception of the responding agent. These manipulations included agent reliability, agent type, and failure salience. Previous work has shown that automation is not uniformly beneficial; problems can occur because operators fail to rely upon automation appropriately, by either misuse (overreliance) or disuse (underreliance). This is because operators often face difficulties in understanding how to combine their judgment with that of an automated aid. This difficulty is especially prevalent in complex tasks in which users rely heavily on automation to reduce their workload and improve task performance. However, when users rely on automation heavily they often fail to monitor the system effectively (i.e., they lose situation awareness a form of misuse). However, if an operator realizes a system is imperfect and fails, they may subsequently lose trust in the system leading to underreliance. In the present studies, it was hypothesized that in a dual-aid environment poor reliability in one aid would impact trust and reliance levels in a companion better aid, but that this relationship is dependent upon the perceived aid type and the noticeability of the errors made. Simulations of a computer-based search-and-rescue scenario, employing uninhabited/unmanned ground vehicles (UGVs) searching a commercial office building for critical signals, were used to investigate these hypotheses. Results demonstrated that participants were able to adjust their reliance and trust on automated teammates depending on the teammate's actual reliability levels. However, as hypothesized there was a biasing effect among mixed-reliability aids for trust and reliance. That is, when operators worked with two agents of mixed-reliability, their perception of how reliable and to what degree they relied on the aid was effected by the reliability of a current aid. Additionally, the magnitude and direction of how trust and reliance were biased was contingent upon agent type (i.e., 'what' the agents were: two humans, two similar robotic agents, or two dissimilar robot agents). Finally, the type of agent an operator believed they were operating with significantly impacted their temporal reliance (i.e., reliance following an automation failure). Such that, operators were less likely to agree with a recommendation from a human teammate, after that teammate had made an obvious error, than with a robotic agent that had made the same obvious error. These results demonstrate that people are able to distinguish when an agent is performing well but that there are genuine differences in how operators respond to agents of mixed or same abilities and to errors by fellow human observers or robotic teammates. The overall goal of this research was to develop a better understanding how the aforementioned factors affect users' trust in automation so that system interfaces can be designed to facilitate users' calibration of their trust in automated aids, thus leading to improved coordination of human-automation performance. These findings have significant implications to many real-world systems in which human operators monitor the recommendations of multiple other human and/or machine systems.
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Date Issued
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2008
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Identifier
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CFE0002077, ucf:47579
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0002077
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Title
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ADAPTIVE TECHNOMYTHOGRAPHY: THE APOTHEOSIS OF MACHINE AND DEVELOPMENT OF LEGEND IN A SYSTEM OF DYNAMIC TECHNOLOGY.
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Creator
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wolf, roger, Robinson, Brady, University of Central Florida
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Abstract / Description
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Human beings will effectively deify any suitably complex system that cannot be explained through basic haptic interaction. Our culture loves technology. These days it seems we need it to feel whole. In an effort to explore the development of mythology and modular aesthetic in a technological age I have designed and constructed a number of interactive robotic 'organisms' to engage in arbitrary movement in geometric enclosures. Through observation and dialog I seek to assess the extent...
Show moreHuman beings will effectively deify any suitably complex system that cannot be explained through basic haptic interaction. Our culture loves technology. These days it seems we need it to feel whole. In an effort to explore the development of mythology and modular aesthetic in a technological age I have designed and constructed a number of interactive robotic 'organisms' to engage in arbitrary movement in geometric enclosures. Through observation and dialog I seek to assess the extent to which people assign human characteristics to the random and oft times aberrant mechanical behavior. To supplement this endeavor, a fictional astrological system that proposes logical (albeit mythological) explanations for the peculiarities in these relationships has been created.
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Date Issued
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2007
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Identifier
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CFE0001677, ucf:47197
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0001677
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Title
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THE EFFECTS OF AN INCREASING FEDERAL MINIMUM WAGE ON FEDERAL UNEMPLOYMENT AND JOB AUTOMATION LEVELS.
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Creator
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Krayeski, Kiana, Hofler, Richard, University of Central Florida
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Abstract / Description
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The industrial revolution was the start of increasing technological advancements that are continuing to grow today. Technology improves accuracy, efficiency and is more productive in comparison to human labor as it does not require breaks and cannot violate any labor laws. With many innovations available today, firms have more options to choose from and can select the relatively cheaper solution. The push for a fifteen-dollar minimum wage affects the firm's options, and the use of technology...
Show moreThe industrial revolution was the start of increasing technological advancements that are continuing to grow today. Technology improves accuracy, efficiency and is more productive in comparison to human labor as it does not require breaks and cannot violate any labor laws. With many innovations available today, firms have more options to choose from and can select the relatively cheaper solution. The push for a fifteen-dollar minimum wage affects the firm's options, and the use of technology might increasingly become the more viable choice. This study took data from the years 1993 to 2016 and created two regressions using the unemployment rate and job automation rate as the dependent variables. The independent variables looked at were the year, the population growth rate, the minimum wage, inflation, the gross domestic product growth rate, and the consumer price index. After normality checks and transformations were done two regressions were run, and the models were studied to determine the effects. Both regressions were found to be valid with f-statistics lower than one percent. All the statistically significant variables were retained in the model, and the insignificant variables were omitted to reproduce the regression and check for accuracy. The models with the lower Akaike's information criterion and Bayesian information criterion values were kept and used as the final models. Overall the regressions found that the year and consumer price index had the most substantial effects on the unemployment rate, and the consumer price index had the strongest effect on the automation rate. Limitations on the study include the data available, a possible lag in the effect of the minimum wage, and the possible inaccuracy in using industrial robot installation as a measure for job automation.
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Date Issued
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2018
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Identifier
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CFH2000424, ucf:45778
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFH2000424
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Title
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DYNAMIC TASK ALLOCATION IN MOBILE ROBOT SYSTEMS USING UTILITY FUNTIONS.
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Creator
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Vander Weide, Scott, Bölöni, Ladislau, University of Central Florida
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Abstract / Description
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We define a novel algorithm based on utility functions for dynamically allocating tasks to mobile robots in a multi-robot system. The algorithm attempts to maximize the performance of the mobile robot while minimizing inter-robot communications. The algorithm takes into consideration the proximity of the mobile robot to the task, the priority of the task, the capability required by the task, the capabilities of the mobile robot, and the rarity of the capability within the population of mobile...
Show moreWe define a novel algorithm based on utility functions for dynamically allocating tasks to mobile robots in a multi-robot system. The algorithm attempts to maximize the performance of the mobile robot while minimizing inter-robot communications. The algorithm takes into consideration the proximity of the mobile robot to the task, the priority of the task, the capability required by the task, the capabilities of the mobile robot, and the rarity of the capability within the population of mobile robots. We evaluate the proposed algorithm in a simulation study and compare it to alternative approaches, including the contract net protocol, an approach based on the knapsack problem, and random task selection. We find that our algorithm outperforms the alternatives in most metrics measured including percent of tasks complete, distance traveled per completed task, fairness of execution, number of communications, and utility achieved.
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Date Issued
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2008
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Identifier
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CFE0002274, ucf:47871
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0002274
Pages