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NONLINEAR ESTIMATION AND CONTROL FOR ASSISTIVE ROBOTS
Title
NONLINEAR ESTIMATION AND CONTROL FOR ASSISTIVE ROBOTS.
Creator
Wang, Zhao, Behal, Aman, University of Central Florida
Abstract / Description
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
2011
Identifier
CFE0003889, ucf:48755
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0003889
COVERAGE PATH PLANNING AND CONTROL FOR AUTONOMOUS MOBILE ROBOTS
Title
COVERAGE PATH PLANNING AND CONTROL FOR AUTONOMOUS MOBILE ROBOTS.
Creator
balakrishnan, mohanakrishnan, Guo, Yi, University of Central Florida
Abstract / Description
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
2005
Identifier
CFE0000641, ucf:46497
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000641
Interactive Perception in Robotics
Title
Interactive Perception in Robotics.
Creator
Baghbahari Baghdadabad, Masoud, Behal, Aman, Haralambous, Michael, Lin, Mingjie, Sukthankar, Gita, Xu, Yunjun, University of Central Florida
Abstract / Description
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
2019
Identifier
CFE0007780, ucf:52361
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007780
INTEGRATION OF COMMUNICATION CONSTRAINTS INTO PHYSIOCOMIMETICSWARMS VIA PLACEMENT OF LOCATION BASED VIRTUAL PARTICLES
Title
INTEGRATION OF COMMUNICATION CONSTRAINTS INTO PHYSIOCOMIMETICSWARMS VIA PLACEMENT OF LOCATION BASED VIRTUAL PARTICLES.
Creator
Haley, Joshua, Wiegand, R. Paul, University of Central Florida
Abstract / Description
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
2011
Identifier
CFH0003812, ucf:44747
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFH0003812
AUTONOMOUS ROBOTIC AUTOMATION SYSTEMWITH VISION FEEDBACK
Title
AUTONOMOUS ROBOTIC AUTOMATION SYSTEMWITH VISION FEEDBACK.
Creator
Rosino, Jeffery, Qu, Zhihua, University of Central Florida
Abstract / Description
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
2004
Identifier
CFE0000277, ucf:46220
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000277
Nonlinear Control Synthesis for Facilitation of Human-Robot Interaction
Title
Nonlinear Control Synthesis for Facilitation of Human-Robot Interaction.
Creator
Ding, Zhangchi, Behal, Aman, Pourmohammadi Fallah, Yaser, Haralambous, Michael, Boloni, Ladislau, Xu, Yunjun, University of Central Florida
Abstract / Description
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
2019
Identifier
CFE0007798, ucf:52360
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007798
THE EFFECTS ON OPERATOR PERFORMANCE AND WORKLOAD WHEN GUNNERY AND ROBOTIC CONTROL TASKS ARE PERFORMED CONCURRENTLY
Title
THE EFFECTS ON OPERATOR PERFORMANCE AND WORKLOAD WHEN GUNNERY AND ROBOTIC CONTROL TASKS ARE PERFORMED CONCURRENTLY.
Creator
Joyner, Carla, McCauley-Bell, Pamela, University of Central Florida
Abstract / Description
The purpose of this research was to examine operator workload and performance in a high risk, multi-task environment. Specifically, the research examined if a gunner of a Future Combat System, such as a Mounted Combat System, could effectively detect targets in the immediate environment while concurrently operating robotic assets in a remote environment. It also analyzed possible effects of individual difference factors, such as spatial ability and attentional control, on operator performance...
Show moreThe purpose of this research was to examine operator workload and performance in a high risk, multi-task environment. Specifically, the research examined if a gunner of a Future Combat System, such as a Mounted Combat System, could effectively detect targets in the immediate environment while concurrently operating robotic assets in a remote environment. It also analyzed possible effects of individual difference factors, such as spatial ability and attentional control, on operator performance and workload. The experimental conditions included a gunner baseline and concurrent task conditions where participants simultaneously performed gunnery tasks and one of the following tasks: monitor an unmanned ground vehicle (UGV) via a video feed (Monitor), manage a semi-autonomous UGV, and teleoperate a UGV (Teleop). The analysis showed that the asset condition significantly impacted gunnery performance with the gunner baseline having the highest number of targets detected (M = 13.600 , SD = 2.353), and concurrent Teleop condition the lowest (M = 9.325 , SD = 2.424). The research also found that high spatial ability participants tended to detect more targets than low spatial ability participants. Robotic task performance was also affect by the asset condition. The results showed that the robotic target detection rate was lower for the concurrent task conditions. A significant difference was seen between the UGV-baseline (80.1%) when participants performed UGV tasks only and UGV-concurrent conditions (67.5%) when the participants performed UGV tasks concurrently with gunnery tasks. Overall, this study revealed that there were performance decrements for the gunnery tasks as well as the robotic tasks when the tasks were performed concurrently.
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Date Issued
2006
Identifier
CFE0000979, ucf:46704
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000979
Bio-Inspired Visual Servo Control of a Picking Mechanism in an Agricultural Ground Robot
Title
Bio-Inspired Visual Servo Control of a Picking Mechanism in an Agricultural Ground Robot.
Creator
Defterli, Sinem, Xu, Yunjun, Kauffman, Jeffrey L., Lin, Kuo-Chi, Song, Sang-Eun, Zheng, Qipeng, University of Central Florida
Abstract / Description
For a recently constructed disease detection agricultural ground robot, the segregation of unhealthy leaves fromstrawberry plants is a major task of the robot's manipulation subsystem in field operations. In this dissertation, the motion planning of a custom-designedpicking mechanism in the ground robot's subsystem is studied in two sections. First, a set of analytical, suboptimal semi-analyticaland numerical algorithms are studied to solve the inverse kinematics problem of the handling...
Show moreFor a recently constructed disease detection agricultural ground robot, the segregation of unhealthy leaves fromstrawberry plants is a major task of the robot's manipulation subsystem in field operations. In this dissertation, the motion planning of a custom-designedpicking mechanism in the ground robot's subsystem is studied in two sections. First, a set of analytical, suboptimal semi-analyticaland numerical algorithms are studied to solve the inverse kinematics problem of the handling mechanism in firmcircumstances. These premeditated approaches are built on the computation of the joint variables by an identified 3Dposition data of the target leaf only. The outcomes of the three solution algorithms are evaluated in terms of the performanceindexes of energy change and the CPU time cost. The resultant postures of the mechanism for different target pointlocations are observed both in simulations and the hardware experiments with each IK solution. Secondly, after the manipulation task of the mechanism via the proposed inverse kinematicalgorithms is performed, some compensation may be needed due to the sudden and unpredicted deviation of the targetposition under field conditions.For the purpose of finding optimal joint values under certain constraints, a trajectory optimization problem in image-based visual servoing method via the camera-in-handconfiguration is initiated when the end-effector is in the close proximity of the target leaf. In this part of the study, a bio-inspired trajectory optimization problem in image-basedvisual servoing method is constructed based on the mathematical model derived from the prey-predatorrelationships in nature. In this biological phenomenon, the predator constructs its path in a certain subspace whilecatching the prey. When this motion strategy is applied to trajectory optimization problems, it causes a significantreduce in the computation cost since it finds the optimum solution in a certain manifold. The performance of the introducedbio-inspired trajectory optimization in visual servoing is validated with the hardware experiments both in laboratory settings and in fieldconditions.
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Date Issued
2018
Identifier
CFE0007170, ucf:52247
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007170