You are here

UCF Digital Collections ยป ETD Collection

Smart Grasping using Laser and Tactile Array Sensors for UCF-MANUS- An Intelligent Assistive Robotic Manipulator

Download pdf | Full Screen View

Date Issued:
2016
Abstract/Description:
This thesis presents three improvements in the UCF MANUS Assistive Robotic Manipulator's grasping abilities. Firstly, the robot can now grasp objects that are deformable, heavy and have uneven contact surfaces without undergoing slippage during robotic operations, e.g. paper cup, filled water bottle. This is achieved by installing a high precision non-contacting Laser sensor1 that runs with an algorithm that processes raw-input data from the sensor, registers smallest variation in the relative position of the object with respect to the gripper. Secondly, the robot can grasp objects that are as light and small as single cereal grain without deforming it. To achieve this a MEMS Barometer based tactile sensor array device that can measure force that are as small as 1 gram equivalent is embedded into the gripper to enhance pressure sensing capabilities. Thirdly, the robot gripper gloves are designed aesthetically and conveniently to accommodate existing and newly added sensors using a 3D printing technology that uses light weight ABS plastic as a fabrication material. The newly designed system was experimented and found that a high degree of adaptability for different kinds of objects can be attained with a better performance than the previous system.
Title: Smart Grasping using Laser and Tactile Array Sensors for UCF-MANUS- An Intelligent Assistive Robotic Manipulator.
54 views
31 downloads
Name(s): Prakash, Kiran, Author
Behal, Aman, Committee Chair
Boloni, Ladislau, Committee Member
Haralambous, Michael, Committee Member
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2016
Publisher: University of Central Florida
Language(s): English
Abstract/Description: This thesis presents three improvements in the UCF MANUS Assistive Robotic Manipulator's grasping abilities. Firstly, the robot can now grasp objects that are deformable, heavy and have uneven contact surfaces without undergoing slippage during robotic operations, e.g. paper cup, filled water bottle. This is achieved by installing a high precision non-contacting Laser sensor1 that runs with an algorithm that processes raw-input data from the sensor, registers smallest variation in the relative position of the object with respect to the gripper. Secondly, the robot can grasp objects that are as light and small as single cereal grain without deforming it. To achieve this a MEMS Barometer based tactile sensor array device that can measure force that are as small as 1 gram equivalent is embedded into the gripper to enhance pressure sensing capabilities. Thirdly, the robot gripper gloves are designed aesthetically and conveniently to accommodate existing and newly added sensors using a 3D printing technology that uses light weight ABS plastic as a fabrication material. The newly designed system was experimented and found that a high degree of adaptability for different kinds of objects can be attained with a better performance than the previous system.
Identifier: CFE0006164 (IID), ucf:51119 (fedora)
Note(s): 2016-05-01
M.S.E.E.
Engineering and Computer Science, Electrical Engineering and Computer Engineering
Masters
This record was generated from author submitted information.
Subject(s): Tactile Array -- MEMS Sensor -- Laser Sensor -- Smart Grasping -- Robot Manipulator -- MANUS -- Assistive Robotics -- Autonomous -- WMRAs
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0006164
Restrictions on Access: campus 2017-05-15
Host Institution: UCF

In Collections