Graduation Year

2011

Document Type

Thesis

Degree

M.S.Cp.E.

Degree Granting Department

Computer Science and Engineering

Major Professor

Yu Sun, Ph.D.

Committee Member

Redwan Alqasemi, Ph.D.

Committee Member

Rajiv Dubey, Ph.D.

Committee Member

Srinivas Katkoori, Ph.D.

Keywords

Rehabilitation, Robotics, Mobile Manipulation, Visual Servoing, ADL

Abstract

The wheelchair-mounted robotic arm (WMRA) is a 9-degree of freedom (DoF) assistive system that consists of a 2-DoF modified commercial power wheelchair and a custom 7-DoF robotic arm. Kinematics and control methodology for the 9-DoF system that combine mobility and manipulation have been previously developed and implemented. This combined control allows the wheelchair and robotic arm to follow a single trajectory based on weighted optimizations. However, for the execution of activities of daily living (ADL) in the real-world environment, modified control techniques have been implemented.

In order to execute macro ADL tasks, such as a "go to and pick up" task, this work has implemented several control algorithms on the WMRA system. Visual servoing based on template matching and feature extraction allows the mobile platform to approach the desired goal object. Feature extraction based on scale-invariant feature transform (SIFT) gives the system object detection capabilities to recommend actions to the user and to orient the arm to grasp the goal object using visual servoing. Finally, a collision avoidance system is implemented to detect and avoid obstacles when the wheelchair platform is moving towards the goal object. These implementations allow the WMRA system to operate autonomously from the beginning of the task where the user selects the goal object, all the way to the end of the task where the task has been fully completed.

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