Ashraf Bader
Ph.D. FinalJan 27, 2021, 12:00 pm - 2:00 pm
Online
Design and Control of Kinematically Redundant Robots for Maximizing Failure-Tolerant Workspaces
Abstract: Kinematically redundant robots have extra degrees of freedom so that they can tolerate a joint failure and still complete an assigned task. Previous work has defined the “failure-tolerant workspace” as the workspace that is guaranteed to be reachable both before and after an arbitrary locked-joint failure. One mechanism for maximizing this workspace is to employ optimal artificial joint limits prior to a failure. This dissertation presents two techniques for determining these optimal artificial joint limits. The first technique is based on the gradient ascent method. The proposed technique is able to deal with the discontinuities of the gradient that are due to changes in the boundaries of the failure tolerant workspace. This technique is illustrated using two examples of three degree-of-freedom planar serial robots. The first example is an equal link length robot where the optimal artificial joint limits are computed exactly. In the second example, both the link lengths and artificial joint limits are determined, resulting in a robot design that has more than twice the failure-tolerant area of previously published locally optimal designs. The second technique presented in this dissertation is a novel hybrid technique for estimating the failure-tolerant workspace size for robots of arbitrary kinematic structure and any number of degrees of freedom performing tasks in a 6D workspace. The method presented combines an algorithm for computing self-motion manifold ranges to estimate workspace envelopes and Monte-Carlo integration to estimate orientation volumes to create a computationally efficient algorithm. This algorithm is then combined with the coordinate ascent optimization technique to determine optimal artificial joint limits that maximize the size of the failure-tolerant workspace of a given robot. This approach is illustrated on multiple examples of robots that perform tasks in 3D planar and 6D spatial workspace.
Adviser: Anthony Maciejewski
Co-Adviser: N/A
Non-ECE Member: Juliana Oprea, Mathematics
Member 3: Ali Pezeshki, Electrical and Computer Engineering
Addional Members: Peter Young
Co-Adviser: N/A
Non-ECE Member: Juliana Oprea, Mathematics
Member 3: Ali Pezeshki, Electrical and Computer Engineering
Addional Members: Peter Young
Publications:
A. M. Bader and A. A. Maciejewski, “Maximizing the failure-tolerant workspace area for planar redundant robots,” Mechanism and Machine Theory, vol. 143, p. 103635, 2020.
A. M. Bader and A. A. Maciejewski, “A hybrid approach for estimating the failure-tolerant workspace size of kinematically redundant robots,” IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 303-310, 2020
A. M. Bader and A. A. Maciejewski, “Maximizing the failure-tolerant workspace area for planar redundant robots,” Mechanism and Machine Theory, vol. 143, p. 103635, 2020.
A. M. Bader and A. A. Maciejewski, “A hybrid approach for estimating the failure-tolerant workspace size of kinematically redundant robots,” IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 303-310, 2020
Program of Study:
ECE-481
MATH-560
ECE-520
ECE-555
ECE-611
ECE-666
CIS-600
N/A
ECE-481
MATH-560
ECE-520
ECE-555
ECE-611
ECE-666
CIS-600
N/A