Agent-based design of fault tolerant manipulators for satellite docking

A rapidly deployable fault tolerant manipulator system consists of modular hardware and support software that allow the user to quickly configure and deploy a fault tolerant manipulator that is custom-tailored for a given task. The main focus of this paper is on the task based design component of such a system, that is, the determination of the optimal manipulator configuration, its base position and the corresponding joint space trajectory for a given task. We introduce a novel agent-based solution approach to task based design and illustrate it with a fault tolerant manipulator design for a satellite docking operation aboard the space shuttle.

[1]  Christiaan J. J. Paredis,et al.  A rapidly deployable manipulator system , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[2]  D. Wolfe,et al.  Nonparametric Statistical Methods. , 1974 .

[3]  Heinz Mühlenbein,et al.  Parallel Genetic Algorithms in Combinatorial Optimization , 1992, Computer Science and Operations Research.

[4]  Christiaan J. J. Paredis,et al.  Fault Tolerant Task Execution through Global Trajectory Planning , 1996 .

[5]  Joel W. Burdick,et al.  Determining task optimal modular robot assembly configurations , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[6]  Christiaan J. J. Paredis,et al.  Designing Fault-Tolerant Manipulators: How Many Degrees of Freedom? , 1996, Int. J. Robotics Res..

[7]  Reiko Tanese,et al.  Distributed Genetic Algorithms , 1989, ICGA.

[8]  Heinz Muehlenbein.  Parallel Genetic Algorithm in Combinatorial Optimization , 1992 .

[9]  Douglas A. Wolfe,et al.  Nonparametric Statistical Methods , 1973 .

[10]  Ron Shonkwiler,et al.  Parallel Genetic Algorithms , 1993, ICGA.

[11]  Ari Juels,et al.  Stochastic Hillclimbing as a Baseline Method for , 1994 .

[12]  Pradeep K. Khosla,et al.  A Multi-population Genetic Algorithm And Its Application To Design Of Manipulators , 1992, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Lashon B. Booker,et al.  Proceedings of the fourth international conference on Genetic algorithms , 1991 .

[14]  Seshashayee Sankarshana Murthy.  Synergy in cooperating agents: designing manipulators from task specifications , 1992 .

[15]  Christiaan J. J. Paredis,et al.  Kinematic Design of Serial Link Manipulators From Task Specifications , 1993, Int. J. Robotics Res..

[16]  S. Baluja.  An Empirical Comparison of Seven Iterative and Evolutionary Function Optimization Heuristics , 1995 .

[17]  Christiaan J. J. Paredis,et al.  An agent-based approach to the design of rapidly deployable fault-tolerant manipulators , 1996 .

[18]  Christiaan J. J. Paredis,et al.  On kinematic design of serial link manipulators , 1991 .

[19]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1992, Artificial Intelligence.

[20]  Shane Farritor,et al.  A systems-level modular design approach to field robotics , 1996, Proceedings of IEEE International Conference on Robotics and Automation.