Parallel Fault-Tolerant Robot Control

As robot tasks in space, nuclear, and medical environments become more widespread, the issues of reliability and safety for robots are becoming more critical. Attempts to address these issues have resulted in a recent surge of activity in robot fault tolerance. This research effort concentrates on fault tolerance in the robot controller, and highlights the importance and potential of multiprocessor control architectures from the fault tolerance perspective. The issue of performance versus reliability is also addressed.

Most robot controllers today employ a single processor architecture. As robot control requirements become more complex, these serial controllers have difficulty providing the desired response time. Additionally, with robots being used in environments that are hazardous or inaccessible to humans, fault-tolerant robotic systems are particularly desirable. Use of multiple processors for robot control offers two advantages over single processor systems. Parallel control provides a faster response, which in turn allows a finer granularity of control. Processor fault tolerance is also made possible by the existence of multiple processors. There is a trade-off between performance and the level of fault tolerance provided. We have developed a shared memory multiprocessor robot controller that is capable of providing high performance and processor fault tolerance. This controller demonstrates how performance and processor fault tolerance can be balanced in a cost-effective manner.

This research wa a joint effort with Prof. Ian Walker, and represents the doctoral thesis work of Dierdre Hamilton.

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