  Robots using cellular-like redundant binary actuators could outmatch
electric-gearmotor robotic systems in terms of reliability, force-to-weight
ratio and cost. This paper presents a robust fault tolerant control scheme that
is designed to meet the control challenges encountered by such robots, i.e.,
discrete actuator inputs, complex system modeling and cross-coupling between
actuators. In the proposed scheme, a desired vectorial system output, such as a
position or a force, is commanded by recruiting actuators based on their
influence vectors on the output. No analytical model of the system is needed;
influence vectors are identified experimentally by sequentially activating each
actuator. For position control tasks, the controller uses a probabilistic
approach and a genetic algorithm to determine an optimal combination of
actuators to recruit. For motion control tasks, the controller uses a sliding
mode approach and independent recruiting decision for each actuator.
Experimental results on a four degrees of freedom binary manipulator with
twenty actuators confirm the method's effectiveness, and its ability to
tolerate massive perturbations and numerous actuator failures.
