Motion recovery of parallel manipulators using task-decomposition approach

Abstract

In this paper, the motion recovery of parallel manipulators is investigated. To achieve the desired performance, a failure recovery based on decomposing the task space of manipulator into the major and secondary subtasks is presented. The major subtasks are more important than the other subtasks and must be accomplished as precisely as possible. The secondary subtasks with less significance can be compromised to achieve secondary criteria such as optimizing measures of fault tolerance, singularity avoidance and obstacle avoidance. The task-decomposition approach minimizes the least square error of the vector of the major subtasks and at the same time optimizes the secondary criterion. © Springer-Verlag Berlin Heidelberg 2012.