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.
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© 2012 Springer-Verlag Berlin Heidelberg
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Nazari, V., Notash, L. (2012). Motion Recovery of Parallel Manipulators Using Task-Decomposition Approach. In: Su, CY., Rakheja, S., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2012. Lecture Notes in Computer Science(), vol 7508. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33503-7_23
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DOI: https://doi.org/10.1007/978-3-642-33503-7_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33502-0
Online ISBN: 978-3-642-33503-7
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