Towards Constraint-based Actuation Allocation for Hyper-redundant Manipulators

Markus P.J. Fromherz, Maia Hoeberechts, and Warren B. Jackson

Abstract

Hyper-redundant robotic manipulators are robots that have many more degrees of freedom than required for a task such as grasping an object in 3D space. The large number of joints, possibly ranging from dozens to thousands, offers both challenges and opportunities for control of such robots. A challenge is to develop algorithms that scale and adapt to different configurations while taking into account a variety of robot constraints. An opportunity is to use the extra degrees of freedom to optimally control multiple objectives. In this paper, we propose to use a control approach based on constrained optimization. We present robot and task models and discuss first results.

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