Predictable Motion of Hyper-redundant Manipulators Using Constrained Optimization Control
Markus P.J. Fromherz and Warren B. Jackson
Abstract
Hyper-redundant robotic manipulators are robots that have many more
degrees of freedom than required for a typical task such as grasping
an object in 3D space. The large number of joints, which may range
from dozens to thousands, offers both opportunities and challenges for
the control of such robots. An opportunity is to use the extra degrees
of freedom to optimally control multiple objectives. A challenge is to
deliver predictable behavior despite the large number of possible
configurations. In this paper, we propose to use a control approach
based on constrained optimization. We discuss a representative example
for an under-constrained task and suggest and analyze possible
solutions that ensure predictable behavior.
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