Predictable motion of hyper-redundant manipulators using constrained optimization control

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.