Quadratically Convergent Algorithms for Optimal Dextrous Hand Grasping
There is a robotic balancing task, namely real-time dextrous-hand grasping, for which linearly constrained, positive definite programming gives a quite satisfactory solution from an engineering point of view. We here propose refinements of this approach to reduce the computational effort. The refinements include elimination of structural constraints in the positive definite matrices, orthogonalization of the grasp maps, and giving a precise Newton step size selection rule.
|Collections||ANU Research Publications|
|Source:||IEEE Transactions on Robotics and Automation|
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