Abstract
In this paper, we consider an optimization problem of the grasping manipulation of multi-fingered hand-arm robots. We first formulate an optimization model for the problem, based on the dynamic equations of the object and the friction constraints. Then, we reformulate the model as a convex quadratic programming over circular cones. Moreover, we propose a primal-dual interior-point algorithm based on the kernel function to solve this convex quadratic programming over circular cones. We derive both the convergence of the algorithm and the iteration bounds for large- and small-update methods, respectively. Finally, we carry out the numerical tests of $$180^{\circ }$$ and $$90^{\circ }$$ manipulations of the hand-arm robot to demonstrate the effectiveness of the proposed algorithm.
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