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- W2969124493 abstract "We present a discrete-optimization technique for finding feasible robot arm trajectories that pass through provided 6-DOF Cartesian-space end-effector paths with high accuracy, a problem called pathwise-inverse kinematics. The output from our method consists of a path function of joint-angles that best follows the provided end-effector path function, given some definition of “best”. Our method, called Stampede, casts the robot motion translation problem as a discrete-space graph-search problem where the nodes in the graph are individually solved for using non-linear optimization; framing the problem in such a way gives rise to a well-structured graph that affords an effective best path calculation using an efficient dynamic-programming algorithm. We present techniques for sampling configuration space, such as diversity sampling and adaptive sampling, to construct the search-space in the graph. Through an evaluation, we show that our approach performs well in finding smooth, feasible, collision-free robot motions that match the input end-effector trace with very high accuracy, while alternative approaches, such as a state-of-the-art per-frame inverse kinematics solver and a global non-linear trajectory-optimization approach, performed unfavorably." @default.
- W2969124493 created "2019-08-22" @default.
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- W2969124493 date "2019-05-01" @default.
- W2969124493 modified "2023-09-23" @default.
- W2969124493 title "STAMPEDE: A Discrete-Optimization Method for Solving Pathwise-Inverse Kinematics" @default.
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- W2969124493 doi "https://doi.org/10.1109/icra.2019.8793617" @default.
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