Titlebook: Algorithmic Foundations of Robotics VIII; Selected Contributio Gregory S. Chirikjian,Howie Choset,Todd Murphey Book 2010 Springer-Verlag Be

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https://doi.org/10.1007/978-3-319-49778-5hand modeling.We demonstrate the technique first with a detailed exposition of modeling an index finger, and then extend the model to a full hand with 19 rigid bodies and 23 muscle strands. We end with a discussion of future work, including the need for impact handling, surface friction representations, and system identification.

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https://doi.org/10.1057/9781137513410 finding a best path. Preliminary experimental results show that our approach is highly effective: our BURM algorithm is at least 40 times faster than an algorithm that tries to evaluate collision probabilities exactly, and it is not much slower than classic probabilistic roadmap planning algorithms, which ignore uncertainty in environment maps.

GRIEF

recession

刺激

bypass

Perceived CT-Space for Motion Planning in Unknown and Unpredictable Environmentst to uncertainties in obstacle behaviors. The introduced method can be used in general by real-time motion planners for high-DOF robots to discover the existence of guaranteed collision-free future motions efficiently. The utility is further confirmed both in simulation and in real-world testing involving a 5-DOF robot manipulator.

現(xiàn)代

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