Efficient Humanoid Contact Planning using Learned Centroidal Dynamics Prediction
Efficient Humanoid Contact Planning using Learned Centroidal Dynamics Prediction
复制标题
使用学习质心动力学预测进行高效的人形接触规划
DOI:
10.1109/icra.2019.8794032
复制
发表时间:
2019
期刊:
影响因子:
--
通讯作者:
Berenson, Dmitry
中科院分区:
文献类型:
--
作者:
Lin, Yu-Chi;Ponton, Brahayam;Righetti, Ludovic;Berenson, Dmitry
Humanoid robots dynamically navigate an environment by interacting with it via contact wrenches exerted at intermittent contact poses. Therefore, it is important to consider dynamics when planning a contact sequence. Traditional contact planning approaches assume a quasi-static balance criterion to reduce the computational challenges of selecting a contact sequence over a rough terrain. This however limits the applicability of the approach when dynamic motions are required, such as when walking down a steep slope or crossing a wide gap. Recent methods overcome this limitation with the help of efficient mixed integer convex programming solvers capable of synthesizing dynamic contact sequences. Nevertheless, its exponential-time complexity limits its applicability to short time horizon contact sequences within small environments. In this paper, we go beyond current approaches by learning a prediction of the dynamic evolution of the robot centroidal momenta, which can then be used for quickly generating dynamically robust contact sequences for robots with arms and legs using a search-based contact planner. We demonstrate the efficiency and quality of the results of the proposed approach in a set of dynamically challenging scenarios.
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DOI:
10.1109/humanoids.2017.8239531
发表时间:
2017
期刊:
2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)
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作者:
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2016
期刊:
2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids)
影响因子:
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通讯作者:
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期刊:
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影响因子:
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