SL1M: Sparse L1-norm Minimization for contact planning on uneven terrain
SL1M: Sparse L1-norm Minimization for contact planning on uneven terrain
复制标题
SL1M：稀疏 L1 范数最小化，用于不平坦地形上的接触规划
DOI：
10.1109/icra40945.2020.9197371
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
A. Prete
中科院分区：
文献类型：
--
作者：
S. Tonneau;Daeun Song;Pierre Fernbach;N. Mansard;M. Taïx;A. Prete
在复杂环境中规划腿运动的主要挑战之一是组合接触选择问题。最近的贡献建议使用整数变量来表示选择的接触面，然后依靠现代的混合整数（MI）优化求解器来处理这个组合问题。为了减少MI的计算成本，我们利用L1范数最小化技术的稀疏性，放松接触规划问题成一个可行的线性规划。我们的方法占运动可达性的质量中心（COM）和接触效应器。我们确保存在一个准静态COM轨迹限制我们的计划准平面接触。对于规划10个步骤，每个阶段的潜在接触面少于10个，我们的方法比MI方法快50到100倍，这表明在线接触重新规划的潜在应用。该方法在仿真中演示了与类人机器人HRP-2和Talos在各种情况下。
One of the main challenges of planning legged locomotion in complex environments is the combinatorial contact selection problem. Recent contributions propose to use integer variables to represent which contact surface is selected, and then to rely on modern mixed-integer (MI) optimization solvers to handle this combinatorial issue. To reduce the computational cost of MI, we exploit the sparsity properties of L1 norm minimization techniques to relax the contact planning problem into a feasibility linear program. Our approach accounts for kinematic reachability of the center of mass (COM) and of the contact effectors. We ensure the existence of a quasi-static COM trajectory by restricting our plan to quasi-flat contacts. For planning 10 steps with less than 10 potential contact surfaces for each phase, our approach is 50 to 100 times faster that its MI counterpart, which suggests potential applications for online contact re-planning. The method is demonstrated in simulation with the humanoid robots HRP-2 and Talos over various scenarios.