サンプリングと最適化を組み合わせた脚車輪ロボットの計画手法
Combined Sampling and Optimization Based Planning for Legged-Wheeled Robots
サンプリングで全身姿勢と接地スケジュールを求め、その初期解を最適化に渡すことで不整地でも脚車輪ロボットの計画を安定して行える手法を提案した。
著者: Edo Jelavic, Farbod Farshidian, Marco Hutter
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
Planning for legged-wheeled machines is typically done using trajectory optimization because of many degrees of freedom, thus rendering legged-wheeled planners prone to falling prey to bad local minima. We present a combined sampling and optimization-based planning approach that can cope with challenging terrain. The sampling-based stage computes whole-body configurations and contact schedule, which speeds up the optimization convergence. The optimization-based stage ensures that all the system constraints, such as non-holonomic rolling constraints, are satisfied. The evaluations show the importance of good initial guesses for optimization. Furthermore, they suggest that terrain/collision (avoidance) constraints are more challenging than the robot model's constraints. Lastly, we extend the optimization to handle general terrain representations in the form of elevation maps.
