ロボット運動の加速度ベース設計のための幾何学的ファブリック
Geometric Fabrics for the Acceleration-based Design of Robotic Motion
RMPを一般化した最適化ファブリックの具体形である幾何学的ファブリックを用い、障害物回避や関節限界回避などを層状に組み合わせて安定性保証付きの反応的ロボット運動を設計する手法を提案した。
著者: Mandy Xie, Karl Van Wyk, Anqi Li, Muhammad Asif Rana, Qian Wan, Dieter Fox, Byron Boots, Nathan Ratliff
分類: cs.RO
原文アブストラクト
This paper describes the pragmatic design and construction of geometric fabrics for shaping a robot's task-independent nominal behavior, capturing behavioral components such as obstacle avoidance, joint limit avoidance, redundancy resolution, global navigation heuristics, etc. Geometric fabrics constitute the most concrete incarnation of a new mathematical formulation for reactive behavior called optimization fabrics. Fabrics generalize recent work on Riemannian Motion Policies (RMPs); they add provable stability guarantees and improve design consistency while promoting the intuitive acceleration-based principles of modular design that make RMPs successful. We describe a suite of mathematical modeling tools that practitioners can employ in practice and demonstrate both how to mitigate system complexity by constructing behaviors layer-wise and how to employ these tools to design robust, strongly-generalizing, policies that solve practical problems one would expect to find in industry applications. Our system exhibits intelligent global navigation behaviors expressed entirely as provably stable fabrics with zero planning or state machine governance.
