微分可能プランニングによるシャドウプログラム反転：ロボットプログラムのパラメータと軌道を統合最適化するフレームワーク
Shadow Program Inversion with Differentiable Planning: A Framework for Unified Robot Program Parameter and Trajectory Optimization
微分可能な衝突回避動作計画器DGPMP2-NDを組み込み、ロボットプログラムのパラメータと軌道を一階勾配法で同時最適化するSPI-DPを提案し、家庭用・産業用タスクで評価した。
著者: Benjamin Alt, Claudius Kienle, Darko Katic, Rainer Jäkel, Michael Beetz
分類: cs.RO, cs.AI
原文アブストラクト
This paper presents SPI-DP, a novel first-order optimizer capable of optimizing robot programs with respect to both high-level task objectives and motion-level constraints. To that end, we introduce DGPMP2-ND, a differentiable collision-free motion planner for serial N-DoF kinematics, and integrate it into an iterative, gradient-based optimization approach for generic, parameterized robot program representations. SPI-DP allows first-order optimization of planned trajectories and program parameters with respect to objectives such as cycle time or smoothness subject to e.g. collision constraints, while enabling humans to understand, modify or even certify the optimized programs. We provide a comprehensive evaluation on two practical household and industrial applications.
