行列リー群上の剛体に対するリーマン直接軌道最適化
Riemannian Direct Trajectory Optimization of Rigid Bodies on Matrix Lie Groups
剛体の軌道最適化をリー群上で行うリーマン最適化フレームワークを提案し、特異点を避けつつ従来法より桁違いに高速化した。
詳しい要約
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著者: Sangli Teng, Tzu-Yuan Lin, William A Clark, Ram Vasudevan, Maani Ghaffari
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
Designing dynamically feasible trajectories for rigid bodies is a fundamental problem in robotics. Although direct trajectory optimization is widely applied to solve this problem, inappropriate parameterizations of rigid body dynamics often result in slow convergence and violations of the intrinsic topological structure of the rotation group. This paper introduces a Riemannian optimization framework for direct trajectory optimization of rigid bodies. We first use the Lie Group Variational Integrator to formulate the discrete rigid body dynamics on matrix Lie groups. We then derive the closed-form first- and second-order Riemannian derivatives of the dynamics. Finally, this work applies a line-search Riemannian Interior Point Method (RIPM) to perform trajectory optimization with general nonlinear constraints. As the optimization is performed on matrix Lie groups, it is correct-by-construction to respect the topological structure of the rotation group and be free of singularities. The paper demonstrates that both the derivative evaluations and Newton steps required to solve the RIPM exhibit linear complexity with respect to the planning horizon and system degrees of freedom. Simulation results illustrate that the proposed method is faster than conventional methods by an order of magnitude in challenging robotics tasks.
