ポテンシャル場法を統合した動的衝突回避のためのリアルタイムUAV軌道最適化
An Integrated Real-time UAV Trajectory Optimization with Potential Field Approach for Dynamic Collision Avoidance
チェビシェフ擬スペクトル法による軌道最適化と人工ポテンシャル場法を並列に組み合わせ、UAVのリアルタイム軌道計画と動的衝突回避を実現する手法を提案し、屋内実験で検証した。
著者: D. M. K. K. Venkateswara Rao, Hamed Habibi, Jose Luis Sanchez-Lopez, Holger Voos
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
This paper presents an integrated approach that combines trajectory optimization and Artificial Potential Field (APF) method for real-time optimal Unmanned Aerial Vehicle (UAV) trajectory planning and dynamic collision avoidance. A minimum-time trajectory optimization problem is formulated with initial and final positions as boundary conditions and collision avoidance as constraints. It is transcribed into a nonlinear programming problem using Chebyshev pseudospectral method. The state and control histories are approximated by using Lagrange polynomials and the collocation points are used to satisfy constraints. A novel sigmoid-type collision avoidance constraint is proposed to overcome the drawbacks of Lagrange polynomial approximation in pseudospectral methods that only guarantees inequality constraint satisfaction only at nodal points. Automatic differentiation of cost function and constraints is used to quickly determine their gradient and Jacobian, respectively. An APF method is used to update the optimal control inputs for guaranteeing collision avoidance. The trajectory optimization and APF method are implemented in a closed-loop fashion continuously, but in parallel at moderate and high frequencies, respectively. The initial guess for the optimization is provided based on the previous solution. The proposed approach is tested and validated through indoor experiments.
