用切比雪夫配置法实现快速轨迹优化，适合资源受限的自主系统。
A Rapid Trajectory Optimization and Control Framework for Resource-Constrained Applications
- 基于切比雪夫多项式参数化状态与控制变量，提升计算效率。
- 在边缘设备上实测性能优于现有方法，支持实时重规划。
- 支持多智能体协同控制，适用于航天器等高动态场景。
本文提出一种计算高效的模型预测控制框架，采用积分切比雪夫配点法，实现自主代理的快速操作。通过将有限时域最优控制问题与最优轨迹的递归重评估相结合，状态和控制误差的L2范数最小化被转化为二次规划问题。利用切比雪夫多项式对控制与状态变量约束进行参数化，并纳入轨迹生成过程，以处理执行器限制和禁入区域约束。采用可微分的多面体碰撞检测实现最优避障。通过在边缘计算机上的对比测试，验证了该方法相较于现有技术的性能提升。最后，考虑了涉及多智能体空间系统的协同控制场景，展示了所提方法的技术优势。
原文摘要 · Abstract (English)
This paper presents a computationally efficient model predictive control formulation that uses an integral Chebyshev collocation method to enable rapid operations of autonomous agents. By posing the finite-horizon optimal control problem and recursive re-evaluation of the optimal trajectories, minimization of the L2 norms of the state and control errors are transcribed into a quadratic program. Control and state variable constraints are parameterized using Chebyshev polynomials and are accommodated in the optimal trajectory generation programs to incorporate the actuator limits and keep-out constraints. Differentiable collision detection of polytopes is leveraged for optimal collision avoidance. Results obtained from the collocation methods are benchmarked against the existing approaches on an edge computer to outline the performance improvements. Finally, collaborative control scenarios involving multi-agent space systems are considered to demonstrate the technical merits of the proposed work.
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