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 keepout 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.

翻译：本文提出了一种计算高效模型预测控制框架，采用积分切比雪夫配点法实现自主智能体的快速操作。通过构建有限时域最优控制问题并递归重评估最优轨迹，将状态与控制误差的L2范数最小化问题转化为二次规划形式。控制变量与状态变量约束通过切比雪夫多项式进行参数化，并整合至最优轨迹生成程序中，以纳入执行器限制与禁入区域约束。利用多面体可微碰撞检测机制实现最优避障。在边缘计算机上将配点法所得结果与现有方法进行基准测试，以展现性能提升。最后，通过多智能体空间系统协同控制场景验证所提方案的技术优势。