In this article, an infinite-horizon optimal regulation problem is considered for a control-affine nonlinear autonomous agent subject to input constraints in the presence of dynamic avoidance regions. A local model-based approximate dynamic programming method is implemented to approximate the value function in a local neighborhood of the agent. By performing local approximations, prior knowledge of the locations of avoidance regions is not required. To alleviate the a priori knowledge of the number of avoidance regions in the operating domain, an extension is provided that modifies the value function approximation. The developed feedback-based motion planning strategy guarantees uniformly ultimately bounded convergence of the approximated control policy to the optimal policy while also ensuring the agent remains outside avoidance regions. Simulations are included to demonstrate the preliminary development for a kinematic unicycle and generic nonlinear system. Results from three experiments are also presented to illustrate the performance of the developed method, where a quadcopter achieves approximate optimal regulation while avoiding three mobile obstacles. To demonstrate the developed method, known avoidance regions are used in the first experiment, unknown avoidance regions are used in the second experiment, and an unknown time-varying obstacle directed by a remote pilot is included in the third experiment.

中文翻译：

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避免未知移动回避区域的近似最优运动规划

在本文中，考虑了在存在动态回避区域的情况下受输入约束的控制仿射非线性自治代理的无限范围最优调节问题。实现了基于局部模型的近似动态规划方法来近似代理的局部邻域中的值函数。通过执行局部近似，不需要回避区域位置的先验知识。为了减轻操作域中回避区域数量的先验知识，提供了一个扩展来修改值函数近似。开发的基于反馈的运动规划策略保证了近似控制策略最终有界收敛到最优策略，同时还确保代理保持在回避区域之外。包括模拟以展示运动学独轮车和通用非线性系统的初步开发。还提供了三个实验的结果来说明所开发方法的性能，其中四轴飞行器在避开三个移动障碍物的同时实现了近似最佳调节。为了演示所开发的方法，在第一个实验中使用了已知的回避区域，在第二个实验中使用了未知的回避区域，并且在第三个实验中包括了由遥控驾驶员引导的未知时变障碍物。其中四轴飞行器在避开三个移动障碍物的同时实现近似最佳调节。为了演示所开发的方法，在第一个实验中使用了已知的回避区域，在第二个实验中使用了未知的回避区域，并且在第三个实验中包括了由遥控驾驶员引导的未知时变障碍物。其中四轴飞行器在避开三个移动障碍物的同时实现近似最佳调节。为了演示所开发的方法，在第一个实验中使用了已知的回避区域，在第二个实验中使用了未知的回避区域，并且在第三个实验中包括了由遥控驾驶员引导的未知时变障碍物。