This paper proposes a motion control scheme for robots operating in a dynamic environment with concave obstacles. A Model Predictive Controller (MPC) is constructed to drive the robot towards a goal position while ensuring collision avoidance without direct use of obstacle information in the optimization problem. This is achieved by guaranteeing tracking performance of an appropriately designed receding horizon path. The path is computed using a guiding vector field defined in a subspace of the free workspace where each point in the subspace satisfies a criteria for minimum distance to all obstacles. The effectiveness of the control scheme is illustrated by means of simulation.

翻译：本文提出了一种针对凸障碍物的动态环境下机器人运动控制方案。使用模型预测控制器（MPC）将机器人驱动到目标位置，同时确保在优化问题中不直接使用障碍物信息的情况下避免碰撞。这是通过保证适当设计的回归视场的跟踪性能来实现的。该路径是使用位于自由工作空间子空间内定义的引导矢量场计算的，该子空间中的每个点均满足所有障碍物的最小距离的标准。通过模拟说明了控制方案的有效性。