We develop an autonomous navigation algorithm for a robot operating in two-dimensional environments containing obstacles, with arbitrary non-convex shapes, which can be in close proximity with each other, as long as there exists at least one safe path connecting the initial and the target location. The proposed navigation approach relies on a hybrid feedback to guarantee global asymptotic stabilization of the robot towards a predefined target location while ensuring the forward invariance of the obstacle-free workspace. The proposed hybrid feedback controller guarantees Zeno-free switching between the move-to-target mode and the obstacle-avoidance mode based on the proximity of the robot with respect to the obstacle-occupied workspace. An instrumental transformation that reshapes (virtually) the non-convex obstacles, in a non-conservative manner, is introduced to facilitate the design of the obstacle-avoidance strategy. Finally, we provide an algorithmic procedure for the sensor-based implementation of the proposed hybrid controller and validate its effectiveness through simulation results.

翻译：本文针对工作在二维环境中、障碍物可具有任意非凸形状且彼此紧密相邻（只要存在至少一条连接初始位置与目标位置的安全路径）的机器人，提出一种自主导航算法。所提出的导航方法基于混合反馈控制，在保证无障碍工作空间前向不变性的同时，实现机器人对预设目标位置的全局渐近镇定。该混合反馈控制器根据机器人与障碍物占据空间的邻近程度，在"趋向目标"与"避障"两种模式间进行无芝诺切换。为便于设计避障策略，本文引入一种非保守的虚拟非凸障碍物重整形变换。最后给出该混合控制器的传感器实现算法流程，并通过仿真结果验证其有效性。