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：本文中，我们开发了一种自主导航算法，用于在包含非凸形壳体（它们可以彼此接近）的二维环境中的机器人操作，并且存在至少一条安全路径可连接初始和目标位置。所提出的导航方法采用混合反馈来保证机器人向预定义目标位置的全局渐近稳定，并确保无障碍工作空间的前向不变性。所提出的混合反馈控制器保证在机器人接近占据障碍物工作空间时，在目标模式和避障模式之间进行免 Zeno 切换。介绍了一种工具性转换，以非保守的方式重塑（虚拟）的非凸壳体，以便促进避障策略的设计。最后，我们提供了一个基于传感器的实现所提出的混合控制器的算法过程，并通过仿真结果验证其有效性。