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 guaranteeing asymptotic stability of 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 via some numerical simulations.

翻译：本文针对在包含任意非凸形状障碍物的二维环境中运行的机器人，提出一种自主导航算法。只要存在至少一条安全路径连接初始位置与目标位置，即使障碍物彼此紧密相邻，该方法依然适用。所提出的导航方法基于混合反馈，既能保证目标位置的渐近稳定性，又能确保无障碍工作空间的前向不变性。该混合反馈控制器根据机器人与障碍物占据工作空间的接近程度，确保在“向目标移动”模式与“障碍物回避”模式之间实现无Zeno现象的切换。我们引入了一种非保守的虚拟变换方法，对非凸障碍物进行（虚拟）重塑，以利于障碍回避策略的设计。最后，给出了基于传感器实现该混合控制器的算法流程，并通过数值仿真验证了其有效性。