We develop an autonomous navigation algorithm for a robot operating in two-dimensional environments cluttered with obstacles having arbitrary convex shapes. 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 main idea consists in designing an appropriate switching strategy between the move-to-target mode and the obstacle-avoidance mode based on the proximity of the robot with respect to the nearest obstacle. The proposed hybrid controller generates continuous velocity input trajectories when the robot is initialized away from the boundaries of the unsafe regions. Finally, we provide an algorithmic procedure for the sensor-based implementation of the proposed hybrid controller and validate its effectiveness through some simulation results.
翻译:我们为在二维环境中运行的机器人开发一种自主导航算法,这种算法包罗着障碍,具有任意的孔形形状。拟议的导航方法依靠一种混合反馈,以保证机器人在预先确定的目标位置上的全球无干扰稳定,同时确保无障碍的工作空间向前移动。主要想法是设计移动到目标模式和以机器人靠近最近的障碍物为基础的障碍物避免模式之间的适当转换战略。拟议的混合控制器在机器人从不安全区域的边界初始化时产生连续速度输入轨迹。最后,我们为以传感器为基础实施拟议的混合控制器提供了一种算法程序,并通过一些模拟结果验证其有效性。