  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.
