Path Planning and Control of Differential and Car-like Robots in Narrow Environments

This paper presents a comprehensive solution for path planning and control of two popular types of autonomous wheeled vehicles. Differentially driven and car-like motion systems are the most widespread structures among wheeled mobile robots. The planning algorithm employs a rapidly exploring random tree based global planner (RTR), which generates paths made of straight motion and in place turning primitives. Such paths can be directly followed by a differential drive robot. Car-like robots have a minimum turning radius constraint, hence we present a local steering method (C*CS) which obtains a path consisting circular and straight movements based on the primary RTR-path, without losing the existence of the solution. Additionally, a velocity profile generation algorithm is presented, which is responsible for the distribution of the time parameter along the geometric path, taking the physical limitations of the robot into account. Finally, control algorithms for path following are given for both robot types. Simulations and real experiments show the effectiveness of these methods, even is constrained environments containing narrow corridors and passages.