Smooth path planning using genetic algorithms

Advances in mechatronics and artificial intelligence make robots play important roles in modern life. Path planning is an important issue in mobile robotics. In an environment with obstacles, path planning is to find a suitable collision-free path, which satisfies certain optimization criteria, for a mobile robot to move from a start location to a target location. Most researches associated with collision-free path planning have focused on finding the shortest path, the minimum-time path, or the safest path etc., and the generated paths may be discontinued. Smoothness of the path is essential for mobile robot navigation, because non-smooth motions can cause slippage of wheels which degrades the robot´s deadreckoning ability. The smoothness property of the path also is extremely important for car-like vehicles, which are constrained with their motion abilities. Therefore an approach for smooth and collision-free path planning using genetic algorithm with B-spline curve is proposed to give the mobile robot the abilities of global path planning in static environment with obstacles.