MOBILE ROBOT PATH PLANNING USING ANT COLONY OPTIMIZATION

Currently Mobile Robot has been widely used in examination and navigation particularly where static and unknown surroundings are involved. Path planning is a crucial problem in mobile robotics. Path planning of robot refers to the determination of a path, a robot takes in order to carry out the necessary task with a given set of key parameters. To find best possible path from starting point to target point, that reduces time and distance, in a given environment, avoiding collision with obstacles is a current potential research area. This paper presents SACO and ACO-MH algorithm to solve the problem of mobile robot path planning such that to reach the target station from source station without collision. The SACO and ACO-MH algorithm will give the collision free optimal path. The result obtained with ACO-MH was compared with SACO. The mobile robot environment is treated as a grid based environment in which each grid can be represented by an ordered pair of row number and column number. The mobile robot is considered as a point in the environment, to reduce the computational complexities. The ACO-MH results show better convergence speed and reduction in computational time than that of SACO through multiple MATLAB experiments