A New Algorithm for Robot Path Planning Based on Scout Ant Cooperation

A new ant algorithm for robot path planning is presented according to the latest achievements of research on actual ants. In this algorithm, m scout ants collaborate with each other to search for an optimal or near-optimal path. Of m scout ants, n ants adopt nearest-neighbor search strategy and the left q=m-n ants adopt random search strategy. A section of optimal path will be found after all ants search L steps. Then m ants regard the end point of as the new starting point and search for L steps to find the next section of optimal path . Repeat this process until one of m ants reaches the goal. In this way, the path is consisted of h sections of path with step length L. Carry out the next generation search after step length L is modified, then repeat the searching course mentioned above. An optimal or near-optimal path will be found through comparison after multi-generation of searching. The simulation experiment results show that an optimal or near-optimal path can be planned even in environment with very complex obstacles, which can meet the requirements of real-time planning or navigation. The effect is quite satisfying.