Collision-free path planning of Dual-arm robots based on improved ant colony algorithm

Using the three-dimensional C space, we combined the method of path planning based on sensor information and the algorithm of the intelligent ant colony optimization, researched on the most effective way on Dual-arm robots collision-free path planning. Based on the traditional algorithm's limitation on space path searching and the joint movement's characteristics of Dual-arm robots in the C space, we enhanced the search strategy for ant colony algorithm, discussed the influence of the size of compartmentalize grid on path planning's speed and accuracy; improved the techniques of local pheromone update, provided the local pheromone update conditions when shortest path, life of electrical and energy consumption are all considered. For the circumstances that ants' feasible region maybe empty in the process of path searching, we introduced the ants back strategy in order to improve the algorithm's adaptability substantially. The simulations show the searching performance and searching speed of the improved algorithm proposed by this article are better than the traditional one. As ensuring collision-free for two arms, the start-stop times are also decreased to a lower degree.