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.