Obstacle-Aware Path Planning in Multi-Robot Systems Using Adaptive Spider Wasp Optimization - Subramanian, Sakthitharan; Devi, B. Renuka; Vinnarasi, F. Sangeetha Francelin; Sarveshwaran, Velliangiri (Journal of Mobile Multimedia, 2025)
Path planning generates a shorter path from source to destination based on sensor information acquired from an environment. An obstacle avoidance is an important task in robotics within path planning since the automatic functioning of robots requires reaching the destination without collisions. Moreover, obstacle avoidance algorithms have an important part in robotics. The existing algorithms did not enable robots to navigate their environments effectively, lessening the threat of collisions and preventing obstacles. Here, an Adaptive Spider Wasp Optimizer (ASWO) is introduced for path planning in mobile multi-robots. Initially, the simulation of an environment utilizing multiple robots and targets along with obstacles is accomplished. Thereafter, multi-objectives namely path smoothness, obstacle avoidance, and path length are considered. Lastly, path planning is conducted employing ASWO by considering fitness parameters such as path smoothness, obstacle avoidance, and path length. However, ASWO is designed by integrating adaptive concept with Spider Wasp Optimizer (SWO). In addition, ASWO achieved maximal value of fitness and path smoothness about 1.795 and 91.121% as well as minimal value of path length about 897.883 km.