Development of optimal path planning based on ant colony and wireless sensor network localization techniques for an autonomous mobile service robot

This study incorporates web and wireless sensor localization techniques to enable the autonomous mobile robot to plan the optimal path and be synchronized with the web for realtime navigation. When the robot is given the task to receive and dispatch files in various offices in a building, a web-based application program assigns tasks to the robot, where the realtime location is calculated by wireless sensor localization and displayed on the web interface synchronously. Hence, the present location of the robot can be known. In terms of path planning, when multiple tasks are successively assigned, the key is how to immediately determine or modify the optimal path according to changes in the assigned work. This study adopts an ant colony optimization algorithm for path planning. When the robot receives a new assignment, it rearranges the priority of task location by automatic optimization, thus, guaranteeing working efficiency. In terms of wireless sensor localization, due to complex restrictions of indoor environments, according to literature, the error of wireless sensor network localization is above 1m. Therefore, this study uses the binocular stereo vision system of the robot for localization compensation to reduce the error.