A Max-Min Ant System Approach to Autonomous Navigation
Chaomin Luo, Saleh Alarabi, Zhuming Bi, Gene Eu Jan · 2019
Multi-goal navigation of an autonomous mobile robot seeks to reach multiple goals with a planned shortest trajectory in some real-world applications such as search and rescue robots, agricultural harvesting robots, resource prospecting robots and service robots, etc. An improved max-min ant system (MMAS) approach is proposed in this paper for real-time concurrent multi-goal navigation and map building. A global trajectory is planned by the proposed MMAS approach, in which a foraging-enabled trail is generated to guide the robot to the multiple goals. A histogram-based local navigator is utilized to guide the robot to follow the trail planned by the global path planner, with obstacle avoidance. In this paper, simulation results demonstrate that the real-time mapping and multi-goal navigation of an autonomous robot is successfully carried out under unknown environments.