Intelligent Multi-Robot System for Collaborative Object Transportation Tasks in Rough Terrains

Human missions on other planets require constructing outposts and infrastructures, one may need to consider relocating such large objects according changes in mission spots. A multi-robot system would be a good option for transportation task because it can carry massive provide better reliability redundancy when compared single robot system. This paper proposes an intelligent decentralized approach the using genetic fuzzy perform object that not only minimizes total travel distance of but also guarantees stability whole rough terrain environment. The proposed inference determines system’s input transporting target position is tuned training process by algorithm with artificially generated structured environment employing multiple scenarios. It validates optimality comparing results obtained solving formulated optimal control problem subject path inequality constraints. highlights performance applying trained systems operate unstructured environments.