Perception-Aware Planning for Active SLAM in Dynamic Environments

This paper presents a perception-aware path planner for active SLAM in dynamic environments using micro-aerial vehicles (MAV). The “Next-Best-View” (NBVP planner) is combined with an loop closing, which called the Active Loop Closing Planner (ALCP planner). proposed to avoid both static and obstacles unknown while reducing uncertainty of system further improving accuracy localization. First, receding horizon strategy adopted find next waypoint. cost function that combines exploration gain closing designed. former can reduce mapping uncertainty, latter takes possibility into consideration. Second, key waypoint selection selected waypoints, instead all are treated as potential loop-closing points make algorithm more efficient. Moreover, fuzzy RRT-based obstacle avoidance realize environments. Simulations different challenging scenarios conducted verify effectiveness algorithm.