Online generation of collision free trajectories is prime importance for autonomous navigation. Dynamic environments, robot motion and sensing uncertainties adds further challenges to avoidance systems. This paper presents an approach in dynamic incorporating obstacle state uncertainties. We derive a tight upper bound probability between formulate it as planning constraint which solvable real t...

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, re...