  Online generation of collision free trajectories is of prime importance for
autonomous navigation. Dynamic environments, robot motion and sensing
uncertainties adds further challenges to collision avoidance systems. This
paper presents an approach for collision avoidance in dynamic environments,
incorporating robot and obstacle state uncertainties. We derive a tight upper
bound for collision probability between robot and obstacle and formulate it as
a motion planning constraint which is solvable in real time. The proposed
approach is tested in simulation considering mobile robots as well as
quadrotors to demonstrate that successful collision avoidance is achieved in
real time application. We also provide a comparison of our approach with
several state-of-the-art methods.
