  We present a fully distributed collision avoidance algorithm based on convex
optimization for a team of mobile robots. This method addresses the practical
case in which agents sense each other via measurements from noisy on-board
sensors with no inter-agent communication. Under some mild conditions, we
provide guarantees on mutual collision avoidance for a broad class of policies
including the one presented. Additionally, we provide numerical examples of
computational performance and show that, in both 2D and 3D simulations, all
agents avoid each other and reach their desired goals in spite of their
uncertainty about the locations of other agents.
