Safe Navigation of Quadrotor Teams to Labeled Goals in Limited Workspaces

Sarah Tang, Justin Thomas, Vijay Kumar

Abstract: In this work, we solve the labeled multi-robot planning problem. Most proposed algorithms to date have modeled robots as kinematic or kinodynamic agents in planar environments, making them impractical for real-world systems. Here, we present experiments to validate a centralized multi-robot planning and trajectory generation method that explicitly accounts for robots with higher-order dynamics. First, we demonstrate successful execution of solution trajectories. Next, we verify the robustness of the robots’ trajectory tracking to unmodeled external disturbances, in particular, the aerodynamic interactions between co-planar neighbors. Finally, we apply our algorithm to navigating quadrotors away from the downwash of their neighbors to improve safety in three-dimensional workspaces.