Saska, Martin (Czech Technical University in Prague), Krajnik, Tomas (Faculty of Electrical Engineering, Czech Technical University), Vonasek, Vojtech (Czech Technical University in Prague, Faculty of electrical engi), Vaněk, Petr (Czech Technical University in Prague), Preucil, Libor (Czech Technical University)

Navigation, Localization and Stabilization of Formations of Unmanned Aerial and Ground Vehicles

Scheduled for presentation during the Invited Session "Cooperative Control Designs for Multiple Aerial Vehicles" (FrAT1), Friday, May 31, 2013, 10:50−11:15, Buckhead Ballroom

2013 International Conference on Unmanned Aircraft Systems, May 28-31, 2013, Grand Hyatt Atlanta, Atlanta, GA

This information is tentative and subject to change. Compiled on August 16, 2018

Abstract

A leader-follower formation driving algorithm developed for control of heterogeneous groups of unmanned micro aerial and ground vehicles stabilized under a top-view relative localization is presented in this paper. The core of the proposed method lies in a novel avoidance function, in which the entire 3D formation is represented by a convex hull projected along a desired path to be followed by the group. Such a representation of the formation provides non-collision trajectories of the robots and respects requirements of the direct visibility between the team members in environment with static as well as dynamic obstacles, which is crucial for the top-view localization. The algorithm is suited for utilization of a simple yet stable visual based navigation of the group (referred to as GeNav). This method together with the on-board relative localization enables deployment of large teams of micro-scale robots in environments without any available global localization system. We formulate a novel Model Predictive Control (MPC) based concept that enables to respond to the changing environment and that provides a robust solution with a failure tolerance technique included. The performance of the proposed method is verified by numerical and hardware experiments inspired by reconnaissance and surveillance missions.