Fault-tolerant formation driving mechanism designed for heterogeneous MAVs-UGVs groups

A fault-tolerant method for stabilization and navigation of 3D heterogeneous formations is proposed in this paper. The presented Model Predictive Control (MPC) based approach enables to deploy compact formations of closely cooperating autonomous aerial and ground robots in surveillance scenarios without the necessity of a precise external localization. Instead, the proposed method relies on a top-view visual relative localization provided by the micro aerial vehicles flying above the ground robots and on a simple yet stable visual based navigation using images from an onboard monocular camera. The MPC based schema together with a fault detection and recovery mechanism provide a robust solution applicable in complex environments with static and dynamic obstacles. The core of the proposed leader-follower based formation driving method consists in a representation of the entire 3D formation as a convex hull projected along a desired path that has to be followed by the group. Such an approach provides non-collision solution and respects requirements of the direct visibility between the team members. The uninterrupted visibility is crucial for the employed top-view localization and therefore for the stabilization of the group. The proposed formation driving method and the fault recovery mechanisms are verified by simulations and hardware experiments presented in the paper

Navigation, localization and stabilization of formations of unmanned aerial and ground vehicles

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), which 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 team members' failure tolerance included. The performance of the proposed method is verified by numerical and hardware experiments inspired by reconnaissance and surveillance missions

BACKWARD MOTION PLANNING AND CONTROL OF MULTIPLE MOBILE ROBOTS MOVING IN TIGHTLY COUPLED FORMATIONS

This work addresses the development of a distributed switching control strategy to drive the group of mobile robots in both backward and forward motion in a tightly coupled geometric pattern, as a solution for the deadlock situation that arises while navigating the unknown environment. A generalized closed-loop tracking controller considering the leader referenced model is used for the robots to remain in the formation while navigating the environment. A tracking controller using the simple geometric approach and the Instantaneous Centre of Radius (ICR), to drive the robot in the backward motion during deadlock situation is developed and presented. State-Based Modelling is used to model the behaviors/motion states of the proposed approach in MATLAB/STATEFLOW environment. Simulation studies are carried out to test the performance and error dynamics of the proposed approach combining the formation, navigation, and backward motion of the robots in all geometric patterns of formation, and the results are discussed

Nonlinear control of nonholonomic mobile robot formations

In this thesis, the framework developed to control a single nonholonomic mobile robot is expanded to include the control of formations of multiple nonholonomic mobile robots. A combined kinematic/torque control law is developed for leader-follower based formation control using backstepping in order to accommodate the dynamics of the robots and the formation in contrast with kinematic-based formation controllers typically found in literature --Abstract, page iv