Distributed Fault-Tolerant Control for Networked Robots in the Presence of Recoverable/Unrecoverable Faults and Reactive Behaviors

The paper presents an architecture for distributed control of multi-robot systems with an integrated fault detection, isolation, and recovery strategy. The proposed solution is based on a distributed observer-controller schema where each robot, by communicating only with its direct neighbors, is able to estimate the overall state of the system; such an estimate is then used by the controllers of each robot to achieve global missions as, for example, centroid and formation tracking. The information exchanged among the observers is also used to compute residual vectors that allow each robot to detect failures on anyone of the teammates, even if not in direct communication. The proposed strategy considers both recoverable and unrecoverable actuator faults as well as it properly manages the possible activation of reactive local control behaviors of the robots (e.g., the activation of obstacle avoidance strategy), which generate control inputs different from those required by the global mission control. In particular, when the robots are subject to recoverable faults, those are managed at a local level by computing a proper compensating control action. On the other side, when the robots are subject to unrecoverable faults, the faults are isolated from anyone of the teammates by means of a distributed fault detection and isolation strategy; then, the faulty robots are removed from the team and the mission is rearranged. The proposed strategy is validated via numerical simulations where the system properly identifies and manages the different cases of recoverable and unrecoverable actuator faults, as well as it manages the activation of local reactive control in an integrated case study

Distributed formation tracking using local coordinate systems

This paper studies the formation tracking problem for multi-agent systems, for which a distributed estimator–controller scheme is designed relying only on the agents’ local coordinate systems such that the centroid of the controlled formation tracks a given trajectory. By introducing a gradient descent term into the estimator, the explicit knowledge of the bound of the agents’ speed is not necessary in contrast to existing works, and each agent is able to compute the centroid of the whole formation in finite time. Then, based on the centroid estimation, a distributed control algorithm is proposed to render the formation tracking and stabilization errors to converge to zero, respectively. Finally, numerical simulations are carried to validate our proposed framework for solving the formation tracking problem

3D Formation Control in Multi-Robot Teams Using Artificial Potential Fields

Multi-robot teams find applications in emergency response, search and rescue operations, convoy support and many more. Teams of autonomous aerial vehicles can also be used to protect a cargo of airplanes by surrounding them in some geometric shape. This research develops a control algorithm to attract UAVs to one or a set of bounded geometric shapes while avoiding collisions, re-configuring in the event of departure or addition of UAVs and maneuvering in mission space while retaining the configuration. Using potential field theory, weighted vector fields are described to attract UAVs to a desired formation. In order to achieve this, three vector fields are defined: one attracts UAVs located outside the formation towards bounded geometric shape; one pushes them away from the center towards the desired region and the third controls collision avoidance and dispersion of UAVs within the formation. The result is a control algorithm that is theoretically justified and verified using MATLAB which generates velocity vectors to attract UAVs to a loose formation and maneuver in the mission space while remaining in formation. This approach efficiently scales to different team sizes

Quadcopter Attitude Control Optimization and Multi-Agent Coordination

This thesis presents a method of automated control gain tuning for a Quadcopter Unmanned Aerial Vehicle and proposes a method of coordination multiple autonomous robotic agents capable for formation aggregation. Sliding Mode Control for Quadcopter altitude and attitude stabilization is presented and tuned using Particle Swarm Optimization. Different configurations for the optimization process are compared to determine an effective and time-efficient setup to complete the control gain tuning. The multi-agent coordination scheme expands upon an existing adjustable swarm framework based on an Artificial Potential Field Sliding Mode Controller. The original leader-follower scheme is modified with the goal of producing a leaderless swarm where agents move towards specific locations to aggregate a desired formation. Analysis of the swarm control scheme pays particular attention to maintaining proper distance between agents. Using Lyapunov methods following that of the original controller analysis, stability under first order and general higher order dynamics is analyzed. Numerical simulations of the swarm controller using agents with nonlinear Quadcopter or second order point mass dynamics are presented to illustrate the capabilities of this algorithm. The automatically tuned Quadcopter controller is used in simulations when applicable. The development of an experimental test platform is discussed with the intention of validating the simulation results on physical Quadcopters

Swarm Robotics

Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties

Contributions to shared control and coordination of single and multiple robots

L’ensemble des travaux présentés dans cette habilitation traite de l'interface entre un d'un opérateur humain avec un ou plusieurs robots semi-autonomes aussi connu comme le problème du « contrôle partagé ».Le premier chapitre traite de la possibilité de fournir des repères visuels / vestibulaires à un opérateur humain pour la commande à distance de robots mobiles.Le second chapitre aborde le problème, plus classique, de la mise à disposition à l’opérateur d’indices visuels ou de retour haptique pour la commande d’un ou plusieurs robots mobiles (en particulier pour les drones quadri-rotors).Le troisième chapitre se concentre sur certains des défis algorithmiques rencontrés lors de l'élaboration de techniques de coordination multi-robots.Le quatrième chapitre introduit une nouvelle conception mécanique pour un drone quadrirotor sur-actionné avec pour objectif de pouvoir, à terme, avoir 6 degrés de liberté sur une plateforme quadrirotor classique (mais sous-actionné).Enfin, le cinquième chapitre présente une cadre général pour la vision active permettant, en optimisant les mouvements de la caméra, l’optimisation en ligne des performances (en terme de vitesse de convergence et de précision finale) de processus d’estimation « basés vision »