17 research outputs found
Control Systems Engineering made Easy: Motivating Students through Experimentation on UAVs
International audienceThis paper focuses on a new elective course on modeling and control of multi-agent systems, with experimentation on Unmanned Aerial Vehicles (UAVs). The module is taught for students with basic knowledge in Automatic Control and Optimization and it intends to increase their interest in applying advanced control techniques on UAVs in an enjoyable framework favorable to develop creativity, practical and team working skills, together with a solid and persistent theoretical background
Formation Control Using Vehicle Operational Envelopes and Behavior-Based Dual-Mode Model Predictive Control
This thesis presents a control framework for formation control. Given an initial desired trajectory, a framework is presented to generate trajectories for each vehicle within the formation. When combined with an operational envelope, a designated area for each vehicle to maneuver, for each vehicle the multi-vehicle formation control problem can be redefined into a single vehicle problem. A single vehicle framework is presented to track the respective trajectory when possible, or stay near it when it passes through previously unknown obstacles. Arc-based motions are used to rapidly produce desirable robot controls while a trajectory tracking motion is used to ensure that the vehicle tracks the trajectory when it is obstacle free. The resulting formation control framework is illustrated through a real-time simulation with trajectories passing through obstacles. The simulated robot is able to seamlessly balance tracking with obstacle avoidance
Vision-based control of multi-agent systems
Scope and Methodology of Study: Creating systems with multiple autonomous vehicles places severe demands on the design of decision-making supervisors, cooperative control schemes, and communication strategies. In last years, several approaches have been developed in the literature. Most of them solve the vehicle coordination problem assuming some kind of communications between team members. However, communications make the group sensitive to failure and restrict the applicability of the controllers to teams of friendly robots. This dissertation deals with the problem of designing decentralized controllers that use just local sensor information to achieve some group goals.Findings and Conclusions: This dissertation presents a decentralized architecture for vision-based stabilization of unmanned vehicles moving in formation. The architecture consists of two main components: (i) a vision system, and (ii) vision-based control algorithms. The vision system is capable of recognizing and localizing robots. It is a model-based scheme composed of three main components: image acquisition and processing, robot identification, and pose estimation.Using vision information, we address the problem of stabilizing groups of mobile robots in leader- or two leader-follower formations. The strategies use relative pose between a robot and its designated leader or leaders to achieve formation objectives. Several leader-follower formation control algorithms, which ensure asymptotic coordinated motion, are described and compared. Lyapunov's stability theory-based analysis and numerical simulations in a realistic tridimensional environment show the stability properties of the control approaches
Multi-Robot Systems: Challenges, Trends and Applications
This book is a printed edition of the Special Issue entitled “Multi-Robot Systems: Challenges, Trends, and Applications” that was published in Applied Sciences. This Special Issue collected seventeen high-quality papers that discuss the main challenges of multi-robot systems, present the trends to address these issues, and report various relevant applications. Some of the topics addressed by these papers are robot swarms, mission planning, robot teaming, machine learning, immersive technologies, search and rescue, and social robotics
Aerial Vehicles
This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space
Decentralized MPC for UAVs Formation Deployment and Reconfiguration with Multiple Outgoing Agents
International audienceThis paper presents a new decentralized algorithm for the deployment and reconfiguration of a multi-agent formation in a convex bounded polygonal area when considering several outgoing agents. The system is deployed over a two-dimensional convex bounded area, each agent being driven by its own linear model predictive controller. At each time instant, the area is partitioned into Voronoi cells associated with each agent. Due to the movement of the agents, this partition is time-varying. The objective of the proposed algorithm is to drive the agents into a static configuration based on the Chebyshev center of each Voronoi cell. When some agents present a non-cooperating behavior (e.g. agents required for a different mission, faulty agents, etc.), they have to leave the formation by tracking a reference outside the system's workspace. The outgoing agents and their objective positions partition the convex bounded polygonal area into working regions. Each remaining agent will track a new objective point allowing it to avoid the trajectory of the outgoing agents. The computation of this objective position is based on the agent's safety region (i.e. the intersection of the contracted Voronoi cell and the contracted working region). When the outgoing agents have left the workspace, the remaining agents resume their deployment objective. Simulation results on a formation of a team of unmanned aerial vehicles are finally presented to validate the algorithm proposed in this paper when several agents leave the formation