Engineering Applications of Artificial Intelligence
Brief paper: Finite-time formation control for multi-agent systems
Automatica (Journal of IFAC)
Nonlinear model predictive formation flight
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Formation path following control of unicycle-type mobile robots
Robotics and Autonomous Systems
International Journal of Robotics Research
Model Predictive Control of a Flexible Links Mechanism
Journal of Intelligent and Robotic Systems
Multi-Agent Formation Control Based on Bell-Shaped Potential Functions
Journal of Intelligent and Robotic Systems
Automatica (Journal of IFAC)
Robotics and Autonomous Systems
Robust Formation Control of Multiple Wheeled Mobile Robots
Journal of Intelligent and Robotic Systems
Formation control of VTOL Unmanned Aerial Vehicles with communication delays
Automatica (Journal of IFAC)
Practical Formation Control of Multiple Unicycle-Type Mobile Robots with Limited Sensing Ranges
Journal of Intelligent and Robotic Systems
Pareto-optimal coordination of multiple robots with safety guarantees
Autonomous Robots
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
Distributed receding horizon control for multi-vehicle formation stabilization
Automatica (Journal of IFAC)
Robot Formations Using a Single Camera and Entropy-based Segmentation
Journal of Intelligent and Robotic Systems
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This article presents a control approach that enables an autonomous operation of fleets of unmanned snow ploughs at large airports. The proposed method is suited for the special demands of tasks of the airport snow shovelling. The robots have to keep a compact formation of variable shapes during moving into the locations of their deployment and for the autonomous sweeping of runways surfaces. These tasks are solved in two independent modes of the airport snow shoveling. The moving and the sweeping modes provide a full-scale solution of the trajectory planning and coordination of vehicles applicable in the specific airport environment. Nevertheless, they are suited for any multi-robot application that requires complex manoeuvres of compact formations in dynamic environment. The approach encapsulates the dynamic trajectory planning and the control of the entire formation into one merged optimization process via a novel Model Predictive Control (MPC) based methodology. The obtained solution of the optimization includes a complete plan for the formation. It respects the overall structure of the workspace and actual control inputs for each vehicle to ensure collision avoidance and coordination of team members. The presented method enables to autonomously design arbitrary manoeuvres, like reverse driving or turning of compact formations of car-like robots, which frequently occur in the airport sweeping application. Examples of such scenarios verifying the performance of the approach are shown in simulations and hardware experiments in this article. Furthermore, the requirements that guarantee a convergence of the group to a desired state are formulated for the formation acting in the sweeping and moving modes.