A Computationally Efficient Feasible Sequential Quadratic Programming Algorithm
SIAM Journal on Optimization
Analysis of Dynamic Task Allocation in Multi-Robot Systems
International Journal of Robotics Research
Decentralized Navigation Functions for Multiple Robotic Agents with Limited Sensing Capabilities
Journal of Intelligent and Robotic Systems
Integral sliding mode control for trajectory tracking of a unicycle type mobile robot
Integrated Computer-Aided Engineering - Informatics in Control, Automation and Robotics
Closed loop motion planning of cooperating mobile robots using graph connectivity
Robotics and Autonomous Systems
Theory and implementation of path planning by negotiation for decentralized agents
Robotics and Autonomous Systems
Robotics and Autonomous Systems
Robot team coordination for target tracking using fuzzy logic controller in game theoretic framework
Robotics and Autonomous Systems
Decentralized receding horizon control for large scale dynamically decoupled systems
Automatica (Journal of IFAC)
Visual perception of obstacles and vehicles for platooning
IEEE Transactions on Intelligent Transportation Systems
A review of conflict detection and resolution modeling methods
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Brief An improved approach for constrained robust model predictive control
Automatica (Journal of IFAC)
Distributed receding horizon control for multi-vehicle formation stabilization
Automatica (Journal of IFAC)
Mono Landmark Localization for an Autonomous Navigation of a Cooperative Mobile Robot Formation
ICIRA '09 Proceedings of the 2nd International Conference on Intelligent Robotics and Applications
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This paper presents a decentralized motion planner for a team of nonholonomic mobile robots subject to constraints imposed by sensors and the communication network. The motion planning scheme consists of decentralized receding horizon planners that reside on each vehicle to achieve coordination among flocking agents. The advantage of the proposed algorithm is that each vehicle only requires local knowledge of its neighboring vehicles. The main requirement for designing an optimal conflict-free trajectory in a decentralized way is that each robot does not deviate too far from its presumed trajectory designed without taking the coupling constraints into account. A comparative study between the proposed algorithm and other existing algorithms is provided in order to show the advantages, especially in terms of computing time. Finally, experiments are performed on a team of three mobile robots to demonstrate the validity of the proposed approach.