A game-theoretic framework for robot motion planning
A game-theoretic framework for robot motion planning
Cooperative strategy based on adaptive Q-learning for robot soccer systems
IEEE Transactions on Fuzzy Systems
Automatica (Journal of IFAC)
Robotics and Autonomous Systems
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IEEE Transactions on Robotics
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Theoretical Computer Science
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International Journal of Robotics Research
Toward opportunistic collaboration in target pursuit problems
AIS'11 Proceedings of the Second international conference on Autonomous and intelligent systems
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Fuzzy Sets and Systems
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Journal of Intelligent and Robotic Systems
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This paper involves a collision free target tracking problem of multi-agent robot system. Target tracking requires team coordination to maintain a desired formation and to keep team-mates and target together. Every team-mate makes decisions on their moving direction that may spoil the tactical position of others and makes the global coordination task nontrivial. The contribution of the paper is twofold. First, the convergence of target tracking is improved by a new game theoretic concept using a semi-cooperative Stackelberg equilibrium point and a new formation component in the individual cost functions. To enhance the robustness, a PD like fuzzy controller tunes the cost function weights directly for the game theoretic solution and helps to achieve a prescribed value of cost function components. Simulation result for target tracking by a three-member robot team is presented.