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Communication Dans Un Congrès Année : 2021

Pursuit-evasion Games Based on Game-theoretic and Model Predictive Control Algorithms

Résumé

Non-cooperative game problems such as pursuitevasion require a solution approach that takes into consideration the strategy of the opponents. To predict the strategy of an opponent in a game, its full information is required and more computation time would be spent. However, this requirement of the opponent's full information is not realistic. Also, the computation time required by the game-theoretic algorithm (GTA) could make the controller unimplementable for some systems. Conversely, Model Predictive Control (MPC) could be use to solve the same problem using only the states information on the opponent by solving minimization or maximization cost functions. In this paper, we compared the GTA and MPC algorithm using two autonomous nonholonomic ground robots. Several simulations were conducted in the absence and presence of obstacles, using different initial conditions. The results obtained showed that the MPC algorithm can achieve similar performance.
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Dates et versions

hal-03412852 , version 1 (03-11-2021)

Identifiants

  • HAL Id : hal-03412852 , version 1

Citer

Mukhtar Sani, Bogdan Robu, Ahmad Hably. Pursuit-evasion Games Based on Game-theoretic and Model Predictive Control Algorithms. ICCAD 2021 : 5th IEEE-International Conference on Control, Automation and Diagnosis, Nov 2021, Grenoble, France. ⟨hal-03412852⟩
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