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has been cited by the following article:
TITLE: Two Agent Paths Planning Collaboration Based on the State Feedback Stackelberg Dynamic Game
AUTHORS: Sousso Kelouwani
KEYWORDS: Robotic Architecture; Share Control; Stackelberg Game; Cooperative Control; Collaborative Control
JOURNAL NAME: Open Journal of Optimization, Vol.2 No.3, September 11, 2013
ABSTRACT: Autonomous Navigation Modules are capable of driving a robotic platform without human direct participation. It is usual to have more than one Autonomous Navigation Modules in the same work space. When an emergency situation occurs, these modules should achieve a desired formation in order to efficiently escape and avoid motion deadlock. We address the collaboration problem between two agents such as Autonomous Navigation Modules. A new approach for team collaborative control based on the incentive Stackelberg game theory is presented. The procedure to find incentive matrices is provided for the case of geometric trajectory planning and following. A collaborative robotic architecture based on this approach is proposed. Simulation results performed with two virtual robotic platforms show the efficiency of this approach.