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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.
This paper presents
a stable, nonlinear, adaptive control scheme for building heating and cooling
systems. The proposed controller utilizes the principle of adaptive one step
ahead control and aims at reducing the energy consumed for heating or cooling a
building. The design steps are discussed in details and a proof of global
stability is also provided. Also, the performance of the proposed controller
is demonstrated on a simulated building thermal model.