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Real-time motion planning and decision-making for a group of differential drive robots under connectivity constraints using robust MPC and mixed-integer programming

Angelo Caregnato‐Neto, Marcos R. O. A. Máximo, Rubens J. M. Afonso

Year
2022
Citations
11

Abstract

This work is concerned with the problem of planning trajectories and assigning tasks for a Multi-Agent System (MAS) comprised of differential drive robots. We propose a multirate hierarchical control structure that employs a planner based on robust Model Predictive Control (MPC) with mixed-integer programming (MIP) encoding. The planner computes trajectories and assigns tasks for each element of the group in real-time, while also guaranteeing the communication network of the MAS to be robustly connected at all times. Additionally, we provide a data-based methodology to estimate the disturbances sets required by the robust MPC formulation. The results are demonstrated with experiments in two obstacle-filled scenarios.

Keywords

Model predictive controlInteger programmingComputer scienceRobotMotion planningPlannerObstacle avoidanceDifferential (mechanical device)Integer (computer science)Mathematical optimization

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