Multi-Agent Dynamic Scheduling with A Posteriori Path Tracking and Collision Avoidance Using Model Predictive Control

This research work investigates a coordinated multi-agent path planning and tracking method. The solution of a pre-processed dynamic scheduling problem performs target assignment and provides optimal starting times and paths for each agent. Afterwards, a linear model predictive controller ensures ro...

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Bibliographic Details
Published in:IEEE control systems letters 2023-01, Vol.7, p.1-1
Main Authors: Bertoncini, Jeremy, Nikitina, Viktoriya, Gerdts, Matthias
Format: Article
Language:English
Subjects:
Collision avoidance
Dynamic scheduling
mixed-integer programming
Optimal control
Optimal scheduling
predictive control for linear systems
Target tracking
Trajectory
Vehicle dynamics
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Summary:This research work investigates a coordinated multi-agent path planning and tracking method. The solution of a pre-processed dynamic scheduling problem performs target assignment and provides optimal starting times and paths for each agent. Afterwards, a linear model predictive controller ensures robust and fast path tracking while preventing agents from collisions. This task is formulated as a discretized quadratic programming (QP) problem and is solved using an in-house developed semi-smooth Newton method. Numerical experiments have demonstrated the efficiency of the approach.
ISSN:2475-1456
2475-1456
DOI:10.1109/LCSYS.2023.3284761