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Predictive Control for Multi-Robot Observation of Multiple Moving Targets Based on Discrete-Continuous Linear Models

Kuhn, Juliane and Reinl, Christian and Stryk, Oskar von and Stryk, Oskar von (2011):
Predictive Control for Multi-Robot Observation of Multiple Moving Targets Based on Discrete-Continuous Linear Models.
In: Proceedings of the 18th IFAC World Congress, [Conference or Workshop Item]

Abstract

The observation of multiple moving targets by cooperating mobile robots is a key problem in many security, surveillance and service applications. In essence, this problem is characterized by a tight coupling of target allocation and continuous trajectory planning. Optimal control of the multi-robot system generally neither permits to neglect physical motion dynamics nor to decouple or successively process target assignment and trajectory planning. In this paper, a numerically robust and stable model-predictive control strategy for solving the problem in the case of discrete-time double-integrator dynamics is presented. Optimization based on linear mixed logical dynamical system models allows for a flexible weighting of different aspects and optimal control inputs for settings of moderate size can be computed in real-time. By simulating sets of randomly generated situations, one can determine a maximum problem size solvable in real-time in terms of the number of considered robots, targets, and length of the prediction horizon. Based on this information, a decentralized control approach is proposed.

Item Type: Conference or Workshop Item
Erschienen: 2011
Creators: Kuhn, Juliane and Reinl, Christian and Stryk, Oskar von and Stryk, Oskar von
Title: Predictive Control for Multi-Robot Observation of Multiple Moving Targets Based on Discrete-Continuous Linear Models
Language: English
Abstract:

The observation of multiple moving targets by cooperating mobile robots is a key problem in many security, surveillance and service applications. In essence, this problem is characterized by a tight coupling of target allocation and continuous trajectory planning. Optimal control of the multi-robot system generally neither permits to neglect physical motion dynamics nor to decouple or successively process target assignment and trajectory planning. In this paper, a numerically robust and stable model-predictive control strategy for solving the problem in the case of discrete-time double-integrator dynamics is presented. Optimization based on linear mixed logical dynamical system models allows for a flexible weighting of different aspects and optimal control inputs for settings of moderate size can be computed in real-time. By simulating sets of randomly generated situations, one can determine a maximum problem size solvable in real-time in terms of the number of considered robots, targets, and length of the prediction horizon. Based on this information, a decentralized control approach is proposed.

Title of Book: Proceedings of the 18th IFAC World Congress
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Simulation, Systems Optimization and Robotics Group
Date Deposited: 20 Jun 2016 23:26
Identification Number: 2011:KuhnReinlVonStryk_IFAC_WC11
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