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A Distributed Model Predictive Control Framework for Road-Following Formation Control of Car-like Vehicles (Extended Version)

Abstract : This work presents a novel framework for the formation control of multiple autonomous ground vehicles in an on-road environment. Unique challenges of this problem lie in 1) the design of collision avoidance strategies with obstacles and with other vehicles in a highly structured environment, 2) dynamic reconfiguration of the formation to handle different task specifications. In this paper, we design a local MPC-based tracking controller for each individual vehicle to follow a reference trajectory while satisfying various constraints (kinematics and dynamics, collision avoidance, etc.). The reference trajectory of a vehicle is computed from its leader's trajectory, based on a pre-defined formation tree. We use logic rules to organize the collision avoidance behaviors of member vehicles. Moreover, we propose a methodology to safely reconfigure the formation on-the-fly. The proposed framework has been validated using high-fidelity simulations.
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https://hal.archives-ouvertes.fr/hal-01309659
Contributor : Xiangjun Qian <>
Submitted on : Friday, April 29, 2016 - 11:35:01 PM
Last modification on : Thursday, April 9, 2020 - 5:08:13 PM
Document(s) archivé(s) le : Monday, May 23, 2016 - 6:40:11 PM

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  • HAL Id : hal-01309659, version 1

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Xiangjun Qian, Florent Altché, Arnaud de la Fortelle, Fabien Moutarde. A Distributed Model Predictive Control Framework for Road-Following Formation Control of Car-like Vehicles (Extended Version). 2016. ⟨hal-01309659⟩

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