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.
Document type :
Preprints, Working Papers, ...
Liste complète des métadonnées

Cited literature [21 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01309659
Contributor : Xiangjun Qian <>
Submitted on : Friday, April 29, 2016 - 11:35:01 PM
Last modification on : Monday, November 12, 2018 - 10:57:49 AM
Document(s) archivé(s) le : Monday, May 23, 2016 - 6:40:11 PM

File

submission.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01309659, version 1

Citation

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⟩

Share

Metrics

Record views

276

Files downloads

114