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Experimental tests of autonomous ground vehicles with preview

Abstract

This paper describes the design and experimental tests of a path planning and reference tracking algorithm for autonomous ground vehicles. The ground vehicles under consideration are equipped with forward looking sensors that provide a preview capability over a certain horizon. A two-level control framework is proposed for real-time implementation of the model predictive control (MPC) algorithm, where the high-level performs on-line optimization to generate the best possible local reference respect to various constraints and the low-level commands the vehicle to follow realistic trajectories generated by the high-level controller. The proposed control scheme is implemented on an indoor testbed through networks with satisfactory performance.

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Author information

Correspondence to Cunjia Liu.

Additional information

Cunjia Liu received the B.Eng. degree in detection, guidance, and control technology in 2005, the M. Eng. degree in guidance, navigation, and control in 2008 from Beijing University of Aeronautics and Astronautics, Beijing, PRC. He currently is a Ph. D. candidate in the Department of Aeronautical and Automotive Engineering at Loughborough University, UK.

His research interests include the optimization based control, flight control, and path planning of unmanned aerial vehicles.

Wen-Hua Chen received the M. Sc. and Ph.D. degrees from Department of Automatic Control at Northeast University, PRC in 1989 and 1991, respectively. From 1991 to 1996, he was a lecturer in Department of Automatic Control at Nanjing University of Aeronautics and Astronautics, PRC. He held a research position and then a lecturer in control engineering in Center for Systems and Control at University of Glasgow, UK from 1997 to 2000. He currently is a senior lecturer in flight control systems in Department of Aeronautical and Automotive Engineering at Loughborough University, UK.

His research interests include the development of advanced control strategies and their applications in aerospace engineering.

John Andrews is the Royal Academy of Engineering Professor of Infrastructure Asset Management at the Nottingham Transportation Engineering Centre (NTEC) at University of Nottingham, UK. Prior to this, he spent 20 years at Loughborough University, UK. The prime focus of his research has been on methods for predicting system reliability in terms of the component failure probabilities and a representation of the system structure. He is founding editor of the Journal of Risk and Reliability (Part O of the IMechE Proceedings). He is also a member of the editorial boards for Reliability Engineering and System Safety, and Quality and Reliability Engineering International.

His research interests include the fault tree technique and the use of the binary decision diagrams (BDDs) as an efficient and accurate solution method.

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Liu, C., Chen, W. & Andrews, J. Experimental tests of autonomous ground vehicles with preview. Int. J. Autom. Comput. 7, 342–348 (2010). https://doi.org/10.1007/s11633-010-0513-9

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Keywords

  • Model predictive control
  • autonomous vehicle
  • online optimization
  • nonholonomic constraint
  • eigenvalue