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Motion planning for a reversing general 2-trailer configuration using Closed-Loop RRT
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-6957-2603
2016 (English)In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 3690-3697Conference paper, Published paper (Refereed)
Abstract [en]

Reversing with a dolly steered trailer configura- tion is a hard task for any driver without extensive training. In this work we present a motion planning and control framework that can be used to automatically plan and execute complicated manoeuvres. The unstable dynamics of the reversing general 2- trailer configuration with off-axle hitching is first stabilised by an LQ-controller and then a pure pursuit path tracker is used on a higher level giving a cascaded controller that can track piecewise linear reference paths. This controller together with a kinematic model of the trailer configuration is then used for forward simulations within a Closed-Loop Rapidly Exploring Random Tree framework to generate motion plans that are not only kinematically feasible but also include the limitations of the controller’s tracking performance when reversing. The approach is evaluated over a series of Monte Carlo simulations on three different scenarios and impressive success rates are achieved. Finally the approach is successfully tested on a small scale test platform where the motion plan is calculated and then sent to the platform for execution. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016. p. 3690-3697
Series
Intelligent Robots and Systems, E-ISSN 2153-0866 ; 2016
National Category
Robotics Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-134035DOI: 10.1109/IROS.2016.7759544ISI: 000391921703107ISBN: 9781509037629 (electronic)ISBN: 9781509037612 (electronic)ISBN: 9781509037636 (print)OAI: oai:DiVA.org:liu-134035DiVA, id: diva2:1066727
Conference
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, South Korea, October 9-14, 2016
Projects
iQMatic
Note

Funding agencies: FFI/VINNOVA

Available from: 2017-01-19 Created: 2017-01-19 Last updated: 2019-01-17Bibliographically approved
In thesis
1. On motion planning and control for truck and trailer systems
Open this publication in new window or tab >>On motion planning and control for truck and trailer systems
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

During the last decades, improved sensor and hardware technologies as well as new methods and algorithms have made self-driving vehicles a realistic possibility in the near future. Thanks to this technology enhancement, many leading automotive and technology companies have turned their attention towards developing advanced driver assistance systems (ADAS) and self-driving vehicles. Autonomous vehicles are expected to have their first big impact in closed areas, such as mines, harbors and loading/offloading sites. In such areas, the legal requirements are less restrictive and the surrounding environment is more controlled and predictable compared to urban areas. Expected positive outcomes include increased productivity and safety, reduced emissions and the possibility to relieve the human from performing complex or dangerous tasks. Within these sites, different truck and trailer systems are used to transport materials. These systems are composed of several interconnected modules, and are thus large and highly unstable while reversing. This thesis addresses the problem of designing efficient motion planning and feedback control frameworks for such systems.

First, a cascade controller for a reversing truck with a dolly-steered trailer is presented. The unstable modes of the system is stabilized around circular equilibrium configurations using a gain-scheduled linear quadratic (LQ) controller together with a higher-level pure pursuit controller to enable path following of piecewise linear reference paths. The cascade controller is then used within a rapidly-exploring random tree (RRT) framework and the complete motion planning and control framework is demonstrated on a small-scale test vehicle.

Second, a path following controller for a reversing truck with a dolly-steered trailer is proposed for the case when the obtained motion plan is kinematically feasible. The control errors of the system are modeled in terms of their deviation from the nominal path and a stabilizing LQ controller with feedforward action is designed based on the linearization of the control error model. Stability of the closed-loop system is proven by combining global optimization, theory from linear differential inclusions and linear matrix inequality techniques.

Third, a systematic framework is presented for analyzing stability of the closed-loop system consisting of a controlled vehicle and a feedback controller, executing a motion plan computed by a lattice planner. When this motion planner is considered, it is shown that the closed-loop system can be modeled as a nonlinear hybrid system. Based on this, a novel method is presented for analyzing the behavior of the tracking error, how to design the feedback controller and how to potentially impose constraints on the motion planner in order to guarantee that the tracking error is bounded and decays towards zero.

Fourth, a complete motion planning and control solution for a truck with a dolly-steered trailer is presented. A lattice-based motion planner is proposed, where a novel parametrization of the vehicle’s state-space is proposed to improve online planning time. A time-symmetry result is established that enhance the numerical stability of the numerical optimal control solver used for generating the motion primitives. Moreover, a nonlinear observer for state estimation is developed which only utilizes information from sensors that are mounted on the truck, making the system independent of additional trailer sensors. The proposed framework is implemented on a full-scale truck with a dolly-steered trailer and results from a series of field experiments are presented.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2019. p. 78
Series
Linköping Studies in Science and Technology. Licentiate Thesis, ISSN 0280-7971 ; 1832
National Category
Control Engineering Vehicle Engineering Robotics Embedded Systems Computer Engineering
Identifiers
urn:nbn:se:liu:diva-153892 (URN)10.3384/lic-diva-153892 (DOI)9789176851302 (ISBN)
Presentation
2019-01-25, Ada Lovelace, B-building, Campus Valla, 10:15 (English)
Opponent
Supervisors
Available from: 2019-01-17 Created: 2019-01-17 Last updated: 2019-01-22Bibliographically approved

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