Sliding mode lateral motion control for automatic steering of vehicles

Zhang, J.R.; Xu, Shengyuan; Rachid, A.

doi:10.23919/ecc.2001.7076498

Cited by 7 publications

(5 citation statements)

References 18 publications

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“…The problem of planning and controlling vehicles with Ackermann steering kinematics has been widely investigated, especially in the context of self-driving cars and outdoor autonomous robots moving in urban environments [12]. Several solutions have been proposed and they can be roughly divided in two categories, non-predictive ( [3], [4], [5], [6], [7]) and predictive ( [8], [9], [10], [11]).…”

Section: A Related Workmentioning

confidence: 99%

“…The formers are not able to plan the motion of the vehicle, therefore it is necessary to compute the trajectory before applying the control law. In Zhang et al [3] the authors propose a sliding mode control law specifically designed for second order differential equation models. The effectiveness of this approach is extensively tested in simulation.…”

Section: A Related Workmentioning

confidence: 99%

“…The problems of planning and control of ground vehicles have been widely investigated in the literature, e.g. [3]- [11]. Typical application scenarios include self-driving vehicles and autonomous racing.…”

Section: Introductionmentioning

confidence: 99%

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A Navigation Architecture for Ackermann Vehicles in Precision Farming

Carpio

Potena

Maiolini

et al. 2020

IEEE Robot. Autom. Lett.

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In this letter, inspired by the needs of the European H2020 Project PANTHEON 1 , we propose a full navigation stack purposely designed for the autonomous navigation of Ackermann steering vehicles in precision farming settings. The proposed stack is composed of a local planner and a pose regulation controller, both implemented in ROS. The local planner generates, in real-time, optimal trajectories described by a sequence of successive poses. The planning problem is formulated as a real-time cost-function minimization problem over a finite time horizon where the Ackermann kinematics and the presence of obstacles are encoded as constraints. The control law ensures the convergence toward each of these poses. To do so, in this paper we propose a novel non-smooth control law designed to ensure the solvability of the pose regulation problem for the Ackermann vehicle. Theoretical characterization of the convergence property of the proposed pose regulation controller is provided. Numerical simulations along with real-world experiments are provided to corroborate the effectiveness of the proposed navigation strategy.

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Section: A Related Workmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

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A Navigation Architecture for Ackermann Vehicles in Precision Farming

Carpio

Potena

Maiolini

et al. 2020

IEEE Robot. Autom. Lett.

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“…In the literature, several control techniques for autonomous racing are known. They can be roughly categorized into two categories, predictive (Liniger et al, 2015;Verschueren et al, 2014;Funke et al, 2017;Rosolia et al, 2017;Liniger and Lygeros, 2019) and non-predictive controllers (Zhang et al, 2001;Kritayakirana and Gerdes, 2012;Klomp et al, 2014). Since non-predictive racing controllers are not able to plan the motion of the car, it is necessary to compute the racing line beforehand.…”

Section: Related Workmentioning

confidence: 99%

AMZ Driverless: The Full Autonomous Racing System

Kabzan¹,

Valls²,

Reijgwart³

et al. 2019

Preprint

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This paper presents the algorithms and system architecture of an autonomous racecar. The introduced vehicle is powered by a software stack designed for robustness, reliability, and extensibility. In order to autonomously race around a previously unknown track, the proposed solution combines state of the art techniques from different fields of robotics. Specifically, perception, estimation, and control are incorporated into one high-performance autonomous racecar. This complex robotic system, developed by AMZ Driverless and ETH Zurich, finished 1st overall at each competition we attended: Formula Student Germany 2017, Formula Student Italy 2018 and Formula Student Germany 2018. We discuss the findings and learnings from these competitions and present an experimental evaluation of each module of our solution.

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“…In related literature, several control techniques for autonomous racing are known. They can be roughly categorized into two categories: predictive (Funke, Brown, Erlien, & Gerdes, 2017; Liniger, Domahidi, & Morari, 2015; Liniger & Lygeros, 2019; Rosolia, Carvalho, & Borrelli, 2017; Verschueren, De Bruyne, Zanon, Frasch, & Diehl, 2014) and nonpredictive controllers (Kapania & Gerdes, 2015; Klomp, Olsson, & Sandberg, 2014; Kritayakirana & Gerdes, 2012; Zhang, Xu, & Rachid, 2001). Since nonpredictive racing controllers are not able to plan the motion of the car, it is necessary to compute the racing line beforehand.…”

Section: Introductionmentioning

confidence: 99%

AMZ Driverless: The full autonomous racing system

Kabzan

Valls

Reijgwart

et al. 2020

Journal of Field Robotics

105

View full text Add to dashboard Cite

This paper presents the algorithms and system architecture of an autonomous racecar. The introduced vehicle is powered by a software stack designed for robustness, reliability, and extensibility. To autonomously race around a previously unknown track, the proposed solution combines state of the art techniques from different fields of robotics. Specifically, perception, estimation, and control are incorporated into one high‐performance autonomous racecar. This complex robotic system, developed by AMZ Driverless and ETH Zürich, finished first overall at each competition we attended: Formula Student Germany 2017, Formula Student Italy 2018 and Formula Student Germany 2018. We discuss the findings and learnings from these competitions and present an experimental evaluation of each module of our solution.

show abstract

Sliding mode lateral motion control for automatic steering of vehicles

Cited by 7 publications

References 18 publications

A Navigation Architecture for Ackermann Vehicles in Precision Farming

A Navigation Architecture for Ackermann Vehicles in Precision Farming

AMZ Driverless: The Full Autonomous Racing System

AMZ Driverless: The full autonomous racing system

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