A Visual Template-Matching Method for Articulation Angle Measurement

Saxe, Christopher C De; Cebon, David

doi:10.1109/itsc.2015.108

Cited by 15 publications

(12 citation statements)

References 12 publications

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“…Different techniques for estimating the joint angle for a tractor with a semitrailer and for a car with a trailer using wide‐angle cameras are reported in Saxe and Cebon () and Caup, Salmen, Muharemovic, and Houben (), respectively. In Saxe and Cebon (), an image bank with images taken at different joint angles is first generated and during execution used to compare and match against the current camera image. Once a match is found, the corresponding joint angle is given from the matched image in the image bank.…”

Section: Background and Related Workmentioning

confidence: 99%

A path planning and path‐following control framework for a general 2‐trailer with a car‐like tractor

Ljungqvist

Evestedt²,

Axehill

et al. 2019

Journal of Field Robotics

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Maneuvering a general 2‐trailer with a car‐like tractor in backward motion is a task that requires a significant skill to master and is unarguably one of the most complicated tasks a truck driver has to perform. This paper presents a path planning and path‐following control solution that can be used to automatically plan and execute difficult parking and obstacle avoidance maneuvers by combining backward and forward motion. A lattice‐based path planning framework is developed in order to generate kinematically feasible and collision‐free paths and a path‐following controller is designed to stabilize the lateral and angular path‐following error states during path execution. To estimate the vehicle state needed for control, a nonlinear observer is developed, which only utilizes information from sensors that are mounted on the car‐like tractor, making the system independent of additional trailer sensors. The proposed path‐planning and path‐following control framework is implemented on a full‐scale test vehicle and results from simulations and real‐world experiments are presented.

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Section: Background and Related Workmentioning

confidence: 99%

A path planning and path‐following control framework for a general 2‐trailer with a car‐like tractor

Ljungqvist

Evestedt²,

Axehill

et al. 2019

Journal of Field Robotics

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“…The visual template-matching concept for articulation angle sensing for HGVs is summarised in Figure 1. 21 The concept builds on preliminary work by Harris, 18 using a single camera mounted to the rear of the tractor and a template-matching image processing method to determine articulation angle G.…”

Section: Summary Of the Template-matching Methodsmentioning

confidence: 99%

“…The method is limited to planar trailers, and the underlying trailer model excludes translational trailer motion which could yield errors at higher articulation angles. This work was later expanded in De Saxe and Cebon 21 in which the concept was validated in small scale experiments; however, computation was still comparably slow at 1 fps.…”

Section: Related Workmentioning

confidence: 99%

Measurement of articulation angle by image template matching

Saxe

Cebon

2019

Proceedings of the Institution of Mechanical Engineers, Part D:

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Articulated heavy goods vehicles and long combination vehicles offer improved efficiency and emissions but reduced low-speed manoeuvrability and high-speed stability compared to rigid lorries. Active control systems can help to address these issues but require additional instrumentation, particularly articulation angle sensing. Existing commercial and research solutions for articulation sensing are limited either in terms of measurement accuracy or practicality. In this paper, a camera-based articulation angle sensing concept using template-matching and an Unscented Kalman Filter is investigated, including detailed simulation and full-scale vehicle experiments. The effects of aliasing and trailer pitch angle are studied, and a correction model for trailer pitch is proposed. The sensing system demonstrates superior measurement accuracy compared to the published literature, with root mean square errors of 0.8°–1.8° for articulation angles up to 37° in full-scale experiments. The sensor solution proposed in this work addresses more of the practical criteria for this problem than the comparable solutions in the literature. It does so through the novel camera and image processing system which is unique to this application. The proposed sensor offers acceptable measurement accuracy in real-time, is non-contact, requires minimal knowledge of trailer parameters and is compatible with semi-trailers and rigid draw-bar trailers.

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“…Compared to other odometry systems such as wheel speed sensors and GPS , 1 visual odometry offers high precision, low-cost hardware and independence from traction conditions. Although vehicle-based visual odometry is commonplace in autonomous vehicles (see, for example, [22,24]), little work has been done with heavy vehicles, with the exception of recent work by Miao, Harris, de Saxe and Cebon [18,[25][26][27].…”

Section: Visual Odometrymentioning

confidence: 99%

Estimation of trailer off-tracking using visual odometry

Saxe

Cebon

2018

Vehicle System Dynamics

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High-capacity vehicles have been shown to be highly effective in reducing emissions associated with road freight transport. However, the reduced manoeuvrability of long vehicles often necessitates the use of active trailer steering. Path-following trailer steering systems are very effective in this regard, but are currently limited to onhighway applications due to the manner in which trailer off-tracking is estimated. In this work, a novel trailer off-tracking measurement concept is introduced which is independent of wheel slip and ground surface conditions, and requires no additional sensor measurements or parameter data from the tractor. The concept utilises a stereo camera pair affixed to the trailer and a visual odometry-based algorithm to calculate off-tracking. The concept was evaluated in detailed simulation and full-scale vehicle tests, demonstrating its feasibility and highlighting some important characteristics. RMS measurement errors of 0.11-0.12 m (3.3-3.6%) were obtained in a challenging visual environment.

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A Visual Template-Matching Method for Articulation Angle Measurement

Cited by 15 publications

References 12 publications

A path planning and path‐following control framework for a general 2‐trailer with a car‐like tractor

A path planning and path‐following control framework for a general 2‐trailer with a car‐like tractor

Measurement of articulation angle by image template matching

Estimation of trailer off-tracking using visual odometry

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