Junior 3: A test platform for Advanced Driver Assistance Systems

Stanek, Ganymed; Langer, Dirk; Müller-Beßler, Bernhard; Huhnke, Burkhard

doi:10.1109/ivs.2010.5547997

Cited by 35 publications

(16 citation statements)

References 5 publications

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“…For another hand, road detection methods can also be categorized into feature-based [15,18,19,42], [16] 2008 Laser range finder, HDL 64E Lidar, binocular camera system Urban Junior 3 [17] 2010 Laser range finder,Riegl laser, HDL 64E Lidar, Bosch Radae, colored camera Urban VRC [36] 2013 Laser range finder, binocular camera system Complex environment model-based [25,44,46] and region-based [11,19]. Feature-based method extract road features such as color, texture, boundary, etc.…”

Section: Related Workmentioning

confidence: 99%

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Road detection in image by fusion laser points based on fuzzy SVM for a small ground mobile robot

Yuan

Tang

Zhao

2015

IFS

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Abstract. Road detection is still full of challenge for a small ground mobile robot with limited load capacity and computing resources which works in complex outdoor environment. This paper proposes a road detection method based on fuzzy support vector machine with on-line updating and retraining strategy. The algorithm extracts multi feature in image and trains a fuzzy support vector machine road classifier off-line by using few training samples. Then it detects road in laser points using a fuzzy clustering method based on maximum entropy principle. After calibrating the camera and laser range finder, and project laser points into the image, the algorithm chooses road samples with high confidence automatically according to range data and designs a rule to retraining the FSVM on-line when needed to improve its environmental adaptability. Experiments in outdoor campus environment indicate that the proposed algorithm is effective.

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Section: Related Workmentioning

confidence: 99%

“…is maximal under the constrains by Equation (17). This optimization problem can be reformulated as the maximization of the Lagrange…”

Section: Road Detection In Laser Pointsmentioning

confidence: 99%

Road detection in image by fusion laser points based on fuzzy SVM for a small ground mobile robot

Yuan

Tang

Zhao

2015

IFS

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“…With nonstationary and interacting robotic systems making progress by the day, as manifested by Google's autonomous car (Folsom 2011) and Junior, the driverless vehicle developed by Volkswagen and Stanford through DARPA (Stanek et al 2010), it Downloaded by [Northwestern University] at 02:05 07 February 2015 is only a matter of time before such technology becomes viable in isolated areas such as a mine. There is little reason why automation should proceed with the ultra-large-size equipment of today and not with much smaller units, perhaps in the 1 to 10 Ton class.…”

Section: Miningmentioning

confidence: 99%

Small Modular Infrastructure

Dahlgren¹,

Göçmen²,

Lackner³

et al. 2013

The Engineering Economist

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“…The PASallows the driver to park a car without manual steering control and has been commercializedrecently by many automakers [1]. Furthermore, the advanced parking assistance system (APAS) (o r called self-parking), which makes a vehicle parked autonomously, has been developed [2,3].For instance, autonomous driving including autonomous valet parking (A VP) was demonstrated in the Urban Challengein 2007, wh ich is an autonomous vehicle co mpetition [4,5]. Whereas it succeeded in showing the feasibility of autonomous drivingwith many additional sensors such as radars, lidars, cameras, and u ltrasonic sensors to recognize lane, obstacles, and a parking lot, it is interesting to remark that the detection range to identify an availab le parking lot in a public parking structure is still limited.…”

Section: Introductionmentioning

confidence: 99%

Lateral Vehicle Control for Semi-Autonomous Valet Parking with Consideration of Actuator Dynamics

Kim¹,

Song²

2013

CONTROL

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In this paper, the lateral control algorith m for semi-autonomous valet parking is presented and its feasibility is demonstrated via field driving tests. With the assumptions of low speed driving and s mall slip angle, a vehicle model with kinemat ic constraints of a steering actuator is proposed todesign the lateral controller. A model-based nonlinear control technique called dynamic surface control is applied to developa lateral control law for forward driving and backward parallel parking maneuvers. Furthermo re, the previewcontrol and filteringtechniquesare incorporated in the lateral controller to improve the tracking performance. Since there is measurement noiseregarding position and yaw angle and model uncertainty, it is necessary for the proposed lateral controller to be robust enough to compensate for noise and disturbance. Finally the performance of the lateral controller is validated experimentally v ia field testsas well as simulat ions.

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Junior 3: A test platform for Advanced Driver Assistance Systems

Cited by 35 publications

References 5 publications

Road detection in image by fusion laser points based on fuzzy SVM for a small ground mobile robot

Road detection in image by fusion laser points based on fuzzy SVM for a small ground mobile robot

Small Modular Infrastructure

Lateral Vehicle Control for Semi-Autonomous Valet Parking with Consideration of Actuator Dynamics

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