Road-Boundary Detection and Tracking Using Ladar Sensing

Wijesoma, W.S.; Kodagoda, Sarath; Balasuriya, A.

doi:10.1109/tra.2004.825269

Cited by 213 publications

(119 citation statements)

References 19 publications

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“…대표적인 방법이 카메라 (vision)를 이용한 방법으로 현재도 이 분야에 대한 연구는 활발히 진행되고 있다 [1,2]. 다른 기술로는 GPS(global positioning system)를 이용하거나 적외선(infra red) 레이더 감지센서를 이용하는 방법의 연구가 활발히 진행되고 있다 [3][4][5].…”

Section: 서 론unclassified

Development of Steering Actuator for Unmanned Vehicle Based on Magnetic Marker

Im¹,

Ryoo²

2009

Journal of Korean Institute of Intelligent Systems

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In this paper, a steering actuator is designed and developed for an unmanned vehicle based on magnetic marker. One of the most important component of an unmanned vehicle is a steering actuator to follow magnetic road. Thus, we develop a steering actuator using a stepping motor and adopt to a new frequency control method depended on speed of the vehicle. In order to verify the usability of the developed system, the setup of unmanned vehicle installed the designed steering actuator is tested on magnetic road.

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Section: 서 론unclassified

Development of Steering Actuator for Unmanned Vehicle Based on Magnetic Marker

Im¹,

Ryoo²

2009

Journal of Korean Institute of Intelligent Systems

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“…Moreover, road extraction from remote sensing images is a critical task in image processing. The reason lies in that recognition of roads is a key problem since they form an important GIS layer in significant civilian and military applications including navigation or location aware systems and emergency planning systems for evacuation and fire response [6,7,8,9]. Automatic road extraction algorithm can reduce both time and labor to construct and update the road spatial database in such applications.…”

Section: Introductionmentioning

confidence: 99%

A Novel Road Extraction Algorithm for High Resolution Remote Sensing Images

Teng¹,

Shun-lin²,

Zhan³

2014

Appl. Math. Inf. Sci.

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Automatic road extraction from the high resolution remote sensing images is of great importance in intelligent transportation and image processing. Hence, in this paper, an effective road extraction algorithm for high resolution remote sensing images based on the circular projection transformation is proposed. The main idea of the proposed algorithm lies in that the road extraction results are obtained by selecting a suitable initial template, and then search the matched templates through moving the initial template in two directions. Firstly, the circular projection vector of the initial template is achieved by calculating the circular projection value at a specific radius. Secondly, the optimal radius of the circle in circular projection transformation and the length of the seeking step and the seeking angle are determined. Thirdly, for each seeking step the similarity between the target template and the initial template is computed, and the template with the highest similarity is chosen. Finally, roads can be detected by the correct direction by exchanging the first two detected points. To make performance evaluation, the IKONOS dataset is utilized and DMES and AUA algorithm are compared. The experimental results demonstrate that the proposed algorithm can automatic the roads from high resolution remote sensing images effectively and efficiently.

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“…Feature extraction in this space can be based on finding and filtering the straight segments that correspond to the road surface and road boundaries. This has been achieved with considerable success as shown in [3] for navigation at low speeds (up to 4 m/s) in urban environments. Fig.…”

Section: Road Feature Extractionmentioning

confidence: 99%

“…Recursive estimation of these parameters using Kalman filtering techniques has become a standard for road (and many other types of) estimation, and this approach has been applied in recent years for human navigation on well-structured paved roads with relatively clear boundary markings (see for example [1], [2], [3]). Common assumptions for these environments include planar road geometry, negligible sensor pitch and roll, and that the vehicle is traveling along the center of the road or lane.…”

Section: Introductionmentioning

confidence: 99%

Model-based estimation of off-highway road geometry using single-axis LADAR and inertial sensing

Cremean

Murray

Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006.

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Abstract-This paper applies some previously studied extended Kalman filter techniques for planar road geometry estimation to the domain of autonomous navigation of off-highway vehicles. In this work, a clothoid model of the road geometry is constructed and estimated recursively based on road features extracted from single-axis LADAR range measurements. We present a method for feature extraction of the road centerline in the image plane, and describe its application to recursive estimation of the road geometry. We analyze the performance of our method against simulated motion of varied road geometries and against closed-loop detection, tracking and following of desert roads. Our method accomodates full 6 DOF motion of the vehicle as it navigates, constructs consistent estimates of the road geometry with respect to a fixed global reference frame, and requires an estimate of the sensor pose for each range measurement.

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Road-Boundary Detection and Tracking Using Ladar Sensing

Cited by 213 publications

References 19 publications

Development of Steering Actuator for Unmanned Vehicle Based on Magnetic Marker

Development of Steering Actuator for Unmanned Vehicle Based on Magnetic Marker

A Novel Road Extraction Algorithm for High Resolution Remote Sensing Images

Model-based estimation of off-highway road geometry using single-axis LADAR and inertial sensing

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