An obstacle detection method by fusion of radar and motion stereo

Kato, T.; Ninomiya, Yoshiki; Masaki, I.

doi:10.1109/tits.2002.802932

Cited by 135 publications

(49 citation statements)

References 13 publications

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“…In accordance with these reinforced legal regulations, automobile manufacturers have been actively conducting studies on an advanced driver assistance system (ADAS), which supports a driver using cutting-edge technologies for driving processes. An ADAS includes systems for blind-spot detection, lane departure detection and prevention, and automatic emergency braking [1,2]. To implement these ADAS technologies, sensors are important to identify the surrounding environment.…”

Section: Introductionmentioning

confidence: 99%

Performance Limits Analysis of Collision Detection System Based on Automotive Radar in Ramp

Cho¹,

Kim

2014

Advanced Science and Technology Letters

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Abstract.A collision detection system with a radar sensor might not be able to detect a forward vehicle when the host vehicle is on a ramp road. In this study, we researched the performance limits of radar under various ramp road conditions. The degree of risk between the host and forward vehicles was determined using the time-to-collision value. The simulation results show that the collision risk index rapidly changes in accordance with the road gradient. In addition, the area of radar sensors' performance limits was quantitatively analyzed.

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Section: Introductionmentioning

confidence: 99%

Performance Limits Analysis of Collision Detection System Based on Automotive Radar in Ramp

Cho¹,

Kim

2014

Advanced Science and Technology Letters

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“…The camera detects the features required for navigating, while the scanner senses the obstacles (in contrast with other works, such as [4], only one sensor is used to detect the obstacles). In the past, obstacle avoidance has been integrated in visual navigation [5], [6] and path following [7], [8], by using the path geometry or the environment 3D model (including, for example, walls and doors).…”

Section: Introductionmentioning

confidence: 99%

A new tentacles-based technique for avoiding obstacles during visual navigation

Cherubini

Spindler

Chaumette

2012

2012 IEEE International Conference on Robotics and Automation

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Abstract-In this paper, we design and validate a new tentacle-based approach, for avoiding obstacles during appearance-based navigation with a wheeled mobile robot. In the past, we have developed a framework for safe visual navigation. The robot follows a path represented as a set of key images, and during obstacle circumnavigation, the on-board camera is actuated to maintain scene visibility. In those works, the model used for obstacle avoidance was obtained using a potential vector field. Here, a more sophisticated and efficient method, that exploits the robot kinematic model, and predicts collision at look-ahead distances, is designed and integrated in that framework. Outdoor experiments comparing the two models show that the new approach presents many advantages. Higher speeds and precision can be attained, very cluttered scenarios involving large obstacles can be successfully dealt with, and the control inputs are smoother.

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“…Here, we focus on this problem: a wheeled vehicle, equipped with an actuated pinhole camera and with a forward-looking range scanner, must follow a visual path represented by key images, without colliding with the ground obstacles. The camera detects the features required for navigating, while the scanner senses the obstacles (in contrast with other works, such as [24], only one sensor is used to detect the obstacles). As in [22], we guarantee that obstacle avoidance has no effect on visual navigation.…”

Section: Introductionmentioning

confidence: 99%

A redundancy-based approach for visual navigation with collision avoidance

Cherubini

Spindler

Chaumette

2011

2011 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Proceedings

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Abstract-We propose an autonomous vehicle guidance framework which combines visual navigation with simultaneous obstacle avoidance. The method was originally designed in [1], but real outdoor experiments and major improvements have been added in this paper. Kinematic redundancy guarantees that obstacle avoidance and navigation are achieved concurrently. The two tasks are realized both in an obstacle-free and in a dangerous context, and the control law is smoothened in between. The experiments show that with our method, the vehicle can replay a taught visual path while avoiding collisions.

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An obstacle detection method by fusion of radar and motion stereo

Cited by 135 publications

References 13 publications

Performance Limits Analysis of Collision Detection System Based on Automotive Radar in Ramp

Performance Limits Analysis of Collision Detection System Based on Automotive Radar in Ramp

A new tentacles-based technique for avoiding obstacles during visual navigation

A redundancy-based approach for visual navigation with collision avoidance

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