Obstacle Avoidance Method for Multi-Agent Robots Using IR Sensor and Image Information

전병승,; 이도영,; 최인환,; 모영학,; 박정민,; 임묘택,

doi:10.5302/j.icros.2012.18.12.1122

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…Thanks to these approaches, a features dimensionality is reduced with minimal precision loss using an unsupervised method. The dimensionality reduction problem with application to vision systems is exhaustively studied in [110].…”

Section: How Are Vision Systems Applied In Gmrs?mentioning

confidence: 99%

“…The avoidance motion is determined using FL-AMS, which considers environmental conditions such as the size of obstacles and the available space. Another paper [110] presents an obstacle avoidance method for a scout robot or an industrial robot in an unknown environment using an IR sensor and a vision system. In the proposed method, robots share information as to where the obstacles are located in real-time; thus, the robots choose the best path for obstacle avoidance.…”

Section: Trajectory Estimationmentioning

confidence: 99%

See 1 more Smart Citation

A Taxonomy of Vision Systems for Ground Mobile Robots

Gómez

Fernández-Caballero

García-Varea

et al. 2014

International Journal of Advanced Robotic Systems

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This paper introduces a taxonomy of vision systems for ground mobile robots. In the last five years, a significant number of relevant papers have contributed to this subject. Firstly, a thorough review of the papers is proposed to discuss and classify both past and the most current approaches in the field. As a result, a global picture of the state of the art of the last five years is obtained. Moreover, the study of the articles is used to put forward a comprehensive taxonomy based on the most up-to-date research in ground mobile robotics. In this sense, the paper aims at being especially helpful to both budding and experienced researchers in the areas of vision systems and mobile ground robots. The taxonomy described is devised from a novel perspective, namely in order to respond to the main questions posed when designing robotic vision systems: why?, what for?, what with?, how?, and where? The answers are derived from the most relevant techniques described in the recent literature, leading in a natural way to a series of classifications that are discussed and contextualized. The article offers a global picture of the state of the art in the area and discovers some promising research lines.

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Section: How Are Vision Systems Applied In Gmrs?mentioning

confidence: 99%

Section: Trajectory Estimationmentioning

confidence: 99%

A Taxonomy of Vision Systems for Ground Mobile Robots

Gómez

Fernández-Caballero

García-Varea

et al. 2014

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

show abstract

Hybrid Path Planning of Multi-Robots for Path Deviation Prevention

Wee¹,

Kim²,

Choi³

et al. 2013

Journal of Institute of Control, Robotics and Systems

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This paper suggests a hybrid path planning method of multi-robots, where a path deviation prevention for maintaining a specific formation is implemented by using repulsive function, A* algorithm and UKF (Unscented Kalman Filter). The repulsive function in potential field method is used to avoid collision among robots and obstacles. A* algorithm helps the robots to find optimal path. In addition, error estimation based on UKF guarantees small path deviation of each robot during navigation. The simulation results show that the swarm robots with designated formation successfully avoid obstacles and return to the assigned formation effectively.

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Obstacle Information Transfer and Control Method using Haptic Device consist of Vibration Motors

Lee¹,

Noh²,

Kang³

et al. 2014

Journal of Institute of Control, Robotics and Systems

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In this paper, a new haptic device is proposed for the teleoperation, which can recognize the invisible environment of a mobile robot. With this new device, it is possible for the user to identify the location of an obstacle and to avoid it. The haptic device has been attached on the top of a joystick so that the user can remotely control the mobile robot to avoid the obstacles which are recognized by the ultrasonic sensors. Also, the invisible environment is recognized more accurately overlapping the data from the ultrasonic sensors. There are five vibration motors in the haptic device to indicate the direction of the obstacle. So the direction of the obstacle can be recognized by the vibration at the finger on each vibration motor. For various situations and surrounding environments, experiments are performed using fuzzy controller and overlapping ultrasonic sensors. The results demonstrate the effectiveness of the proposed haptic joystick.

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Obstacle Avoidance Method for Multi-Agent Robots Using IR Sensor and Image Information

Cited by 3 publications

References 9 publications

A Taxonomy of Vision Systems for Ground Mobile Robots

A Taxonomy of Vision Systems for Ground Mobile Robots

Hybrid Path Planning of Multi-Robots for Path Deviation Prevention

Obstacle Information Transfer and Control Method using Haptic Device consist of Vibration Motors

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