A New Mobile Robot Guidance System Using Optical Reflectors

Mesaki, Yoya; Masuda, I.

doi:10.1109/iros.1992.587407

Cited by 8 publications

(4 citation statements)

References 10 publications

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“…Another typical form is landmark-based navigation which is more practical and efficient since it does not require a three-dimensional environment model. However, in case of the landmark-based navigation, we need special patterns or objects in the robot environment [3], [4], [5]. Therefore, Hong et a/.…”

Section: Indoor Mobile Robot Navigationmentioning

confidence: 99%

Sensor Fusion for Omnidirectional Sensor-Based Local Homing Navigation using Fuzzy Arithmetic

Bang¹,

Kim²,

Chung³

1998

Intelligent Automation & Soft Computing

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In this paper, we propose a novel environment modeling method for local homing for indoor mobile navigation. An environment model is constructed from a set of omnidirectional sensor data obtained by rotating an ultrasonic sensor and a vision sensor. We develop a sensor fusion method to deal with uncertainties in the two types of sensor data. The proposed sensor fusion method uses fuzzy numbers to represent subjective knowledge and manipulates uncertain quantities using fuzzy arithmetic. Using the proposed method, we can determine a more precise geometric relation between the current location and the target location. To evaluate the proposed environment modeling and to verify the sensor fusion method, experiments are carried out in an indoor environment.Recently various types of sensors have been applied to obtain more accurate data and to improve the intelligence because a single sensor does not provide sufficient information needed for an intelligent system[7], [8]. Such multiple sensors increase the reliability of the sensory information and provide more complete information about the environment by combining partial information from each sensor. But, as various types of sensors are involved, an appropriate sensor fusion method is required to handle the uncertainties effectively. Sensor fusion, as defined in this paper, refers to any stage in the integration process where there is an actual combination( or fusion) of different sources of sensory information into one representational format. The fusion of data or information from multiple sensors or a single sensor over time can take place at different levels of representation[9], [10]. So far, the probabilistic approach has dominated much of the work on the representation and manipulation of uncertainties [ 11]. However, it is difficult to obtain probability density functions for a variety of environments [12]. Furthermore, if we know the probability density functions(p.d.fs), the calculation with p.d.fs is highly complicated [13]. However, when fuzzy arithmetic is used, we can represent the environment using sensor information with more ease and also incorporate the expert's knowledge about the properties of sensors.Inherent uncertainties in the sensory information, which can arise due to noise, changes in the environment, or changes in the system itself, can be represented in different ways. If we use fuzzy numbers, the degree of possibility can be easily represented. When a sensor provides a measured value m about a feature f of an environment, the sensor is actually providing a linguistic proposition of the form of "the feature f is about m". A possibility distribution can be determined to represent the degree of possibility that any x in the referential set X might actually be the true value f [ 14]. In general, the mean value of the fuzzy number represents the actual sensor measurement and the spread of the fuzzy number represents the uncertainty level, which reflects the physical properties of each sensor.

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Section: Indoor Mobile Robot Navigationmentioning

confidence: 99%

Sensor Fusion for Omnidirectional Sensor-Based Local Homing Navigation using Fuzzy Arithmetic

Bang¹,

Kim²,

Chung³

1998

Intelligent Automation & Soft Computing

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“…Another idea is that some localization systems developed in the field of robot or autonomous vehicle are applied for detecting and recording position. They uses laser beam [1] [2], ultrasound [4] [5], infrared LED [3], and so on. They usually request that some beacons or reflectors are attached in the target place previously and it is troublesome.…”

Section: Introductionmentioning

confidence: 99%

Development of position recording system on structural surface using laser pointer

Seki

Fukumura

Kamiya

et al. 2011

IECON 2011 - 37th Annual Conference of the IEEE Industrial Electronics Society

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Surfaces of old structures are inspected by workers and the positions of the damaged places are manually recorded for their maintenance. In order to lighten this work, we propose a novel system to record position on structural surface by a laser pointer and a fisheye camera. When a worker traces the target surface with a laser light, its position in the camera image is detected after some image processing and the position is recorded directly on the surface image. In order to make the image processing easy and reliable, a tilted camera is placed away from workers, the subtraction of the images with the blinking circular beam of a laser pointer is utilized, and the pattern matching by templates of circles with several sizes is applied. Since this system needs no beacons for positioning, it is simple and inexpensive. It can be used in noisy environment with much traffic. We made experiments using the prototype system and confirmed that we can record position with good accuracy and reliability.

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“…Therefore, we think that partially autonomous operations are a better way to make the tele-operation easier. Several methods to move the robot autonomously have been already investigated [3].…”

Section: Resultsmentioning

confidence: 99%

“…There was little difference between the two interfaces in the time taken to control the camera. 3. The time taken to observe the obstacles and walls, to know thier relative locations, was shorter for interface A than interface B.…”

Section: Methodsmentioning

confidence: 96%

A visual interface for security robots

Takahashi

Masuda

[1992] Proceedings IEEE International Workshop on Robot and Human Communication

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In this paper, we evaluate the visual tele-presence interface for a mobile robot which was developed as a testbed for a new robotic security system. This robot is fully tele-operated in the first stage and is to be used to identify a fire, fight an initial Are and detect intruders.We experimented driving the robot through a test path to evaluate this interface. A Axed display was used as a comparison to the visual interface.We found that, due to its performance and other restrictions, the visual tele-presence interface is not suitable to tele-operate this kind of mobile robot.

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A New Mobile Robot Guidance System Using Optical Reflectors

Cited by 8 publications

References 10 publications

Sensor Fusion for Omnidirectional Sensor-Based Local Homing Navigation using Fuzzy Arithmetic

Sensor Fusion for Omnidirectional Sensor-Based Local Homing Navigation using Fuzzy Arithmetic

Development of position recording system on structural surface using laser pointer

A visual interface for security robots

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