Ultrasonic Sensing For A Mobile Robot To Recognize An Environment - Measuring The Normal Direction Of Walls -

Nagashima, Yoshiaki; Yuta, Shin’ichi

doi:10.1109/iros.1992.594485

Cited by 47 publications

(16 citation statements)

References 8 publications

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“…Rough surfaces can be treated with other techniques (Bozma and Kuc 1991). The applications of primary interest are robot localization from sensing known environmental features, such as wall and corner positions (Leonard and Durrant-Whyte 1991, Nagashima and Yuta 1992, Manyika and DurrantWhyte 1993, and conversely, mapping of unknown environments for later use for localization and navigation (Bozma and Kuc 1991a, Iijima and Yuta 1992, Bozma and Kuc 1991, Elfes 1987, Crowley 1985, Moravec and Elfes 1985. Obstacle avoidance (Kuc 1990, Borenstein andKoren 1988) is another application of the sensor.…”

Section: Introductionmentioning

confidence: 99%

Mobile Robot Sonar for Target Localization and Classification

Kleeman

Kuc

1995

The International Journal of Robotics Research

251

188

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A novel sonar array is presented that has applications in mobile robotics for localization and mapping of indoor environments. The ultrasonic sensor localizes and classifies multiple targets in two dimensions to ranges of up to 8 meters. By accounting for effects of temperature and humidity, the system is accurate to within a millimeter and 0.1 degrees in still air. Targets separated by 10 mm in range can be discriminated. The error covariance matrix for these measurements is derived to allow fusion with other sensors. Targets are statistically classified into four reflector types: planes, corners, edges and unknown.The paper establishes that two transmitters and two receivers are necessary and sufficient to distinguish planes, corners and edges. A sensor array is presented with this minimum number of transmitters and receivers. A novel design approach is that the receivers are closely spaced so as to minimize the correspondence problem of associating different receiver echoes from multiple targets.A linear filter model for pulse transmission, reception, air absorption and dispersion is used to generate a set of templates for the echo as a function of range and bearing angle. The optimal echo arrival time is estimated from the maximum cross-correlation of the echo with the templates. The use of templates also allows overlapping echoes and disturbances to be rejected. Noise characteristics are modeled for use in the maximum likelihood estimates of target range and bearing. Experimental results are presented to verify assumptions and characterize the sensor.

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Section: Introductionmentioning

confidence: 99%

Mobile Robot Sonar for Target Localization and Classification

Kleeman

Kuc

1995

The International Journal of Robotics Research

251

188

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“…We have developed a ultrasonic range finding system A in which the following fundamental method is employed [4] [3]. Ultrasonic waves are discharged from a transmitter given comparatively long burst waves in order to vibrate its piezoelectric vibrator fully.…”

Section: Two Ultrasonic Ranging Systemsmentioning

confidence: 99%

Obstacle detectability of ultrasonic ranging system and sonar map understanding

Ohya

Ohno

Yuta

1996

Robotics and Autonomous Systems

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“…Because of these benefits, many robotics studies use acoustic echolocation for localization problems [4,5]. Additionally, ultrasonic distance measurement, which uses an acoustic system, is a relatively flexible approach for environmental recognition in robotic systems [6,7]. Ultrasonic distance measurements can be determined simply by using the time-of-flight (TOF) method, which is a measurement of the time for sound waves to travel between the sound source and the object, multiplied by the sound velocity.…”

Section: Introductionmentioning

confidence: 99%