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Shraga Shoval

Researcher at Ariel University

Publications -  126
Citations -  1642

Shraga Shoval is an academic researcher from Ariel University. The author has contributed to research in topics: Mobile robot & Computer science. The author has an hindex of 17, co-authored 100 publications receiving 1307 citations. Previous affiliations of Shraga Shoval include University of South Australia & Technion – Israel Institute of Technology.

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Journal ArticleDOI

NavBelt and the Guide-Cane [obstacle-avoidance systems for the blind and visually impaired]

TL;DR: The NavBelt and GuideCane are computerized devices based on advanced mobile robotics obstacle-avoidance technologies that provide acoustic signals via a set of stereo earphones that guides the user around obstacles or displays a virtual acoustic panoramic image of the traveler's surroundings.
Journal ArticleDOI

Auditory guidance with the Navbelt-a computerized travel aid for the blind

TL;DR: The use of a mobile robot obstacle avoidance system as a guidance device for blind and visually impaired people is described and implemented and tested in a new travel aid for the blind, called the Navbelt.
Journal ArticleDOI

The NavBelt-a computerized travel aid for the blind based on mobile robotics technology

TL;DR: Experimental results with the NavBelt simulator and a portable prototype show that users can travel safely in an unfamiliar and cluttered environment at speeds of up to 0.8 m/s.
Proceedings ArticleDOI

Mobile robot obstacle avoidance in a computerized travel aid for the blind

TL;DR: The use of a mobile robot obstacle avoidance system as a guidance device for blind and visually impaired people, where auditory signals can guide the blind traveler around obstacles, or alternatively, they can provide an "acoustic image" of the surroundings.
Proceedings ArticleDOI

Using coded signals to benefit from ultrasonic sensor crosstalk in mobile robot obstacle avoidance

TL;DR: A method in which data generated by crosstalk is actually used to generate more reliable and accurate object detection by assigning a unique code to the signals emitted by each sonar, so that the source sonar can be identified even if its signal's echo is received by another sonar.