Abstract

Practical autonomous robotic vehicles require dependable methods for accurately identifying course or roadway boundaries. The authors have developed a method to reliably extract the boundary line using simple dynamic thresholding, noise filtering, and blob removal. This article describes their efforts to apply this procedure in developing an autonomous vehicle.

Highlights

  • Follow this and additional works at: https://digitalcommons.uri.edu/gsofacpubs Part of the Ocean Engineering Commons, Oceanography Commons, and the Robotics

  • The potential for reducing automobile accidents deatbs and injuries is, in itself, a compelling reason to pursue systems that enhance driver performance and minimize errors due to poor judgement or inaccurate driver perception.‘. In pursuit of such systems, the Society of Automotive Engineers, the Association for Unmanned Vehicle Systems, and Oakland University jointly sponsor the annual Unmanned Ground Robotics Competition. This competition fosters the development of small robotic vehicles that can autonomously navigate an outdoor obstacle course approximately 700 feet long

  • The major hurdle for a mobile robot’s vision system is in ensuring reliable perception, which guarantees efficient autonomous navigation: “Perception robustness depends essentially upon the reliability of the road-edge extraction algorithm.”2Furthermore, the system must correctly identify its path under a wide range of light and weather condtions

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Summary

Charles Reinholtz

Follow this and additional works at: https://digitalcommons.uri.edu/gsofacpubs Part of the Ocean Engineering Commons, Oceanography Commons, and the Robotics. The potential for reducing automobile accidents deatbs and injuries is, in itself, a compelling reason to pursue systems that enhance driver performance and minimize errors due to poor judgement or inaccurate driver perception.‘. In pursuit of such systems, the Society of Automotive Engineers, the Association for Unmanned Vehicle Systems, and Oakland University jointly sponsor the annual Unmanned Ground Robotics Competition. This competition fosters the development of small robotic vehicles that can autonomously navigate an outdoor obstacle course approximately 700 feet long. The vehicles must be completely autonomous, PR( :TICAL AUTOL$0 fOUS ROBOTIC IEHICLES REQ TRE

Path following
Pixel number
Pixel intensity
IEEE INTELLIGENT SYSTEMS
Vehicle control and navigation
Use of passive optical devices for improved algorithm performance
Full Text
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