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Low Cost Localisation for Agricultural Robotics

Andrew English, David Ball, Patrick Ross, Ben Upcroft, Gordon Wyeth, Peter Corke

发表年份
2013
引用次数
17
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摘要

This paper presents a pose estimation approach that is resilient to typical sensor failure and suitable for low cost agricultural robots. Guiding large agricultural machinery with highly accurate GPS/INS systems has become standard practice, however these systems are inappropriate for smaller, lower-cost robots. Our positioning system estimates pose by fusing data from a low-cost global positioning sensor, low-cost inertial sensors and a new technique for vision-based row tracking. The results first demonstrate that our positioning system will accurately guide a robot to perform a coverage task across a 6 hectare field. The results then demonstrate that our vision-based row tracking algorithm improves the performance of the positioning system despite long periods of precision correction signal dropout and intermittent dropouts of the entire GPS sensor.

关键词

Global Positioning SystemComputer scienceArtificial intelligenceRobotRoboticsComputer visionDropout (neural networks)PoseReal-time computingTracking system

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