Ground Plane Detection for Autonomous Robots in Complex Environments Inclined with Flexed Far-Field Terrains

I.O. Osunmakinde and T. Ndhlovu (South Africa)


Robotics, Intelligence, Detection, and Emergent SituationAwareness


Ground plane detection is often used as one of the important safety key operations to address some of the issues associated with autonomous navigation in complex environments. Despite the strides on related detection methods developed for such navigation, detection of ground planes inclined with flexed far-fields to alleviate robot short-sightedness, with a guarantee on tarred and coarse terrains have received little attention. Finding a solution to these uncertainty problems is a challenge. In this paper, collective intelligence of the Emergent Situation Awareness (ESA) technology is proposed as a supportive strategy for autonomous robotic navigation. The ability to reveal uncertainties over time on flexed far field is a ground plane detection strategy embedded in the complex environments. Experimental evaluations of the ESA by benchmarking the results of publicly available roads promise that collective intelligence will one day put an end to most autonomous ground plane detection problems. Such detection on flexed far fields tremendously contributes to good navigational strategies for robotic vehicles being cautious of road accidents.

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