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Carnegie Mellon Robotics Institute

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Abstract

For autonomously navigating vehicles, the automatic generation of dense geometric models of the environment is a computationally expensive process. Yet, analysis suggests that some approaches to mapping the environment in mobility scenarios can waste significant computational resources. This paper proposes a relatively simple method of approaching the minimum required perceptual throughput in a terrain mapping system, and hence the fastest possible update of the environmental model. We accomplish this by exploiting the constraints of typical mobility scenarios. The technique proposed will be applicable to any application that models the environment with a terrain map or other 2-1/2 D representation.

Notes

Text Reference

Alonzo Kelly and Anthony (Tony) Stentz, "Minimum Throughput Adaptive Perception for High Speed Mobility," Proceedings of the IEEE/RJS International Conference on Intelligent Robotic Systems, September, 1997, pp. 215 - 223.

BibTeX Reference

@inproceedings{Kelly_1997_1203,
   author = "Alonzo Kelly and Anthony (Tony) Stentz",
   title = "Minimum Throughput Adaptive Perception for High Speed Mobility",
   booktitle = "Proceedings of the IEEE/RJS International Conference on Intelligent Robotic Systems",
   pages = "215 - 223",
   month = "September",
   year = "1997",
   volume = "1",
}

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