The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

Many robotics tasks require an ability to determine quickly the nature of the terrain surrounding the robot. In cross country navigation in particular, the robot needs to know where the vegetation is and where the hard obstacles are. I have developed a general system which has successfully allowed real-time terrain typing in the NavLab II autonomous vehicle. This system and training paradigm are based on standard neural network technology and allow the robot to learn arbitrary non-linear mappings from color and texture space to terrain space.

Notes

Sponsor: NSF

Grant ID: DACA76-89-C-0014, DAAE07-90-C-R059

Number of pages: 12

Text Reference

Ian Davis, "Neural Networks for Real-Time Terrain Typing," tech. report CMU-RI-TR-95-06, Robotics Institute, Carnegie Mellon University, January, 1995

BibTeX Reference

@techreport{Davis_1995_365,
   author = "Ian Davis",
   title = "Neural Networks for Real-Time Terrain Typing",
   institution = "Robotics Institute",
   month = "January",
   year = "1995",
   number= "CMU-RI-TR-95-06",
   address= "Pittsburgh, PA",
}

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