Experimental Analysis of Overhead Data Processing To Support Long Range Navigation

Abstract— Long range navigation by unmanned ground vehicles continues to challenge the robotics community. Efficient navigation requires not only intelligent on-board perception and planning systems, but also the effective use of prior knowledge of the vehicle’s environment. This paper describes a system for supporting unmanned ground vehicle navigation through the use of heterogeneous overhead data. Semantic information is obtained through supervised classification, and vehicle mobility is predicted from available geometric data. This approach is demonstrated and validated through over 50 kilometers of autonomous traversal through complex natural environments.

• Type: Conference
• Year: 2006
• Where: IROS
• Authors: David Silver, Boris Sofman, Nicolas Vandapel, J. Andrew Bagnell, Anthony Stentz
• Keywords: Ground Vehicle Navigation, Intelligent On-board Perception, IROS 2006, Robotics, Unmanned Ground Vehicle