Learning and prediction of slip from visual information

Citations Over TimeTop 1% of 2007 papers

Abstract

Abstract This paper presents an approach for slip prediction from a distance for wheeled ground robots using visual information as input. Large amounts of slippage which can occur on certain surfaces, such as sandy slopes, will negatively affect rover mobility. Therefore, obtaining information about slip before entering such terrain can be very useful for better planning and avoiding these areas. To address this problem, terrain appearance and geometry information about map cells are correlated to the slip measured by the rover while traversing each cell. This relationship is learned from previous experience, so slip can be predicted remotely from visual information only. The proposed method consists of terrain type recognition and nonlinear regression modeling. The method has been implemented and tested offline on several off‐road terrains including: soil, sand, gravel, and woodchips. The final slip prediction error is about 20%. The system is intended for improved navigation on steep slopes and rough terrain for Mars rovers. © 2006 Wiley Periodicals, Inc.

Related Papers

• Application of Non-oriented Traverse and Its Accuracy Analysis(2002)
• The Method about Application of Excel to Adjust Singleness Traverse in Facility(2004)
• The Design and Implement of Mine Traverse Management System(2004)
• Traverse Parameter Adjustment(2007)
• → Numerical Analysis of Contact Area under Slippage Conditions(2019)