Minimum throughput adaptive perception for high speed mobility

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.

Authors

• Alonzo Kelly
• Anthony Stentz

Keywords

• Throughput
• Navigation
• Remotely operated vehicles
• Mobile robots
• Robotics and automation
• Uniform resource locators
• Terrain mapping
• Land vehicles
• Solid modeling
• Vehicle safety
• Mobility Scenarios
• Terrain Map
• Field Of View
• Values In The Range
• Image Pixels
• Variation In Density
• Regional Data
• Image Plane
• Autonomous Vehicles
• Maximum Range
• Ground Plane
• Selection Problem
• Angular Position
• Stereopsis
• Direction Of Travel
• Vehicle Motion
• Laser Ranging
• Terrain Slope
• Projective Transformation
• Rough Terrain
• Vertical Field Of View
• Small Incidence Angles
• Vehicle Position
• Minimum Range
• Image Space
• Minimum Throughput
• Range Resolution
• Angular Resolution
• Disparity Range