A novel method of sensing and classifying terrain for autonomous unmanned ground vehicles
A novel method of sensing and classifying terrain for autonomous unmanned ground vehicles
Unmanned Ground Vehicles (UGVs) play a vital role in preserving human life during hostile military operations and extend our reach by exploring extraterrestrial worlds during space missions. These systems generally have to operate in unstructured environments which contain dynamic variables and unpredictable obstacles, making the seemingly simple task of traversing from A-B extremely difficult. Terrain is one of the biggest obstacles within these environments as it could potentially cause a vehicle to become stuck and render it useless, therefore autonomous systems must possess the ability to directly sense terrain conditions. Current autonomous vehicles use look-ahead vision systems and passive laser scanners to navigate a safe path around obstacles; however these methods lack detail when considering terrain as they make predictions using estimations of the terrain’s appearance alone. This study establishes a more accurate method of measuring, classifying and monitoring terrain in real-time. A novel instrument for measuring direct terrain features at the wheel-terrain contact interface is presented in the form of the Force Sensing Wheel (FSW). Additionally a classification method using unique parameters of the wheel-terrain interaction is used to identify and monitor terrain conditions in real-time. The combination of both the FSW and real-time classification method facilitates better traversal decisions, creating a more Terrain Capable system.
Vehicle, Trafficability, Terrain, Sensors
Middlesex University London
Prior, Stephen
9c753e49-092a-4dc5-b4cd-6d5ff77e9ced
27 March 2015
Prior, Stephen
9c753e49-092a-4dc5-b4cd-6d5ff77e9ced
Prior, Stephen
9c753e49-092a-4dc5-b4cd-6d5ff77e9ced
Prior, Stephen
(2015)
A novel method of sensing and classifying terrain for autonomous unmanned ground vehicles.
Middlesex University, Doctoral Thesis, 141pp.
Record type:
Thesis
(Doctoral)
Abstract
Unmanned Ground Vehicles (UGVs) play a vital role in preserving human life during hostile military operations and extend our reach by exploring extraterrestrial worlds during space missions. These systems generally have to operate in unstructured environments which contain dynamic variables and unpredictable obstacles, making the seemingly simple task of traversing from A-B extremely difficult. Terrain is one of the biggest obstacles within these environments as it could potentially cause a vehicle to become stuck and render it useless, therefore autonomous systems must possess the ability to directly sense terrain conditions. Current autonomous vehicles use look-ahead vision systems and passive laser scanners to navigate a safe path around obstacles; however these methods lack detail when considering terrain as they make predictions using estimations of the terrain’s appearance alone. This study establishes a more accurate method of measuring, classifying and monitoring terrain in real-time. A novel instrument for measuring direct terrain features at the wheel-terrain contact interface is presented in the form of the Force Sensing Wheel (FSW). Additionally a classification method using unique parameters of the wheel-terrain interaction is used to identify and monitor terrain conditions in real-time. The combination of both the FSW and real-time classification method facilitates better traversal decisions, creating a more Terrain Capable system.
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More information
Published date: 27 March 2015
Additional Information:
PhD student that remained at Middlesex University when I moved to UoS in Oct 2012.
Keywords:
Vehicle, Trafficability, Terrain, Sensors
Identifiers
Local EPrints ID: 492798
URI: http://eprints.soton.ac.uk/id/eprint/492798
PURE UUID: 0d5c7fe1-c9be-44d5-9e45-ae3793928b80
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Date deposited: 14 Aug 2024 16:45
Last modified: 15 Aug 2024 01:44
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