Title:
Rule-based reasoning and neural network perception for safe off-road robot mobility

dc.contributor.author Tunstel, Edward en_US
dc.contributor.author Howard, Ayanna M. en_US
dc.contributor.author Seraji, Homayoun en_US
dc.contributor.corporatename Jet Propulsion Laboratory (U.S.). Robotic Vehicles Group en_US
dc.contributor.corporatename Jet Propulsion Laboratory (U.S.). Telerobotics Research and Applications Group en_US
dc.contributor.corporatename Georgia Institute of Technology. Center for Robotics and Intelligent Machines en_US
dc.date.accessioned 2011-04-19T20:21:04Z
dc.date.available 2011-04-19T20:21:04Z
dc.date.issued 2002-09
dc.description © 2002 Blackwell. The definitive version is available at www3.interscience.wiley.com en_US
dc.description DOI: 10.1111/1468-0394.00204 en_US
dc.description.abstract Operational safety and health monitoring are critical matters for autonomous field mobile robots such as planetary rovers operating on challenging terrain. This paper describes relevant rover safety and health issues and presents an approach to maintaining vehicle safety in a mobility and navigation context. The proposed rover safety module is composed of two distinct components: safe attitude (pitch and roll) management and safe traction management. Fuzzy logic approaches to reasoning about safe attitude and traction management are presented, wherein inertial sensing of safety status and vision-based neural network perception of terrain quality are used to infer safe speeds of traversal. Results of initial field tests and laboratory experiments are also described. The approach provides an intrinsic safety cognizance and a capacity for reactive mitigation of robot mobility and navigation risks. en_US
dc.identifier.citation E. Tunstel, A. Howard, H. Seraji, "Rule-based reasoning and neural network perception for safe off-road robot mobility,” Expert Systems, 19(4), 191-200, Sept. 2002. en_US
dc.identifier.doi 10.1111/1468-0394.00204
dc.identifier.issn 0266-4720
dc.identifier.uri http://hdl.handle.net/1853/38625
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.publisher.original Wiley-Blackwell en_US
dc.subject Safe navigation en_US
dc.subject Planetary rovers en_US
dc.subject Neural networks en_US
dc.subject Fuzzy logic en_US
dc.subject Off-road mobility en_US
dc.title Rule-based reasoning and neural network perception for safe off-road robot mobility en_US
dc.type Text
dc.type.genre Article
dc.type.genre Pre-print
dspace.entity.type Publication
local.contributor.author Howard, Ayanna M.
local.contributor.corporatename School of Civil and Environmental Engineering
local.contributor.corporatename Institute for Robotics and Intelligent Machines (IRIM)
relation.isAuthorOfPublication 6d77e175-105c-4b0b-9548-31f20e60e20a
relation.isOrgUnitOfPublication 88639fad-d3ae-4867-9e7a-7c9e6d2ecc7c
relation.isOrgUnitOfPublication 66259949-abfd-45c2-9dcc-5a6f2c013bcf
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
au_rule_base_reas_10.1.1.7.9768.pdf
Size:
582.54 KB
Format:
Adobe Portable Document Format
Description: