Intelligent Mobility Algorithm Research: Dependencies on Autonomous Systems

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Authors
  1. Beckman, B.
  2. Trentini, M.
  3. Brosinsky, C.
  4. Penzes, S.
Corporate Authors
Defence R&D Canada - Suffield, Ralston ALTA (CAN)
Abstract
The mission of the Autonomous Intelligent Systems Section at Defence R&D Canada – Suffield is to augment soldier and combat systems by developing and demonstrating practical, cost-effective autonomous intelligent systems capable of completing military missions in complex operating environments. Fulfilling this mission, in part, is current intelligent mobility research aimed at control algorithms that exploit an Unmanned Ground Vehicle’s (UGV’s) inherent dexterity and available world representation information to produce intelligent locomotion in complex urban terrains. Traditional UGV research has largely been applied to operations in unstructured, obstacle-free outdoor environments. The shift to the complexity of a highly unstructured, obstacle-rich, military urban environment requires dramatically improved mobility characteristics. Intelligent mobility algorithms will exploit learning and control theory to enhance UGV mobility in extremely cluttered environments. This paper defines intelligent mobility research and provides a framework for algorithm development, simulation capabilities and describes the inherent dependencies on other autonomous systems research.

Il y a un résumé en français ici.

Keywords
Autonomous Intelligent Systems;Research and Development;UGV (Unmanned Ground Vehicles)
Report Number
DRDC-SUFFIELD-TM-2005-225 — Technical Memorandum
Date of publication
01 Dec 2005
Number of Pages
22
DSTKIM No
CA026741
CANDIS No
524676
Format(s):
Hardcopy;Document Image stored on Optical Disk

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