Access the full text.
Sign up today, get DeepDyve free for 14 days.
Edward Tunstel (1995)
Coordination of distributed fuzzy behaviors in mobile robot control1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century, 5
H. Seraji (2003)
New traversability indices and traversability grid for integrated sensor/map-based navigationJournal of Robotic Systems, 20
L. Ojeda, G. Reina, J. Borenstein (2004)
Experimental results from FLEXnav: an expert rule-based dead-reckoning system for Mars rovers2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720), 2
H. Seraji, A. Howard (2002)
Behavior-based robot navigation on challenging terrain: A fuzzy logic approachIEEE Trans. Robotics Autom., 18
H. Seraji (2005)
SmartNav: A rule-free fuzzy approach to rover navigationJ. Field Robotics, 22
A. Howard, H. Seraji (2001)
Vision-based terrain characterization and traversability assessmentJ. Field Robotics, 18
Sanjiv Singh, R. Simmons, Trey Smith, A. Stentz, V. Verma, Alex Yahja, K. Schwehr (2000)
Recent progress in local and global traversability for planetary roversProceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065), 2
H. Seraji (2005)
SmartNav: A rule-free fuzzy approach to rover navigation: Research ArticlesJournal of Robotic Systems, 22
H. Seraji (2003)
New Traversability Indices and Traversability Grid for Integrated Sensor/Map-Based NavigationJ. Field Robotics, 20
Mustafa Güven, K. Passino (2001)
Avoiding exponential parameter growth in fuzzy systemsIEEE Trans. Fuzzy Syst., 9
H. Seraji (1999)
Traversability index: a new concept for planetary roversProceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C), 3
S. Goldberg, M. Maimone, L. Matthies (2002)
Stereo vision and rover navigation software for planetary explorationProceedings, IEEE Aerospace Conference, 5
A. Saffiotti (1997)
The uses of fuzzy logic in autonomous robot navigationSoft Computing, 1
H. Hagras, M. Colley, V. Callaghan, M. Carr-West (2002)
Online Learning and Adaptation of Autonomous Mobile Robots for Sustainable AgricultureAutonomous Robots, 13
A. Martin-Alvarez, R. Volpe, S. Hayati, R. Petras (1999)
Fuzzy reactive piloting for continuous driving of long range autonomous planetary micro-rovers1999 IEEE Aerospace Conference. Proceedings (Cat. No.99TH8403), 2
A. Shirkhodaie, R. Amrani, E. Tunstel (2004)
Visual terrain mapping for traversable path planning of mobile robots, 5608
B. Werger (2000)
Ayllu: Distributed Port-Arbitrated Behavior-Based Control
C. Ye, J. Borenstein (2004)
T-transformation: traversability analysis for navigation on rugged terrain, 5422
A. Howard, H. Seraji (2001)
An intelligent terrain-based navigation system for planetary roversIEEE Robotics & Automation Magazine, 8
H. Seraji (2000)
Fuzzy traversability index: A new concept for terrain‐based navigationJournal of Robotic Systems, 17
N. Pfluger, J. Yen, R. Langari (1992)
A defuzzification strategy for a fuzzy logic controller employing prohibitive information in command formulation[1992 Proceedings] IEEE International Conference on Fuzzy Systems
S. Lacroix, R. Chatila, S. Fleury, M. Herrb, T. Siméon (1994)
Autonomous navigation in outdoor environment: adaptive approach and experimentProceedings of the 1994 IEEE International Conference on Robotics and Automation
H. Seraji (2005)
SmartNav: A rule-free fuzzy approach to rover navigationJournal of Robotic Systems, 22
R. Simmons, E. Krotkov, L. Chrisman, Fabio Cozman, R. Goodwin, M. Hebert, Lalitesh Katragadda, Sven Koenig, G. Krishnaswamy, Y. Shinoda, W. Whittaker, P. Klarer (1995)
Experience with rover navigation for lunar-like terrainsProceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots, 1
D. Gennery (1999)
Traversability Analysis and Path Planning for a Planetary RoverAutonomous Robots, 6
D. Langer, J. Rosenblatt, M. Hebert (1994)
A behavior-based system for off-road navigationIEEE Trans. Robotics Autom., 10
This paper describes theoretical and experimental results using the SmartNav rule-free fuzzy rover navigation system. SmartNav divides the terrain perceived by the rover into a number of circular sectors, and evaluates each sector using goal and safety preference factors to differentiate between preferred and unpreferred terrain sectors. The goal-preference factor is used to make sector evaluation based on the sector orientation relative to the designated goal position. The safety-preference factors are used to make sector evaluations on the basis of the sector local and regional terrain hazards. Three methods are developed to blend the three sector evaluations in order to find the effective preference factor for each sector. Two sector selection methods are then described in which the sector preference factors are used to find the heading command for the rover. The rover speed command is also computed based on the goal distance and safety-preference factor of the chosen sector. The above navigation steps are continuously repeated throughout the rover motion. Experimental results are presented to demonstrate the navigational capabilities of SmartNav using a commercial Pioneer 2AT rover traversing a simulated Martian terrain at the JPL Mini Mars Yard.
Autonomous Robots – Springer Journals
Published: Nov 23, 2006
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.