Sensor fusion by pseudo information measure: A mobile robot application

ISA Transactions

Volumn 41, Issue 3, 2002, Pages 283-301

  Asharif, Mohammad Reza ^a,b   Moshiri, Behzad ^a   HoseinNezhad, Reza ^a  

^a UNIVERSITY OF TEHRAN   (Iran)

^b UNIVERSITY OF THE RYUKYUS   (Japan)

Author keywords

Bayesian theory; Occupancy grids; Path planning; Pseudo information measure; Sensor data fusion

Indexed keywords

COMPUTER SIMULATION; MOTION PLANNING; PROBABILITY; ROBOT APPLICATIONS; SENSORS;

BAYESIAN THEORY;

SENSOR DATA FUSION;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYES THEOREM; COMPARATIVE STUDY; COMPUTER SIMULATION; FEEDBACK SYSTEM; FUZZY LOGIC; INSTRUMENTATION; METHODOLOGY; MOTION; ROBOTICS; STATISTICAL MODEL; TRANSDUCER;

ALGORITHMS; BAYES THEOREM; COMPUTER SIMULATION; FEEDBACK; FUZZY LOGIC; MODELS, STATISTICAL; MOTION; NEURAL NETWORKS (COMPUTER); ROBOTICS; TRANSDUCERS;

EID: 0036636153     PISSN: 00190578     EISSN: None     Source Type: Journal    
DOI: 10.1016/s0019-0578(07)60088-3     Document Type: Article

References (21)

1. Abidi, A. and Gonzalez, R. C., Data Fusion in Robotic and Machine Intelligence. Academic Press, New York, 1992.
2. Elfes, A., Using occupancy grids for mobile robot perception and navigation. Computer 22, 249-265 (1989).
3. Elfes, A., Sonar-based real-world mapping and navigation. IEEE J. Rob. Autom. 3, 249-265 (1987).
4. Van Dam, J. W. M., Krose, B. J. A., and Groen, F. C. A., Neural network Applications in Sensor Fusion for An Autonomous Mobile Robot, University of Amsterdam, Technical Report, 1998.
5. Van Dam, J. W. M., Environment modeling for mobile robot: Neural learning for sensor fusion, Ph.D. thesis, University of Amsterdam, 1998.
6. Thrun, S., Probabilistic algorithms in robotics. AI Mag. 21, 93-109 (2000).
7. Thrun, S., Learning metric-topological maps for indoor mobile robot navigation. Artif. Intel. 99, 22-71 (1998).
8. Thrun, S., Bayesian landmark learning for mobile robot localization. Mach. Learn. 33, 41-76 (1998).
9. Thrun, S., A probabilistic online mapping algorithm for teams of robots. Int. J. Robot. Res. 20, 335-363 (2001).
10. Asharif, M. R., Moshiri, B., and HoseinNezhad, R., Pseudo information measure: A new concept for sensor data fusion, applied in map building for mobile robots, in: Proc. of International Conference of Signal Processing Applications and Technology (ICSPAT), Dallas, Texas, October 2000, http:// www.dspworld.com/icspat/robotics.htm
11. Asharif, M. R., Moshiri, B., and HoseinNezhad, R., Environment mapping for Khepera robot: A new method by fusion of pseudo information measures, in: Proc. of International Symposium on Artificial Life and Robotics (AROB), Tokyo, Japan, January 2001, 305-308.
12. Oriolo, G., Ulivi, G., and Vendittelli, M., Fuzzy maps: A new tool for mobile robot perception and planning. J. Rob. Syst. 14, 179-197 (1997).
13. Oriolo, G., Ulivi, G., and Vendittelli, M., On-line map building and navigation for autonomous mobile robots, in: Proc. of IEEE International Conference on Robotics and Automation, Nagoya, Japan, 1995, pp. 2900-2906.
14. Oriolo, G., Ulivi, G., and Vendittelli, M., Potential-based motion planning on fuzzy maps, in: Proc. of European Conference on Intelligent Techniques and Soft Computing (EUFIT94), Aachen, 1994, pp. 731-735.
15. Poloni, M., Ulivi, G., and Vendittelli, M., Fuzzy logic and autonomous vehicles: Experiments in ultrasonic vision. Fuzzy Sets Syst. 69, 15-27 (1995).
16. Polaroid Corporation, Ultrasonic Rangin System, 1987.
17. Moshiri, B., Eydgahi, A., Najafi, M., and Hosein-Nezhad, R., Multi-sensor data fusion used in intelligent autonomous navigation, in: Proc. of IASTEDCA'99 (Control Systems and Applications), Banff, Canada, July 1999, 515-520.
18. Warren, C. W., Fast path planning using modified A* method, in: Proc. of IEEE International Conference on Robotics and Automation, Atlanta, Georgia, 1993, pp. 662-667.
19. S. A., K-Team, Khepera User Manual (5.0 ed.), Lausanne, Switzerland, 1998, http://www.k-team.com/download/khepera/documentation/KheperaUserManual.pdf
20. Brailenberg, V., Vehicles. MIT Press, Cambridge, MA, 1984.
21. Moshiri, B., Asharif, M. R., and HoseinNezhad, R., Improved on-line pose estimation for mobile robots by fusion of odometry information and environment map, in: Proc. of the Fourth International Conference on Information Fusion, FUSION 2001, Montreal, Canada, 7-10 August 2001, TuB1.11-TuB1.18.