Robot Navigation using Velocity Potential Fields and Particle Filters for Obstacle Avoidance

Dan-Sorin Necsulescu, Jin Bai, Jurek Sasiadek

Abstract

Autonomous robots are required to avoid the obstacles during navigation. For this purpose unknown and unexpected obstacles have to be detected during motion. The proposed approach uses particle filters to process sensors data and estimate relative position of the robot with regard to the obstacles and to the goal. These relative position estimations are inputs to the velocity potential field approach for obtaining time varying velocity commands for the robot to avoid all obstacles and reach the goal.

References

  1. Arulampalam, M. S., Maskell, S., Gordon, N. & Clapp, T., 2002. A tutorial on particle filters for online nonlinear/non-gaussian Bayesian tracking, IEEE Transactions on Signal Processing, 50(2), pp.174-188.
  2. Dissanayake, G., Newman, P., Clark, S., Durrant-Whyte, H. F., Csorba, M. 2001. A solution to the simultaneous. localization and map building (SLAM) problem. IEEE. Transactions of Robotics and Automation. Vol 17 , Issue 3, pp. 229 - 241.
  3. Doucet, A., de Freitas, N., Gordon, N., 2001. An. Introduction to Sequential Monte Carlo Methods, Sequential Monte Carlo Methods in Practice, pp 3-14.
  4. Faisal, M., Hedjar, R., Sulaiman, M. A., Al-Mutib, K., 2013. Fuzzy Logic Navigation and Obstacle Avoidance by a Mobile Robot in an Unknown Dynamic Environment, International Journal of Advanced Robotic Systems, Vol. 10, pp.1-7.
  5. Masoud, A., 2007, “Decentralized self-organizing potential field-based control for individually motivated mobile agents in a cluttered environment: A vectorharmonic potential field”. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 37(3), pp. 372-390.
  6. Montemerlo, M., Thrun, M. Koller, D. and Wegbreit, B. 2001. “FastSLAM: A Factored Solution to the. Simultaneous Localization and Mapping Problem” AAAI Proceedings. pp. 593-598.
  7. Necsulescu, D., G. Nie, 2014, Quasi-harmonic Approach. to Non- holonomic Robot Motion Control with. Concave Obstacles Avoidance, 2014CCDC Conf., Changsa, China, May 31 - June 2.
  8. Nie, G, 2014. Quasi-Harmonic Function Approach to Human-Following Robots, M. S. thesis, Dept. of Mechanical Engineering, Univ. Ottawa, Ottawa, ON.
  9. Rekleitis, I. M., 2004, A Particle Filter Tutorial for Mobile Robot Localization, Center for Intelligent Machines, McGill University, Report TR-CIM-04-02.
  10. Simon, D., 2006. Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches, Hoboken, N. J. Wiley-Interscience.
  11. Wang, D., 2009. A Generic Force Field Method for Robot. Real-time Motion Planning and Coordination. PhD dissertation, University of Technology, Sydney, Australia.
  12. Svensson, A., 2014, An introduction to particle filters, Department of Information Technology, Uppsala University, Uppsala, Sweden.
Download


Paper Citation


in Harvard Style

Necsulescu D., Bai J. and Sasiadek J. (2015). Robot Navigation using Velocity Potential Fields and Particle Filters for Obstacle Avoidance . In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-122-9, pages 43-48. DOI: 10.5220/0005501400430048


in Bibtex Style

@conference{icinco15,
author={Dan-Sorin Necsulescu and Jin Bai and Jurek Sasiadek},
title={Robot Navigation using Velocity Potential Fields and Particle Filters for Obstacle Avoidance},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2015},
pages={43-48},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005501400430048},
isbn={978-989-758-122-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Robot Navigation using Velocity Potential Fields and Particle Filters for Obstacle Avoidance
SN - 978-989-758-122-9
AU - Necsulescu D.
AU - Bai J.
AU - Sasiadek J.
PY - 2015
SP - 43
EP - 48
DO - 10.5220/0005501400430048