Odor source localization using a mobile robot in outdoor airflow environments with a particle filter algorithm

Abstract

This paper discusses odor source localization (OSL) using a mobile robot in an outdoor time-variant airflow environment. A novel OSL algorithm based on particle filters (PF) is proposed. When the odor plume clue is found, the robot performs an exploratory behavior, such as a plume-tracing strategy, to collect more information about the previously unknown odor source. In parallel, the information collected by the robot is exploited by the PF-based OSL algorithm to estimate the location of the odor source in real time. The process of the OSL is terminated if the estimated source locations converge within a given small area. The Bayesian-inference-based method is also performed for comparison. Experimental results indicate that the proposed PF-based OSL algorithm performs better than the Bayesian-inference-based OSL method.

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, 174-188.
2. Consi, T. R., Atema, J., Goudey, C. A., Cho, J., & Chryssostomidis, C. (1994). AUV guidance with chemical signals. In Proceedings of 1994 symposium on autonomous underwater vehicle technology (pp. 450-455).
3. Farrell, J. A., Pang, S., & Li, W. (2005). Chemical plume tracing via an autonomous underwater vehicle. IEEE Journal of Oceanic Engineering, 30, 428-442.
4. Ferri, G., Caselli, E., Mattoli, V., Mondini, A., Mazzolai, B., & Dario, P. (2009). SPIRAL: a novel biologically-inspired algorithm for gas/odor source localization in an indoor environment with no strong airflow. Robotics and Autonomous Systems, 57, 393-402.
5. Grasso, F. W., Consi, T. R., Mountain, D. C., & Atema, J. (2000). Biomimetic robot lobster performs chemo-orientation in turbulence using a pair of spatially separated sensors: progress and challenges. Robotics and Autonomous Systems, 30(1), 115-131.
6. Hayes, A. T., Martinoli, A., & Goodman, R. M. (2003). Swarm robotic odor localization: off-line optimization and validation with real robots. Robotica, 21, 427-441.
7. Holland, O., & Melhuish, C. (1996). Some adaptive movements of animats with single symmetrical sensors. In Proceedings of 4th conference on simulation and adaptive behavior--from animals to animats (Vol. 4, pp. 55-64).
8. Ishida, H., Suetsugu, K., Nakamoto, T., & Moriizumi, T. (1994). Study of autonomous mobile sensing system for localization of odor source using gas sensors and anemometric sensors. Sensors and Actuators. A, Physical, 45, 153-157.
9. Ishida, H., Nakamoto, T., & Moriizumi, T. (1998). Remote sensing of gas/odor source location and concentration distribution using mobile system. Sensors and Actuators. B, Chemical, 49, 52-57.
10. Kahn, H. (1956). Use of different Monte Carlo sampling techniques. In H. A. Meyer (Ed.), Symposium onMonte Carlo methods (pp. 146- 190). New York: Wiley.
11. Kowadlo, G., & Russell, R. A. (2006). Using naïve physics for odor localization in a cluttered indoor environment. Autonomous Robots, 20(3), 215-230.
12. Kowadlo, G., & Russell, R. A. (2009). Improving the robustness of naïve physics airflow mapping using Bayesian reasoning on a multiple hypothesis tree. Robotics and Autonomous Systems, 57, 723-737.
13. Li, F., Meng, Q. H., Bai, S., Li, J. G., & Popescu, D. (2008). Probability-PSO algorithm for multi-robot based odor source localization in ventilated indoor environments. In Lecture notes in computer science: Vol. 5314. Lecture notes in artificial intelligence and lecture notes in bioinformatics (pp. 1206-1215).
14. Li, J. G., Meng, Q. H., Li, F., Zeng, M., & Popescu, D. (2009). Mobile robot based odor source localization via particle filter. In Proceedings of IEEE international conference on decision and control (pp. 2984-2989).
15. Li, W., Farrell, J. A., Pang, S., & Arrieta, R. M. (2006). Moth-inspired chemical plume tracing on an autonomous underwater vehicle. IEEE Transactions on Robotics, 22, 292-307.
16. Lilienthal, A. J., & Duckett, T. (2004). Building gas concentration gridmaps with a mobile robot. Robotics and Autonomous Systems, 48, 3-16.
17. Lilienthal, A. J., Loutfi, A., & Duckett, T. (2006). Airborne chemical sensing with mobile robots. Sensors, 6, 1616-1678.
18. Marques, L., Nunes, U., & de Almeida, A. T. (2006). Particle swarm-based olfactory guided search. Autonomous Robots, 20(3), 277- 287.
19. Pang, S., & Farrell, J. A. (2006). Chemical plume source localization. IEEE Transactions on Systems, Man and Cybernetics. Part B. Cybernetics, 36, 1068-1080.
20. Russell, R. A., Thiel, D., & Mackay-Sim, A. (1994). Sensing odour trails for mobile robot navigation. In Proceedings of IEEE international conference on robotics and automation (pp. 2672- 2677).
21. Russell, R. A., Thiel, D., Deveza, R., & Mackay-Sim, A. (1995). A robotic system to locate hazardous chemical leaks. In Proceedings of IEEE international conference on robotics and automation (pp. 556-561).
22. Russell, R. A., Bab-Hadiashar, A., Shepherd, R. L., & Wallace, G. G. (2003). A comparison of reactive chemotaxis algorithms. Robotics and Autonomous Systems, 45(2), 83-97.
23. Sandini, G., Lucarini, G., & Varoli, M. (1993). Gradient-driven self-organizing systems. In Proceedings of IEEE/RSJ international conference on intelligent robots systems (pp. 429-432).
24. Vergassola, M., Villermaux, E., & Shraiman, B. I. (2007). 'Infotaxis' as a strategy for searching without gradients. Nature, 445, 406-409.
25. Zarzhitsky, D., Spears, D. F., & Spears, W. M. (2005). Distributed robotics approach to chemical plume tracing. In Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (pp. 4034-4039).