Abstract
Sound source localization can be used in the Robocup Rescue Robots League as a sensor that is capable to autonomously detect victims that emit sound. Using differential time of flight measurements through energy cross-spectrum evaluation of the sound signals, the angular direction to multiple sound sources can be determined with a pair of microphones for SNRs better than -8dB. Assuming that the robot pose is known, this information is sufficient to create probabilistic occupancy grid map of the sound sources in the environment and thus localize the victims in a global map. This has been demonstrated using example measurements in an urban search and rescue scenario.
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References
Mattos, L., Grant, E.: Passive Sonar Applications: Target Tracking and Navigation of an Autonomous Robot. In: Proceedings of the IEEE International Conference on Robotics and Automation. IEEE Press, Los Alamitos (2004)
Kitano, H., Tadokoro, S.: Robocup rescue. a grand challenge for multiagent and intelligent systems. AI Magazine 22, 39–52 (2001)
Takahashi, T.: Tadokoro: Working with robots in disasters. IEEE Robotics and Automation Magazine 9, 34–39 (2002)
Osuka, K., Murphy, R., Schultz, A.: Usar competitions for physically situated robots. IEEE Robotics and Automation Magazine 9, 26–33 (2002)
Birk, A., Kenn, H., et al.: The IUB 2002 Smallsize League Team. In: Kaminka, G.A., Lima, P.U., Rojas, R. (eds.) RoboCup 2002. LNCS (LNAI), vol. 2752. Springer, Heidelberg (2003)
Birk, A., Carpin, S., Kenn, H.: The IUB 2003 Rescue Robot Team. In: Polani, D., Browning, B., Bonarini, A., Yoshida, K. (eds.) RoboCup 2003. LNCS (LNAI), vol. 3020. Springer, Heidelberg (2004)
Kenn, H., Carpin, S., et al.: FAST-Robots: a rapid-prototyping framework for intelligent mobile robotics. In: Artificial Intelligence and Applications (AIA 2003). ACTA Press (2003)
Carpin, S., Kenn, H., Birk, A.: Autonomous Mapping in the Real Robots Rescue League. In: Polani, D., Browning, B., Bonarini, A., Yoshida, K. (eds.) RoboCup 2003. LNCS (LNAI), vol. 3020. Springer, Heidelberg (2004)
McLachlan, G., Krishnan, T.: The EM Algorithm and Extensions. Wiley-Interscience, Hoboken (1996)
Kalman, R.: A new approach to linear filtering and prediction problems. Transactions of ASME. Journal of Basic Engineering 83 (1960)
Dissanayake, G., Newman, P., Clark, S., Durrant-Whyte, H., Csorba, M.: A solution to the simultaneous localisation and map building (slam) problem. IEEE Transactions of Robotics and Automation 17, 229–241 (2001)
Moravec, H.P.: Sensor fusion in certainty grids for mobile robots. AI Magazine (1988)
Thrun, S.: Robot mapping: a survey. Technical Report CMU-CS-02-111, Carnegie Mellon University (2002)
Kenn, H., Pfeil, A.: A sound source localization sensor using probabilistic occupancy grid maps. In: Proceedings of the Mechatronics and Robotics Conference 2004. IEEE Press, Los Alamitos (2004)
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Kenn, H., Pfeil, A. (2006). Localizing Victims Through Sound and Probabilistic Grid Maps in an Urban Search and Rescue Scenario. In: Bredenfeld, A., Jacoff, A., Noda, I., Takahashi, Y. (eds) RoboCup 2005: Robot Soccer World Cup IX. RoboCup 2005. Lecture Notes in Computer Science(), vol 4020. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11780519_28
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DOI: https://doi.org/10.1007/11780519_28
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