Introduction
So far, we have seen how to augment the maps representing environments with semantic information. This additional information was obtained by classifying the laser range data obtained by a mobile robot into some of the classes that represent the different places in the environment.
This chapter deals with semantic information from a different point of view. Instead of classifying the pose of the robot according to the corresponding laser range observation, we classify the observation itself by assigning a semantic label to each of its measurements. The main idea is to classify each laser beam into the class of the entity it hits. In this way, the data provided by the range sensor contains additional semantic information about the environment.
This chapter originated from a collaboration with Kai O. Arras.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Cui, J., Zha, H., Zhao, H., Shibasaki, R.: Tracking multiple people using laser and vision. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Alberta, Canada (2005)
Fod, A., Howard, A., Mataric, M.J.: Laser-based people tracking. In: Proceedings of the IEEE International Conference on Robotics and Automation (2002)
Hähnel, D., Triebel, R., Burgard, W., Thrun, S.: Map building with mobile robots in dynamic environments. In: Proceedings of the IEEE International Conference on Robotics and Automation (2003)
Kleinhagenbrock, M., Lang, S., Fritsch, J., Lömker, F., Fink, G.A., Sagerer, G.: Person tracking with a mobile robot based on multi-modal anchoring. In: Proceedings of the IEEE International Workshop on Robot and Human Interactive Communication, Berlin, Germany (2002)
Premebida, C., Monteiro, G., Nunes, U., Peixoto, P.: Lidar and vision-based approach for pedestrian and vehicle detection and tracking. In: Proceedings of the IEEE Intelligent Transportation Systems Conference, Seattle,Washington, USA, pp. 1044–1049 (2007)
Scheutz, M., McRaven, J., Cserey, G.: Fast, reliable, adaptive, bimodal people tracking for indoor environments. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Sendai, Japan (2004)
Schulz, D., Burgard, W., Fox, D., Cremers, A.B.: People tracking with a mobile robot using sample-based joint probabilistic data association filters. International Journal of Robotics Research 22(2), 99–116 (2003)
Topp, E.A., Christensen, H.I.: Tracking for following and passing persons. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Alberta, Canada (2005)
Xavier, J., Pacheco, M., Castro, D., Ruano, A., Nunes, U.: Fast line, arc/circle and leg detection from laser scan data in a player driver. In: Proceedings of the IEEE International Conference on Robotics and Automation (2005)
Zivkovic, Z., Kröse, B.: Part based people detection using 2D range data and images. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA, USA, pp. 214–219 (2007)
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Mozos, Ó.M. (2010). Semantic Information in Sensor Data. In: Semantic Labeling of Places with Mobile Robots. Springer Tracts in Advanced Robotics, vol 61. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11210-2_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-11210-2_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11209-6
Online ISBN: 978-3-642-11210-2
eBook Packages: EngineeringEngineering (R0)