Abstract
This paper presents a novel navigation system designed for a brain-controlled wheelchair, which interacts with human user by the low throughput interface. The navigation system proposes the semantic map, which is integrated with the navigation points, semantic targets and local 3D map, to a human user who can choose one of the navigation points as a goal for navigation. The semantic targets provide category, geometry and functionality information of the recognized objects, such as a table which can be docked. The local 3D map provides the navigation points in the traversable areas. The human-wheelchair interactive system shows the semantic map to user, and the user selects the goal via a brain-computer interfaces (BCI). Therefore, this method can help the wheelchair implement accurate navigation (e.g. docking) with a low throughput interface and the safety and comfortability are improved. Our navigation system is successfully tested in real environment.
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References
del Milan, J.R., Carmena, J.: Invasive or Noninvasive: Understanding Brain-Machine Interface Technology. IEEE Engineering in Medicine and Biology Magazine 29, 16–22 (2010)
Wei, Z., Chen, W., Wang, J.: 3D semantic map-based shared control for smart wheelchair. In: Su, C.-Y., Rakheja, S., Liu, H. (eds.) ICIRA 2012, Part II. LNCS, vol. 7507, pp. 41–51. Springer, Heidelberg (2012)
Wei, Z., Chen, W., Wang, J.: Semantic Mapping for Smart Wheelchairs Using RGB-D Camera. Journal of Medical Imaging and Health Informatics 3, 94–100 (2013)
Carlson, T., Monnard, G., del Millán, J.R.: Vision-based shared control for a BCI wheelchair. International Journal of Bioelectromagnetism 13, 20–21 (2011)
Mandel, C., Luth, T., Laue, T., Rofer, T., Graser, A., Krieg-Bruckner, B.: Navigating a smart wheelchair with a brain-computer interface interpreting steady-state visual evoked potentials. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1118–1125. IEEE Press, St. Louis (2009)
Iturrate, I., Antelis, J.M., Kubler, A., Minguez, J.: A noninvasive brain-actuated wheelchair based on a P300 neurophysiological protocol and automated navigation. IEEE Transactions on Robotics 25, 614–627 (2009)
Perrin, X., Chavarriaga, R., Colas, F., Siegwart, R., del Millán, J.R.: Brain-coupled interaction for semi-autonomous navigation of an assistive robot. Robotics and Autonomous Systems 58, 1246–1255 (2010)
Baumeister, J., Barthel, T., Geiss, K., Weiss, M.: Influence of phosphatidylserine on cognitive performance and cortical activity after induced stress. Nutritional Neuroscience 11, 103–112 (2008)
Murphy, K.: Bayesian map learning in dynamic environments. Advances in Neural Information Processing Systems 12, 1015–1021 (1999)
Grisetti, G., Stachniss, C., Burgard, W.: Improved techniques for grid mapping with rao-blackwellized particle filters. IEEE Transactions on Robotics 23, 34–46 (2007)
Thrun, S., Burgard, W., Fox, D.: Probabilistic robotics, vol. 1. The MIT Press, Cambridge (2005)
Siegwart, R., Nourbakhsh, I.R.: Introduction to autonomous mobile robots. The MIT Press, Cambridge (2004)
Parikh, S.P., Grassi Jr, V., Kumar, V., Okamoto Jr, J.: Integrating human inputs with autonomous behaviors on an intelligent wheelchair platform. IEEE intelligent systems 22, 33–41 (2007)
Carlson, T., Demiris, Y.: Human-wheelchair collaboration through prediction of intention and adaptive assistance. In: IEEE International Conference on Robotics and Automation, pp. 3926–3931. IEEE Press, Pasadena (2008)
Robot Operating System (ROS), http://www.ros.org
Rusu, R.B., Cousins, S.: 3D is here: Point Cloud Library (PCL). In: IEEE International Conference on Robotics and Automation, pp. 1–4. IEEE Press, Shanghai (2011)
Niedermeyer, E., da Silva, F.H.L.: Electroencephalography: basic principles, clinical applications, and related fields. Lippincott Williams &Wilkins, Hagerstown (2005)
International 10-20 system, http://en.wikipedia.org/wiki/10-20_system_EEG
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Wei, Z., Chen, W., Wang, J., Wang, H., Li, K. (2013). Semantic Mapping for Safe and Comfortable Navigation of a Brain-Controlled Wheelchair. In: Lee, J., Lee, M.C., Liu, H., Ryu, JH. (eds) Intelligent Robotics and Applications. ICIRA 2013. Lecture Notes in Computer Science(), vol 8102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40852-6_32
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DOI: https://doi.org/10.1007/978-3-642-40852-6_32
Publisher Name: Springer, Berlin, Heidelberg
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