Abstract
This paper presents a new approach to shared control. It consists of combining orders from a mobile and a human. The weight of these orders is obtained by evaluating their corresponding efficiencies but also of his/her condition, which is estimated by continuously monitoring attached biosensors. We rely on a hierarchical architecture where the reactive layer provides a simple and adaptive combination of these sources. We have evaluated the resulting emergent behaviour for different tasks to measure their efficiencies under different circumstances. The system has been successfully tested in real environments from a quantitative and a qualitative point of view.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Horiguchi, Y., Sawaragi, T.: Effects of probing to adapt machine autonomy in shared control systems. In: Proc. International Conference on Systems, Man and Cybernetics, vol. 1, Hawaii, USA, October 2005, pp. 317–323 (2005)
Connell, J.H., Viola, P.: Cooperative control of a semi-autonomous mobile robot. In: Proc. of the IEEE Conference on Robotics and Automation, Cincinnati, USA, pp. 1118–1121. IEEE Computer Society Press, Los Alamitos (1990)
Vanhooydonck, D., Demeester, E., Nuttin, M., Brussel, H.V.: Shared control for intelligent wheelchairs: an implicit estimation of the user intention. In: Proc. of the 1st International Workshop on Advances in Service Robotics, Bardolino, Italy, pp. 176–182 (2003)
Katevas, N.L., Sgouros, N.M., Tzafestas, S.G., Papakonstantinou, G., Beattie, P., Bishop, J.M., Tsanakas, P., Koutsouris, D.: The autonomous mobile robot senario: A sensor-aided intelligent navigation system for powered wheelchairs. IEEE Robotics Automation Magazine 4(4), 60–70 (1997)
Parikh, S.P., Grassi, V., Kumar, V., Okamoto, J.: Usability study of a control framework for an intelligent wheelchair. In: Proc. of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain, April 2005, pp. 4745–4750. IEEE Computer Society Press, Los Alamitos (2005)
Urdiales, C., Bandera, A., Pérez, E.J., Poncela, A., Sandoval, F.: Hierarchical planning in a mobile robot for map learning and navigation. In: Autonomous robotic systems: soft computing and hard computing methodologies and applications, pp. 165–188. Physica, Heidelberg (2003)
Arkin, R.C.: Behavior-based robotics. MIT Press, Cambridge (1998)
Hu, H., Brady, M.: A parallel processing architecture for sensor based control of intelligent mobile robots. Robotics and Autonomous Systems 17, 235–257 (1996)
Brooks, R.A.: Intelligence without representation. Artificial Intelligence 47, 139–159 (1991)
Lisetti, C.L.: Using noninvasive wearable computers to recognize human emotions from physiological signals. EURASIP Journal on Applied Signal Processing 11, 1672–1687 (2004)
Luharuka, R., Gao, R.X., Krishnamurty, S.: Design and realization of a portable data logger for physiological sensing. IEEE Transactions on Instrumentation and Measurement 52(4) (2003)
Moravec, H.P.: Sensor fusion in certainty grids for mobile robots. AI Magazine 9, 61–74 (1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fernández-Espejo, B., Poncela, A., Urdiales, C., Sandoval, F. (2007). Collaborative Emergent Navigation Based on Biometric Weighted Shared Control. In: Sandoval, F., Prieto, A., Cabestany, J., Graña, M. (eds) Computational and Ambient Intelligence. IWANN 2007. Lecture Notes in Computer Science, vol 4507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73007-1_98
Download citation
DOI: https://doi.org/10.1007/978-3-540-73007-1_98
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73006-4
Online ISBN: 978-3-540-73007-1
eBook Packages: Computer ScienceComputer Science (R0)