Downloads provided by UsageCounts
{"references": ["", "Breitenberg, V.: Vehicles: Experiments in Synthetic Psychology. MIT, Cambridge, MA (1984).", "T. Duckett, U. Nehmzow, Learning to predict sonar readings for mobile robot landmark selection, Internal Report, University of Manchester, Manchester, UK, 1999.", "Fleischer, J., Marsland, S., Shapiro, J., Sensory anticipation for autonomous selection of robot landmarks, M. Butz et al. (Eds.): Anticipatory Behavior ..., LNAI 2684, pp. 201-221, Springer-Verlag 2003.", "Khepera 2, User Manual, K-Team, S.A. 2001, http://ftp.k-team.com/khepera/documentation/Kh2UserManual.pdf", "Marsland, S., Nehmzow, U., and Duckett, T. (2001). Learning to select distinctive landmarks for mobile robot navigation. Robotics and Autonomous Systems, 37:241-260.", "Tani, J.: Model-based learning for mobile robot navigation from the dynamical systems perspective. IEEE Trans. Syst. Man Cybern., Part B, Cybern. 26(3), 421-436 (1996)."]}
This paper presents a predictive model of sensor readings for mobile robot. The model predicts sensor readings for given time horizon based on current sensor readings and velocities of wheels assumed for this horizon. Similar models for such anticipation have been proposed in the literature. The novelty of the model presented in the paper comes from the fact that its structure takes into account physical phenomena and is not just a black box, for example a neural network. From this point of view it may be regarded as a semi-phenomenological model. The model is developed for the Khepera robot, but after certain modifications, it may be applied for any robot with distance sensors such as infrared or ultrasonic sensors.
Mobile robot, anticipation., prediction, sensors
Mobile robot, anticipation., prediction, sensors
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 2 | |
| downloads | 3 |

Views provided by UsageCounts
Downloads provided by UsageCounts