Using Temporal Consistency to Improve Robot Localisation
Symbolic reasoning has rarely been applied to filter sensor information; and for data fusion, probabilistic models are favoured over reasoning with logic models. However, we show that in the fast dynamic environment of robotic soccer, Plausible Logic can be used effectively to deploy non-monotonic reasoning. We show this is also possible within the frame rate of vision in the (not so powerful) hardware of the AIBO ERS-7 used in the legged league. The non-monotonic reasoning with Plausible Logic not only has algorithmic completion guarantees but we show that it effectively filters the visual input for improved robot localisation. Moreover, we show that reasoning using Plausible Logic is not restricted to the traditional value domain of discerning about objects in one frame. We present a model to draw conclusions over consecutive frames and illustrate that adding temporal rules can further enhance the reliability of localisation.
KeywordsCurrent Frame Previous Frame Temporal Consistency Nonmonotonic Reasoning Nonmonotonic Logic
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- 4.Brooks, R.A.: Intelligence without reason. In: ICJAI 1991. 12th Int Joint Conf on Artificial Intelligence, San Mateo, CA, pp. 569–595. Morgan Kaufmann, San Francisco (1991)Google Scholar
- 5.Compton, P., et al.: Ripple down rules: possibilities and limitations. In: 6th Banf AAAI Knowledge Acquisiiton for Knowledge Based Systems Workshop (1991)Google Scholar
- 7.Gutmann, J.-S., Fox, D.: An experimental comparison of localization methods continued. In: IEEE/RSJ Int. Conf. Intelligent Robots and Systems, Lausanne (2002)Google Scholar
- 8.Haemmi, R., Hartmann, S.: Modeling partially reliable information sources: A general approach based on Dempster-Shafer theory. Information Fusion (forthcoming)Google Scholar
- 10.Billington, D., Estivill-Castro, V., Hexel, R., Rock, A.: Non-monotonic Reasoning for Localisation in RoboCup. In: Sammut, C. (ed.) Australasian Conf. on Robotics and Automation. UNSW, Sydney (2005) CD-ROMGoogle Scholar
- 11.Rich, E., Knight, K.: Artificial Intelligence, 2nd edn. McGraw-Hill, New York (1991)Google Scholar
- 12.Rock, A., Billington, D.: An implementation of propositional plausible logic. In: Edwards, J. (ed.) 23rd Australasian Computer Science Conf. Australian Computer Science Comms, pp. 204–210. IEEE Computer Society, Los Alamitos (2000)Google Scholar
- 13.Röfer, T., Jüngel, M.: Fast and robust edge-based localization in the SONY four-legged robot league. In: Polani, D., Browning, B., Bonarini, A., Yoshida, K. (eds.) RoboCup 2003. LNCS (LNAI), vol. 3020, Springer, Heidelberg (2004)Google Scholar
- 14.Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach, 2nd edn. Prentice-Hall, Englewood Cliffs, NJ (2002)Google Scholar
- 16.Wooldridge, M.: An Introduction to MultiAgent Systems. Wiley, New York (2002)Google Scholar