Abstract
Case-based reasoning is reasoning based on specific instances of past experience. A new solution is generated by retrieving and adapting an old one which approximately matches the current situation. In this paper, we outline a case-based reasoning scheme for path planning in autonomous underwater vehicle (AUV) missions. An annotated map database is employed to model the navigational environment. Routes which are used in earlier missions are represented as objects in the map. When a new route is to be planned, the path planner retrieves a matching route from the database and modifies it to suit to the current situation. Whenever a matching route is not available, a new route is synthesized based on past cases that describe similar navigational environments. Case-based approach is thus used not only to adapt old routes but also to synthesize new ones. Since the proposed scheme is centered around reuse of old routes, it would be fast especially when long routes need to be generated. Moreover, better reliability of paths can be expected as they are adapted from earlier missions. The scheme is novel and appropriate for AUV mission scenarios. In this paper, we describe the representation of navigation environment including past routes and objects in the navigational space. Further, we discuss the retrieval and repair strategies and the scheme for synthesizing new routes. Sample results of both synthesis and reuse of routes and system performance analysis are also presented. One major advantage of this system is the facility to enrich the map database with new routes as they are generated.
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Caroll, K.P., McClaran, S.R., Nelson, E.L., Barnett, D.M., Friesen, D.K., and Williams, G.N. 1992. AUV path planning: An A* approach. In Proc. Symposium on AUV Technology (AUV 92), pp. 3–8.
Chappel, S.T. 1987. A blackboard based system for context sensitive mission planning in an autonomous vehicle. In Proc. Fifth International Symposium on Unmanned Untethered Submersible Technology (UUST 89), pp. 467–476.
Chen, P. 1992. Improving path planning with learning. In Proc. of the 9th Int. Conference on Machine Learning, pp. 55–61.
Ganesan, K., Dunn, S.E., Vasudevan, C., and Rae, G.J.S. 1992. Annotated maps for autonomous underwater vehicles. In Proc. 18th Meeting of the US/Japan Marine Facilities Panel of UJNR.
Goel, A.K. and Callentine, T.J. 1992. An experience-based approach to navigational route planning. In Proc. IEEE/RSJ Int. Conference on Intelligent Robots and Systems, pp. 888–893.
Haigh, K. and Veloso, M. 1993. Combining search and analogical reasoning in path planning from road maps. In Proc. of the Workshop on Case-Based Reasoning, Washington D.C., pp. 79–85.
Hammond, K.J. 1989. Proceedings of the DARPA Case-based Reasoning Workshop, Morgan Kaufmann Inc.
Hwang, Y. and Ahuja, N. 1992. Gross motion planning—A survey. ACM Computing Surveys, 24(3):219–292.
Kao, M., Weitzel, G., and Zheng X. 1992. A simple approach to planning and executing complex AUV missions. In Proc. of the Symposium of AUV—AUV-92, pp. 95–102.
Kolodner, J.L. 1988. Proceedings of the DARPA Case-based Reasoning Workshop, Morgan Kaufmann Inc.
Liu, B., Choo, S., Lok, S., Leong, S., Lee, S., Poon, F., and Tan, H. 1994. Integrating case-based reasoning, knowledge-based approach and Dijkstra algorithm for route finding. In Proc. of the IEEE Conference on AI Applications, pp. 149–155.
Pouliot, M. and Smith, J.T. 1992. Integrated mission planning achitectures for unmanned underwater vehicles. In Proc. of the 1992 Symposium on Autonomous Underwater Vehicle Technology, Washington DC., pp. 85–90.
Qiu, Rand Feng, X. 1991. Trajectory planning of underwater vehicle using dynamic CRP model. In Proc. of the 1991 Symposium on AUV Technology, pp. 1082–1086.
Quinn, Andrew. W., and Lane, David M. 1994. Computational issues in motion planning for autonomous underwater vehicles with manipulators. In Proc. of the 1994 Symposium on Autonomous Underwater Vehicle Technology, Cambridge, Massachusetts, pp. 255–262.
Vasudevan, C., Smith, S.M., and Ganesan, K. 1994. Fuzzy logic in case-based reasoning. In Proc. Joint Conference of NAFIPS, IFIS, and NASA on Fuzzy Logic and Neural Networks, pp. 118–128.
Warren, C.W. 1990. A technique for autonomous underwater vehicle route planning. IEEE Journal of Oceanic Engineering, 15(3):199–204.
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This work was supported in part by National Science Foundation Grant No. BCS-9017990.
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Vasudevan, C., Ganesan, K. Case-based path planning for autonomous underwater vehicles. Auton Robot 3, 79–89 (1996). https://doi.org/10.1007/BF00141149
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DOI: https://doi.org/10.1007/BF00141149