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Case-Based Path Planning for Autonomous Underwater Vehicles

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Underwater Robots

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.

This work was supported in part by National Science Foundation Grant No. BCS-9017990.

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© 1996 Kluwer Academic Publishers

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Vasudevan, C., Ganesan, K. (1996). Case-Based Path Planning for Autonomous Underwater Vehicles. In: Yuh, J., Ura, T., Bekey, G.A. (eds) Underwater Robots. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1419-6_1

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  • DOI: https://doi.org/10.1007/978-1-4613-1419-6_1

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4612-8616-5

  • Online ISBN: 978-1-4613-1419-6

  • eBook Packages: Springer Book Archive

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