Abstract
We describe an approach to the design, analysis, and control of hybrid systems which is data intensive in contrast to more traditional approaches which tend to be compute-intensive. A key idea is to use a low overhead, high performance persistent object manager to trade space for time, even when the amount of data is very large. The main advantage is that near real time solutions to problems can be obtained which would be prohibitive with other approaches. To illustrate the effectiveness of this approach, we show how millions of trajectories segments can be stored and retrieved to solve path planning problems and how hundreds of modes can be stored to aid in the study of mode switching strategies.
This research was supported in part by NASA grant NAG2-513, DOE grant DE-FG02-92ER25133, and NSF grants DMS-9101089, IRI-9224605, CDA-9303433, and CDA-9413948.
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© 1996 Springer-Verlag Berlin Heidelberg
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Bailey, S., Grossman, R.L., Gu, L., Hanley, D. (1996). A data intensive computing approach to path planning and mode management for hybrid systems. In: Alur, R., Henzinger, T.A., Sontag, E.D. (eds) Hybrid Systems III. HS 1995. Lecture Notes in Computer Science, vol 1066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020970
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DOI: https://doi.org/10.1007/BFb0020970
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