Abstract
Local search has been proposed as a means of responding to changes in problem context requiring replanning. Iterative repair and iterative improvement have desirable properties of preference for plan stability (e.g., non-disruption, minimizing change), and have performed well in a number of practical applications. However, there has been little real empirical evidence to support this case. This paper focuses on the use of local search to support a continuous planning process (e.g., continuously replanning to account for problem changes) as is appropriate for autonomous spacecraft control. We describe results from ongoing empirical tests using the CASPER system to evaluate the effectiveness of local search to replanning using a number of spacecraft scenario simulations including landed operations on a comet and rover operations.
This work was performed by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.
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Chien, S., Knight, R., Rabideau, G. (2001). An Empirical Evaluation of the Effectiveness of Local Search for Replanning. In: Nareyek, A. (eds) Local Search for Planning and Scheduling. LSPS 2000. Lecture Notes in Computer Science(), vol 2148. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45612-0_5
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DOI: https://doi.org/10.1007/3-540-45612-0_5
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