Stochastic Language-based Motion Control
MARYLAND UNIV COLLEGE PARK DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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In this work we present an efficient environment representation based on the use of landmarks and language based motion programs. The approach is targeted towards applications involving expansive, imprecisely known terrain without a single global map. To handle the uncertainty inherent in real-world applications a partially-observed controlled Markov chain structure is used in which the state space is the set of landmarks and the control space is a set of motion programs. Using dynamic programming, we derive an optimal controller to maximize the probability of arriving at a desired landmark after a finite number of steps. A simple simulation is presented to illustrate the approach.
- Operations Research