Constrained Probabilistic Search for a One-Dimensional Random Walker

• Published in: IEEE transactions on robotics Vol. 32; no. 2; pp. 261 - 274
• Main Authors: Noori, Narges, Renzaglia, Alessandro, Hook, Joshua Vander, Isler, Volkan
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Design analysis; Games; Image edge detection; Land; Legged locomotion; Markov analysis; Markov models; Mathematical models; Networked robots; Optimization; Probabilistic logic; Probability distribution; Random walk theory; Search problems; Searching; sensor networks; Strategy; surveillance systems; Target detection; Time factors; Networked robots; sensor networks; surveillance systems
• ISSN: 1552-3098; 1941-0468
• DOI: 10.1109/TRO.2015.2513751

This paper addresses a fundamental search problem in which a searcher subject to time and energy constraints tries to find a mobile target. The target's motion is modeled as a random walk on a discrete set of points on a line segment. At each time step, the target chooses one of the adjacent nodes at random and moves there. We study two detection models. In the no-crossing model, the searcher detects the target if it is on the same node or if it takes the same edge at the same time. In the crossing model, detection happens only if the target lands on the same node at the same time. For the no-crossing model, where move and stay actions may have different costs, we present an optimal search strategy under energy and time constraints. For the crossing model, we formulate the problem of designing an optimal strategy as a partially observable Markov decision process (POMDP) and solve it using methods that reduce the state-space representation of the belief. The POMDP solution reveals structural properties of the optimal solution. We use this structure to design an efficient strategy and analytically study its performance. Finally, we present preliminary experimental results to demonstrate the applicability of our model to our tracking system, which is used for finding radio-tagged invasive fish.