Linear Search for Capturing an Oblivious Mobile Target in the Sender/Receiver Model

TL;DR

This paper investigates linear search algorithms for capturing an oblivious, moving target using two autonomous robots with asymmetric communication abilities, analyzing how communication modes influence search efficiency in different movement scenarios.

Contribution

It introduces new linear search algorithms tailored for robots with face-to-face and wireless communication, analyzing their competitive ratios across various knowledge scenarios.

Findings

New algorithms with analyzed competitive ratios for different models

Asymmetric communication impacts search efficiency

Optimal strategies depend on known target speed and initial distance

Abstract

We consider linear search for capturing an oblivious moving target by two autonomous robots with different communicating abilities. Both robots can communicate Face-to-Face (F2F) when co-located but in addition one robot is a Sender (can also send messages wirelessly) and the other also a Receiver (can also receive messages wirelessly). This is known as Sender/Receiver (S/R, for short) communication model. The robots can move with max speed $1$. The moving target starts at distance $d$ from the origin and can move either with speed $v<1$ away from the origin in the ``away'' model or with speed $v \geq 0$ toward the origin in the ``toward'' model. We assume that the direction of motion of the target (i.e., whether it is the away or toward model) is known to the robots in advance. To capture the target the two robots must be co-located with it. We design new linear search algorithms and analyze the competitive ratio of the time required to capture the target. The approach takes into account various scenarios related to what the robots know about the search environment (e.g., starting distance or speed of the mobile, away or toward model, or a combination thereof). Our study contributes to understanding how asymmetric communication affects the competitive ratio of linear search.