Presenter(s)

Mukilan Ashokraj Rajapriya

Comments

Presentation: 1:15-2:30 p.m., Kennedy Union Ballroom

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Description

This project presents an algorithm for a Multi-Robot Visibility-Based Pursuit-Evasion problem in a 2-Dimensional polygonal environment where a team of pursuers attempts to locate an unknown number of evaders given that the pursuers have access to a probabilistic model which describes how the evaders are likely to move in the environment. We present an algorithm to compute a joint plan for pursuers that considers two criterion; the expected time to capture the evaders, and the guaranteed (maximal) time to capture all of the evaders. The desired outcome of our algorithm is a plan for the pursuers that returns a relatively low expected time to capture without drastically increasing the guaranteed time to capture. Intuitively, this can be viewed as a “re-routing” of the pursuers in order to locate more evaders, sooner, than a naive uninformed search. The algorithm proceeds in two phases that we term an “exploitation” phase and an “exploration” phase. We beginthe exploitation phase by first drawing a collection of representative samples from the probabilistic model describing potential evader behavior. We then compute a joint plan for the pursuers that captures all of these sampled evader trajectories. We then proceed tothe exploration phase which provides a complete solution by appending additional pursuer motions to the plan computed during the exploit phase. The resulting strategy ensures that all evaders are located, regardless of whether they follow the probabilistic model or not. Weplan to evaluate our algorithm in simulation to demonstrate the efficacy of the proposed approach.

Publication Date

4-19-2023

Project Designation

Graduate Research

Primary Advisor

Nick Stiffler

Primary Advisor's Department

Computer Science

Keywords

Stander Symposium, College of Arts and Sciences

Institutional Learning Goals

Scholarship

Multi-Robot Visibility-Based Pursuit-Evasion with Probabilistic Evader Models

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