Authors

    Presenter(s)

    Mukilan Ashokraj Rajapriya

    Comments

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

    Files

    Download

    Download Project (1.5 MB)

    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

    Share

    COinS