Defending a Perimeter from a Ground Intruder Using an Aerial Defender: Theory and Practice
Not on the map. Why?
Abstract (arXiv)
The perimeter defense game has received interest in recent years as a variant of the pursuit-evasion game. A number of previous works have solved this game to obtain the optimal strategies for defender and intruder, but the derived theory considers the players as point particles with first-order assumptions. In this work, we aim to apply the theory derived from the perimeter defense problem to robots with realistic models of actuation and sensing and observe performance discrepancy in relaxing the first-order assumptions. In particular, we focus on the hemisphere perimeter defense problem where a ground intruder tries to reach the base of a hemisphere while an aerial defender constrained to move on the hemisphere aims to capture the intruder. The transition from theory to practice is detailed, and the designed system is simulated in Gazebo. Two metrics for parametric analysis and comparative study are proposed to evaluate the performance discrepancy.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Sep 2021.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 2; 2023: 1; 2024: 0; 2025: 1.
4 papers.
- 2023Graph Neural Networks for Decentralized Multi-Agent Perimeter Defensecited by 3
- 2022Vision-based Perimeter Defense via Multiview Pose Estimationcited by 2
- 2022Learning Decentralized Strategies for a Perimeter Defense Game with Graph Neural Networkscited by 2
- 2025Embedded Mean Field Reinforcement Learning for Perimeter-defense Gamecited by 0
- 2025Embedded Mean Field Reinforcement Learning for Perimeter-defense Game20 May 2025
- 2023Graph Neural Networks for Decentralized Multi-Agent Perimeter Defense23 Jan 2023
- 2022Vision-based Perimeter Defense via Multiview Pose Estimation25 Sep 2022
- 2022Learning Decentralized Strategies for a Perimeter Defense Game with Graph Neural Networks24 Sep 2022