A Game Benchmark for Real-Time Human-Swarm Control

TL;DR

This paper introduces a real-time game benchmark for testing human-swarm control algorithms, featuring a high-cadence virtual environment where players manage swarms through touchscreen interfaces, emphasizing rapid decision-making and control strategies.

Contribution

The paper presents a novel game-based benchmark environment for evaluating human-swarm control in high-cadence scenarios, including a default control system and a comparison with flocking control methods.

Findings

The benchmark effectively tests real-time swarm control algorithms.

Touchscreen interface enables intuitive high-level control of swarms.

Comparison highlights traits crucial for effective swarm control in dynamic scenarios.

Abstract

We present a game benchmark for testing human-swarm control algorithms and interfaces in a real-time, high-cadence scenario. Our benchmark consists of a swarm vs. swarm game in a virtual ROS environment in which the goal of the game is to capture all agents from the opposing swarm; the game's high-cadence is a result of the capture rules, which cause agent team sizes to fluctuate rapidly. These rules require players to consider both the number of agents currently at their disposal and the behavior of their opponent's swarm when they plan actions. We demonstrate our game benchmark with a default human-swarm control system that enables a player to interact with their swarm through a high-level touchscreen interface. The touchscreen interface transforms player gestures into swarm control commands via a low-level decentralized ergodic control framework. We compare our default human-swarm control system to a flocking-based control system, and discuss traits that are crucial for swarm control algorithms and interfaces operating in real-time, high-cadence scenarios like our game benchmark. Our game benchmark code is available on Github; more information can be found at https://sites.google.com/view/swarm-game-benchmark.