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Title: A Game Benchmark for Real-Time Human-Swarm Control
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.  more » « less
Award ID(s):
1837515
PAR ID:
10471791
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
IEEE
Date Published:
Journal Name:
IEEE International Conference on Automation Science and Engineering CASE
ISSN:
2161-8070
ISBN:
978-1-6654-9042-9
Page Range / eLocation ID:
743 to 750
Format(s):
Medium: X
Location:
Mexico City, Mexico
Sponsoring Org:
National Science Foundation
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