Autonomous swarms of robots can bring robustness, scalability and adaptability to safety-critical tasks such as search and rescue but their application is still very limited. Using semi-autonomous swarms with human control can bring robot swarms to real-world applications. Human operators can define goals for the swarm, monitor their performance and interfere with, or overrule, the decisions and behaviour. We present the “Human And Robot Interactive Swarm” simulator (HARIS) that allows multi-user interaction with a robot swarm and facilitates qualitative and quantitative user studies through simulation of robot swarms completing tasks, from package delivery to search and rescue, with varying levels of human control. In this demonstration, we showcase the simulator by using it to study the performance gain offered by maintaining a “human-in-the-loop” over a fully autonomous system as an example. This is illustrated in the context of search and rescue, with an autonomous allocation of resources to those in need.
Keywords: Human-Swarm Teaming; Swarm Robotics; Human-robot Interaction; Simulation Environments; HARIS.
ACM Reference Format: William Hunt , Jack Ryan , Ayodeji O. Abioye , Sarvapali D. Ramchurn, and Mohammad D. Soorati .
2023. Demonstrating Performance Benefits of Human-Swarm Teaming: Demonstration Track. In Proc. of the 22nd International
Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023), London, United Kingdom, May 29 – June 2, 2023, IFAAMAS, 3 pages.