Robot helper improves human control of ungovernable swarms in virtual reality
Mediating Human-Swarm Interactions Through a Robot Helper: A Shepherding-Inspired Approach
RoboticsHuman-Computer Interaction
Summary
Controlling large groups of animals or robots is hard because you can't direct each member individually. The authors study how a single robot helper can guide these groups by acting like a shepherd. They compare two ways of controlling the helper robot in virtual reality: direct control versus using pre-set movement patterns that affect the group's shape. They found that using these higher-level movement commands made it easier and less tiring for people to steer the group effectively.
What this means in practice
- •For robotics engineers: Develop robotic systems that help humans steer large ungovernable swarms through shape-based motion commands instead of individual control.
- •For vr training developers: Create VR platforms that train users in efficient swarm guidance techniques using intermediate robot helpers and motion primitives.
Authors
Arihant Yadav, Sophie Jörg, Eakta Jain
Abstract
This work investigates human-swarm interaction (HSI) for steering large collectives through an intermediary robot helper. While prior robot-swarm control and HSI techniques commonly assume swarm members are addressable, these assumptions often fail for ``ungovernable'' swarms such as wildlife flocks and schools of fish. Motivated by pastoral shepherding, we compare low-level teleoperation to a higher-autonomy motion-primitives interface in a virtual reality (VR) shepherding task under varied swarm cohesion dynamics. Results indicate that motion primitives that operate on collective shape (e.g., boundary-based control) improve task performance and reduce perceived workload.