Swarm manipulation: An efficient and accurate technique for multi-object manipulation in virtual reality
Xiang Li, Jin-Du Wang, John J. Dudley, Per Ola Kristensson

TL;DR
This paper presents a novel swarm manipulation technique for multi-object control in virtual reality, demonstrating improved performance and user experience over traditional methods through user studies and analysis.
Contribution
Introduces a new swarm manipulation interaction method for VR, showing its advantages over baseline techniques in efficiency and user experience.
Findings
Swarm Manipulation achieved faster task completion times.
It reduced resizing size deviations.
Trade-offs between speed and accuracy were observed in rotation tasks.
Abstract
The theory of swarm control shows promise for controlling multiple objects, however, scalability is hindered by cost constraints, such as hardware and infrastructure. Virtual Reality (VR) can overcome these limitations, but research on swarm interaction in VR is limited. This paper introduces a novel Swarm Manipulation interaction technique and compares it with two baseline techniques: Virtual Hand and Controller (ray-casting). We evaluated these techniques in a user study ( = 12) in three tasks (selection, rotation, and resizing) across five conditions. Our results indicate that Swarm Manipulation yielded superior performance, with significantly faster speeds in most conditions across the three tasks. It notably reduced resizing size deviations but introduced a trade-off between speed and accuracy in the rotation task. Additionally, we conducted a follow-up user study ( = 6)…
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Taxonomy
TopicsRobotic Path Planning Algorithms · Robotics and Automated Systems · Robot Manipulation and Learning
