Papers for

vr training developers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Robot helper improves human control of ungovernable swarms in virtual reality

Mediating Human-Swarm Interactions Through a Robot Helper: A Shepherding-Inspired Approach

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.

Mon 2 NovRoboticsHuman-Computer Interaction
The gist
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.
Open → 2611.03548v1

Multiple agents boost user confidence in VR evacuation training

Influence of Agent Number and Behavior on Users' Psychological Responses in VR Evacuation Training

Abstract: This study aims to build effective drill software by combining a virtual simulation of a disaster with multiple agents capable of expressing emotions. We evaluated how the number of agents and their emotional and behavioral actions during evacuation influence users in a virtual space. The results showed that users tended to act more confidently when many agents evacuated with them, and that the evacuation route chosen by the agents influenced the users' decision-making. These findings indicate that users' evacuation behavior is shaped not only by the environment itself but also by the collective behavior of surrounding agents, underscoring the need to consider how agent behavior affects users' psychological states during training.

Wed 28 OctHuman-Computer InteractionMultimediaRobotics
The gist
When people practice escaping dangers in virtual reality, the number and actions of nearby virtual characters affect how they feel and behave. The authors found that users act more confidently when many characters evacuate with them. Also, the paths chosen by these characters influence the users' decisions where to go. This means that in virtual training, not just the environment but how other people act matters a lot.
Open → 2610.38536v1

VR system uses AI to help teach stage lighting more effectively

LumiNote: LLM-Assisted Multimodal Instruction for VR Stage Lighting Education

Abstract: Stage lighting education requires instructors to bridge abstract concepts, technical operations, and learner-understandable representations. While Virtual Reality (VR) removes physical constraints, existing systems provide limited support for live instruction. We present LumiNote, an LLM-assisted VR system that transforms spoken pedagogical intent into instructor-reviewable spatial annotations, executable demonstrations, and linguistic support. In an exploratory study with 3 instructors and 24 students, we examined how instructors incorporated LumiNote into familiar lighting topics and how students received the resulting representations. We found LLM assistance most valuable for expressive, under-specified goals, but requiring greater expert intervention for fixture-specific or spatial configuration requests. Instructors engaged with generated suggestions as a controllable refinement process, shifting effort from manual setup toward pedagogical expression. However, representations that externalized expert reasoning did not always align with novice comprehension. These findings characterize LLM-assisted VR instruction as a domain-grounded mediation process among expert expression, executable operations, and learner-facing representations.

Tue 15 SeptHuman-Computer Interaction
The gist
Teaching stage lighting is hard because it involves abstract ideas and complicated equipment. The authors created LumiNote, a virtual reality tool that uses an AI language model to turn an instructor’s spoken instructions into clear visual notes, demonstrations, and explanations inside VR. They found it helped instructors explain hard-to-describe concepts, but experts still needed to guide the system for detailed equipment or positioning. The tool shifted teachers’ effort from setup to teaching, although some explanations were tricky for beginners to understand.
Open → 2609.17335v1