Conflict Resolution Strategies for Co-manipulation of Virtual Objects Under Non-disjoint Conditions

Abstract

Virtual Reality (VR) co-manipulation enables multiple users to collaboratively interact with shared virtual objects. However, existing research treats objects as monolithic entities, overlooking scenarios where users need to manipulate different sub-components simultaneously. This work addresses conflict resolution when users select overlapping vertices (non-disjoint sets) during co-manipulation. We present a comprehensive framework comprising preventive strategies (Object-level and Action-level Restrictions) and reactive strategies (computational conflict resolution). Through two user studies with 76 participants (38 pairs), we evaluated these approaches in collaborative wireframe editing tasks. Study 1 identified Averaging as the optimal computational method, balancing task efficiency with user experience. Study 2 highlighted that Action-level Restriction, which permits overlapping selections but restricts concurrent identical operations, achieved better performance compared to exclusive object locking. Reactive strategies using averaging provided smooth collaboration for experienced users, while second-user priority enabled quick corrections. Our findings indicate that optimal strategy selection depends on task requirements, user expertise, and collaboration patterns. Based on the findings, we provide design implications for developing VR collaboration systems that support flexible sub-components manipulation while maintaining collaborative awareness and minimizing conflicts.

Figures (7)

• Figure 1: Overview of conflict resolution strategies for NDS conditions in VR. (a) Object-level Restriction enforces exclusive access control where users can only manipulate their own vertex groups (User 1: red, User 2: blue) with no overlapping selections permitted. (b) Action-level Restriction allows overlapping vertex selections (purple indicates joint vertices) but prevents concurrent identical operations on overlapping points, users must perform different transformation types when manipulating joint vertices. The system applies both operations to the joint vertices simultaneously. (c)Reactive Strategies permit both overlapping selections and concurrent identical operations without restrictions; conflicts are resolved computationally using Additive Combination, Average, or Intersection methods when users simultaneously perform the same operation on joint vertices. For strategies (2) and (3), and represent User 1 and User 2's respective individual actions, while results show what both users see in real-time.
• Figure 2: Multi-object transformation operations: (a) translation, (b) rotation, and (c) scaling performed relative to the group centroid.
• Figure 3: Partial Overlap Support Examples for NDS co-manipulation scenarios.
• Figure 4: Task environment examples: (a) User Study 1, (b) User Study 2, and (c) the workbench in the physical environment.
• Figure 5: Comparison of Objective Metrics Across Three Methods (a -- g); Box plots of subjective questionnaires for User Study 1 (h -- k). The four subscales of (k) are (1) Co-presence; (2) Attentional allocation; (3) Perceived message understanding, and (4) Perceived behavioral interdependence. The colors represent the Averaging, Additive Combination, and Intersection conditon ($p<.05$(*), $p<.01$(**), $p<.001$(***)).