Jinghan Yu, Junhao Xiao, Chenyu Zhu, Jiaming Li, Jia Li, HanMing Deng, Xirui Wang, Guoli Jia, Jianjun Li, Xiang Bai, Bowen Zhou, Zhiyuan Ma. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

Although virtual reality (VR) is becoming increasingly popular and many interaction techniques for navigating virtual environments, known as “locomotion techniques,” exist, data regarding the accessibility of locomotion techniques for people with upper-body motor impairments do not exist, making it difficult to understand which locomotion techniques work well for users and why. To address this gap, we conducted a study with 19 participants with upper-body motor impairments who completed a navigation task in VR using six seated locomotion techniques. We collected task performance data and elicited participant feedback using questionnaires and interviews. We found that participants performed similarly well with three techniques that required one controller input, little to no upper-body movement, and had a low perceived workload: Teleport, Astral Body, and Sliding Looking. However, Teleport was consistently favored in interview responses and could be considered the best technique for this group of participants. On the other hand, participants performed similarly poorly with three techniques that required arm, head, and torso movement and also rated these techniques as having a high workload: Chicken Acceleration, Grab and Pull, and Throw Teleport. However, participants did not necessarily prefer or want to use the techniques with which they performed best or had the lowest perceived workloads. Factors such as enjoyment, exercise, and presence sometimes outweighed accessibility. This finding suggests that accessibility alone should not override all other considerations when designing or recommending locomotion techniques to people with upper-body motor impairments, and that users with disabilities should have a range of accessible locomotion techniques to choose from based on their preferences.