LocoScooter: Designing a Stationary Scooter-Based Locomotion System for Navigation in Virtual Reality

TL;DR

LocoScooter tackles the challenge of locomotion in space-limited VR by introducing a compact, scooter-inspired interface that decouples forward propulsion (foot-sliding) from steering (handlebar rotation). Built from commodity hardware and integrated with Unreal Engine, it enables continuous, sensorimotor-aligned navigation within a small footprint without room-scale tracking. A within-subject study shows comparable task efficiency to joystick navigation while delivering higher immersion and enjoyment, with a dissociation between increased physical demand and fatigue. The work demonstrates the potential of metaphor-driven, embodied locomotion for deployable VR experiences in public demos, education, and fitness contexts, and offers design guidance for balancing physical engagement with usability and adaptability.

Abstract

Virtual locomotion remains a challenge in VR, especially in space-limited environments where room-scale walking is impractical. We present LocoScooter, a low-cost, deployable locomotion interface combining foot-sliding on a compact treadmill with handlebar steering inspired by scooter riding. Built from commodity hardware, it supports embodied navigation through familiar, physically engaging movement. In a within-subject study (N = 14), LocoScooter significantly improved immersion, enjoyment, and bodily involvement over joystick navigation, while maintaining comparable efficiency and usability. Despite higher physical demand, users did not report increased fatigue, suggesting familiar movements can enrich VR navigation.

Figures (9)

• Figure 1: LocoScooter system diagram consists of three parts: User, Sensors, and VR. The User section represents the direct interaction through hands and feet, where users rotate the handlebar or step on the treadmill to control the virtual scooter’s forward movement or rotation in the VR environment. The Sensors, equipped with two angle encoders attached to the LocoScooter, directly receive the user’s raw action data, which is then analyzed and converted into electric numeric data by a control unit. This processed data is transmitted via UDP through a Wi-Fi router to the VR system. The VR system is responsible for receiving the processed data from the Sensors and mapping it into the avatar’s motion, providing visual cue feedback to the user, which can be observed in the VR.
• Figure 2: System components of LocoScooter. The platform combines a welded frame, commercial scooter, and treadmill. Steering and foot-sliding are tracked by rotary encoders, with signals processed by an ESP32 microcontroller and transmitted wirelessly to the VR application.
• Figure 3: Top-down view of the VR city environment (map) used in the study. The red pin indicates the starting position, and the orange circles represent target locations that participants navigated to during the tasks.
• Figure 4: Illustration of the experimental procedure. (1) Participants receive a location prompt (e.g., "Please go to 'Pizzeria'"). (2) A navigation path appears on the ground in the virtual environment to guide movement. (3) Upon reaching the blue goal zone, participants must stop and dwell for 2 seconds to complete the round. They are then teleported back to the starting position to begin the next of six trials, each targeting a different location.
• Figure 5: Representative paths taken by participants in the virtual city navigation task. Colored lines illustrate different routes from the starting location (orange dot) to various target destinations across the environment. This visualization highlights the spatial coverage and directional variety of participant movements during the experiment.