Goal

Identify design principles for effective bare-hand travel techniques using the Leap Motion Controller across different types of 3D navigation tasks.

Challenge

• Bare-hand devices like the Leap have a limited tracking workspace (~3–50cm) and lose accuracy beyond ~80° hand rotation — making it unclear how to design reliable travel techniques around these constraints

• No established design guidance existed for this new class of input devices

Approach

• Designed and prototyped 5 travel techniques spanning 2 metaphors (airplane, camera-in-hand), 2 control types (rate vs. position), and 2 handedness modes (unimanual vs. bimanual)

• Evaluated with 12 participants across 3 task types: absolute travel, naïve search, and path following

• Used ANOVA to measure technique effect on speed and accuracy per task

My Role

Lead researcher responsible for technique design, prototype implementation, study design, and analysis.

Key Findings

• Camera-in-hand was significantly faster for search tasks — found all 12 targets faster than all 4 airplane techniques (p < 0.005)

• Airplane metaphor was significantly more accurate for path following (p < 0.0001) — better suited where precise trajectory control matters

• Bimanual techniques required more learning time — efficiency gap vs. unimanual narrowed only in the second half of tasks

• Continuous speed control (finger-based) outperformed discrete methods and provided a better user experience overall

• Key insight: no single technique wins across tasks — technique choice must match the navigation goal