AMP-IT and WISDOM: Improving 3D Manipulation for High-Precision Tasks in Virtual Reality
Francielly Rodrigues, Alexander Giovannelli, Leonardo Pavanatto, Haichao Miao, Jauvane C. de Oliveira, Doug A. Bowman
Abstract
Precise 3D manipulation in virtual reality (VR) is essential for effectively aligning virtual objects. However, state-of-the-art VR manipulation techniques have limitations when high levels of precision are required, including the unnaturalness caused by scaled rotations and the increase in time due to degree-of-freedom (DoF) separation in complex tasks. We designed two novel techniques to address these issues: AMP-IT, which offers direct manipulation with an adaptive scaled mapping for implicit DoF separation, and WISDOM, which offers a combination of Simple Virtual Hand and scaled indirect manipulation with explicit DoF separation. We compared these two techniques against baseline and state-of-the-art manipulation techniques in a controlled experiment. Results indicate that WISDOM and AMP-IT have significant advantages over best-practice techniques regarding task performance, usability, and user preference.