Precise Tool to Target Positioning Widgets (TOTTA) in Spatial Environments: A Systematic Review

TL;DR

This systematic review analyzes 70 designs of visual widgets used for precise positioning of tools in mixed reality, highlighting common features, feedback mechanisms, and the lack of standardized testing procedures.

Contribution

It provides a comprehensive overview of TOTTA visual widgets, identifying common design patterns and gaps in testing standards across various applications.

Findings

Widgets often use visual overlap and collimation cues

Designs frequently represent tool and target with similar shapes distinguished by topological features

Current testing procedures lack standardization and are biased towards specific participant groups

Abstract

TOTTA outlines the spatial position and rotation guidance of a real/virtual tool (TO) towards a real/virtual target (TA), which is a key task in Mixed Reality applications. The task error can have critical consequences regarding safety, performance, and quality, such as in surgical implantology or industrial maintenance scenarios. The TOTTA problem lacks a dedicated study and is scattered across different domains with isolated designs. This work contributes to a systematic review of the TOTTA visual widgets, studying 70 unique designs from 24 papers. TOTTA is commonly guided by visual overlap an intuitive, pre-attentive 'collimation' feedback of simple-shaped widgets: Box, 3D Axes, 3D Model, 2D Crosshair, Globe, Tetrahedron, Line, and Plane. Our research discovers that TO and TA are often represented with the same shape. They are distinguished by topological elements (e.g., edges, vertices, faces), colors, transparency levels, and added shapes, widget quantity, and size. Meanwhile, some designs provide continuous 'during manipulation feedback' relative to the distance between TO and TA by text, dynamic color, sonification, and amplified graphical visualization. Some approaches trigger discrete 'TA reached feedback,' such as color alteration, added sound, TA shape change, and added text. We found a lack of golden standards, including in testing procedures, as current ones are limited to partial sets with different and incomparable setups (different target configurations, avatar, background, etc.). We also found a bias in participants: right-handed, young male, non-color impaired.