# DIJIT: A Robotic Head for an Active Observer

arXiv: https://arxiv.org/abs/2512.07998 · HTML: https://mlsanity.com/paper/2512.07998/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 50 references that are in the map.
- First posted on arXiv 8 Dec 2025.

## Builds on (most cited first, 4 of 4)

- [Revisiting Active Perception](https://mlsanity.com/paper/1603.02729/) (2016)
- [A Survey on Active Simultaneous Localization and Mapping: State of the Art and New Frontiers](https://mlsanity.com/paper/2207.00254/) (2022)
- [Improving saliency models' predictions of the next fixation with humans' intrinsic cost of gaze shifts](https://mlsanity.com/paper/2207.04250/) (2022)
- [The Psychophysics of Human Three-Dimensional Active Visuospatial Problem-Solving](https://mlsanity.com/paper/2306.11756/) (2023)

## Abstract (arXiv)

We present DIJIT, a novel binocular robotic head expressly designed for mobile agents that behave as active observers. DIJIT's unique breadth of functionality enables active vision research and the study of human-like eye and head-neck motions, their interrelationships, and how each contributes to visual ability. DIJIT is also being used to explore the differences between how human vision employs eye/head movements to solve visual tasks and current computer vision methods. DIJIT's design features nine mechanical degrees of freedom, while the cameras and lenses provide an additional four optical degrees of freedom. The ranges and speeds of the mechanical design are comparable to human performance. DIJIT attains 85% of the peak human saccade speed. Our design includes the ranges of motion required for convergent stereo, namely, vergence, version, and cyclotorsion. Here, we present DIJIT and some aspects of its performance. We also present a novel method for saccadic camera movements, using a direct relationship between camera orientation and motor values. The resulting saccadic camera movements are close to human movements in terms of their accuracy, with 1.17^circ and 1.14^circ mean error for the left and right cameras, respectively.