DIJIT: A Robotic Head for an Active Observer
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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.
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
4 of 50 references.
References · 4
- 2016Revisiting Active Perceptioncited by 94
- 2022A Survey on Active Simultaneous Localization and Mapping: State of the Art and New Frontierscited by 66
- 2022Improving saliency models' predictions of the next fixation with humans' intrinsic cost of gaze shiftscited by 4
- 2023The Psychophysics of Human Three-Dimensional Active Visuospatial Problem-Solvingcited by 2
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- 2026TAVIS: A Benchmark for Egocentric Active Vision and Anticipatory Gaze in Imitation Learning
- 2026Cortical Policy: A Dual-Stream View Transformer for Robotic Manipulation
- 2026ActiveScale: Scaling Active Perception for Robots across Model, Data, and Hardware
- 2026Behavior Foundations for Quadruped Robots: ABot-C0 Technical Report
- 2024Active Vision Might Be All You Need: Exploring Active Vision in Bimanual Robotic Manipulation
- 2026Towards Exploratory and Focused Manipulation with Bimanual Active Perception: A New Problem, Benchmark and Strategy