CaFe-TeleVision: A Coarse-to-Fine Teleoperation System with Immersive Situated Visualization for Enhanced Ergonomics

TL;DR

CaFe-TeleVision is a teleoperation system that improves efficiency and ergonomics through a coarse-to-fine control mechanism and immersive situated visualization, validated by user studies and quantitative performance metrics.

Contribution

The paper introduces a novel coarse-to-fine control and immersive visualization framework that enhances teleoperation ergonomics and efficiency, validated on a humanoid robot with challenging tasks.

Findings

Significantly reduces user task load and increases acceptance.

Outperforms comparative methods with up to 28.89% higher success rate.

Speeds up task completion by 26.81%.

Abstract

Teleoperation presents a promising paradigm for remote control and robot proprioceptive data collection. Despite recent progress, current teleoperation systems still suffer from limitations in efficiency and ergonomics, particularly in challenging scenarios. In this paper, we propose CaFe-TeleVision, a coarse-to-fine teleoperation system with immersive situated visualization for enhanced ergonomics. At its core, a coarse-to-fine control mechanism is proposed in the retargeting module to bridge workspace disparities, jointly optimizing efficiency and physical ergonomics. To stream immersive feedback with adequate visual cues for human vision systems, an on-demand situated visualization technique is integrated in the perception module, which reduces the cognitive load for multi-view processing. The system is built on a humanoid collaborative robot and validated with six challenging bimanual manipulation tasks. User study among 24 participants confirms that CaFe-TeleVision enhances ergonomics with statistical significance, indicating a lower task load and a higher user acceptance during teleoperation. Quantitative results also validate the superior performance of our system across six tasks, surpassing comparative methods by up to 28.89% in success rate and accelerating by 26.81% in completion time. Project webpage: https://clover-cuhk.github.io/cafe_television/