Early Estimation of User's Intention of Tele-Operation Using Object Affordance and Hand Motion in a Dual First-Person Vision

TL;DR

This paper presents a method for early estimation of user intention in robot tele-operation by combining hand motion and object affordance cues from dual first-person vision, aiming to reduce latency.

Contribution

It introduces a novel approach that integrates hand motion and object affordance analysis for proactive intention estimation in tele-operation.

Findings

Effective intention estimation reduces robot response latency.

Experimental results validate the approach in object pickup tasks.

Improved tele-operation responsiveness demonstrated.

Abstract

This paper describes a method of estimating the intention of a user's motion in a robot tele-operation scenario. One of the issues in tele-operation is latency, which occurs due to various reasons such as a slow robot motion and a narrow communication channel. An effective way of reducing the latency is to estimate the human intention of motions and to move the robot proactively. To enable a reliable early intention estimation, we use both hand motion and object affordances in a dual first-person vision (robot and user) with an HMD. Experimental results in an object pickup scenario show the effectiveness of the method.