Enhanced Visual Feedback with Decoupled Viewpoint Control in Immersive Humanoid Robot Teleoperation using SLAM

TL;DR

This paper introduces a novel SLAM-based visual feedback system for humanoid robot teleoperation that reduces latency, increases FOV, and enhances operator awareness by presenting real-time point cloud visualizations.

Contribution

The paper presents a decoupled viewpoint control method using SLAM to improve visual feedback in immersive humanoid robot teleoperation, addressing latency and FOV mismatches.

Findings

Reduced visual feedback latency improves operator immersion.

Enhanced FOV range matches operator headset, increasing situational awareness.

Real-time point cloud visualization effectively conveys robot's environment.

Abstract

In immersive humanoid robot teleoperation, there are three main shortcomings that can alter the transparency of the visual feedback: the lag between the motion of the operator's and robot's head due to network communication delays or slow robot joint motion. This latency could cause a noticeable delay in the visual feedback, which jeopardizes the embodiment quality, can cause dizziness, and affects the interactivity resulting in operator frequent motion pauses for the visual feedback to settle; (ii) the mismatch between the camera's and the headset's field-of-views (FOV), the former having generally a lower FOV; and (iii) a mismatch between human's and robot's range of motions of the neck, the latter being also generally lower. In order to leverage these drawbacks, we developed a decoupled viewpoint control solution for a humanoid platform which allows visual feedback with low-latency and artificially increases the camera's FOV range to match that of the operator's headset. Our novel solution uses SLAM technology to enhance the visual feedback from a reconstructed mesh, complementing the areas that are not covered by the visual feedback from the robot. The visual feedback is presented as a point cloud in real-time to the operator. As a result, the operator is fed with real-time vision from the robot's head orientation by observing the pose of the point cloud. Balancing this kind of awareness and immersion is important in virtual reality based teleoperation, considering the safety and robustness of the control system. An experiment shows the effectiveness of our solution.