实时生成逼真三维地图，提升机器人远程操作效率。
Real-time Photorealistic Mapping for Situational Awareness in Robot Teleoperation
- 融合高斯溅射SLAM与现有系统，实现高效GPU加速
- 实测决策速度更快，环境交互更准确
- 适合无人机等需快速感知陌生环境的远程操作
在未知环境中实现高效的远程机器人操作尤为困难，因操作者需快速理解场景布局。在线3D建图是应对这一挑战的有效策略，可使操作者从多角度逐步探索环境。然而，传统基于地图的远程操作系统因计算成本过高，难以实时生成视觉逼真的3D地图，导致操作性能下降。本文提出一种新方案，通过将最新的高斯溅射SLAM技术与现有在线地图系统进行模块化、高效的GPU集成，显著提升实时性。我们在真实飞行器上进行了实验验证，结果表明该系统在决策速度和环境交互准确性方面均有显著提升，大幅增强了远程操作效率。本系统实现了逼真地图生成与实时性能的无缝结合，有效支持在陌生环境中的远程操作。
原文摘要 · Abstract (English)
Achieving efficient remote teleoperation is particularly challenging in unknown environments, as the teleoperator must rapidly build an understanding of the site's layout. Online 3D mapping is a proven strategy to tackle this challenge, as it enables the teleoperator to progressively explore the site from multiple perspectives. However, traditional online map-based teleoperation systems struggle to generate visually accurate 3D maps in real-time due to the high computational cost involved, leading to poor teleoperation performances. In this work, we propose a solution to improve teleoperation efficiency in unknown environments. Our approach proposes a novel, modular and efficient GPU-based integration between recent advancement in gaussian splatting SLAM and existing online map-based teleoperation systems. We compare the proposed solution against state-of-the-art teleoperation systems and validate its performances through real-world experiments using an aerial vehicle. The results show significant improvements in decision-making speed and more accurate interaction with the environment, leading to greater teleoperation efficiency. In doing so, our system enhances remote teleoperation by seamlessly integrating photorealistic mapping generation with real-time performances, enabling effective teleoperation in unfamiliar environments.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。