发表机构
Mitsubishi Electric Research Laboratories (MERL); University of Pennsylvania（三菱电机研究实验室; 宾夕法尼亚大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对机器人在非结构化动态环境控制难题，提出SplatCtrl框架。基于3D高斯溅射，引入混合滤波和重定位策略用于场景重建，还提出从高斯推导距离函数的方法，纳入控制障碍函数，实现感知-动作耦合，经实验验证有效。
AI 中文摘要
机器人操纵器在结构化环境中表现出色，但在非结构化和动态环境中面临重大挑战。本文提出了SplatCtrl，这是一个用于实时场景重建和反应式机器人运动生成的统一框架，以在以前未见过且不断变化的环境中实现无碰撞机器人手臂控制。基于3D高斯溅射（3D-GS），我们引入了一种基于体素的混合滤波和动态高斯重定位策略，支持从RGB-D流进行高效场景重建并适应环境变化。为了实现安全和反应式控制，我们进一步提出了一种从各向同性高斯推导连续符号距离函数的方法，提供稳定且可微的碰撞概率估计，将经典距离场与现代隐式表示联系起来。这些连续距离度量被纳入控制障碍函数，形成一个统一的感知-动作耦合框架，支持响应场景变化的平滑且可靠的实时运动生成。在模拟、物理机器人和共享人机工作空间中的实验验证证明了该框架的有效性，在不确定和动态环境中实现了集成场景重建和反应式控制。
英文摘要
Robotic manipulators excel in structured environments but face substantial challenges in unstructured and dynamic settings. This paper presents SplatCtrl, a unified framework for real-time scene reconstruction and reactive robot motion generation to enable collision-free robotic arm control in previously unseen and continuously changing environments. Building on 3D Gaussian Splatting (3D-GS), we introduce a hybrid voxel-based filtering and dynamic Gaussian relocation strategy that supports efficient scene reconstruction from RGB-D streams while accommodating environmental changes. For safe and reactive control, we further propose a method for deriving continuous signed distance functions from isotropic Gaussians, providing stable and differentiable collision probability estimates that bridge classical distance fields with the modern implicit representation. These continuous distance metrics are incorporated into control barrier functions, resulting in a unified perception-action coupling framework that supports smooth and reliable real-time motion generation in response to scene changes. Experimental validation in simulation, on physical robot, and within shared human-robot workspace demonstrates the framework's effectiveness, achieving integrated scene reconstruction and reactive control in uncertain, and dynamic environments.
CommentsPublished in 2026 International Conference on Robotics and Automation (ICRA). 8 pages, 8 figures
