低成本机器人相机系统，靠学习人类动作实现自动运镜。
IRIS: Learning-Driven Task-Specific Cinema Robot Arm for Visuomotor Motion Control
- 用人类示范数据训练，让机械臂自动学拍电影镜头。
- 成本低于1000美元，定位精度约1毫米，可扛1.5公斤重物。
- 适合影视制作、自动化拍摄等需要精准动态运镜的场景。
机器人摄像系统能实现超越人力的动态、可重复运动，但因工业级平台成本高、操作复杂，普及受限。本文提出智能机器人影像系统（IRIS），一种面向特定任务的6-自由度机械臂，用于自主、学习驱动的电影级运动控制。IRIS结合轻量化全3D打印硬件与基于动作分块变换器（ACT）的目标条件视觉运动模仿学习框架，直接从人类示范中学习具对象感知和视觉流畅性的摄像轨迹，无需显式几何编程。整个平台成本低于1000美元，支持1.5公斤负载，重复定位精度约1毫米。真实世界实验表明，系统具备准确轨迹跟踪能力、可靠的自主执行效果，并能泛化至多种电影运镜任务。
原文摘要 · Abstract (English)
Robotic camera systems enable dynamic, repeatable motion beyond human capabilities, yet their adoption remains limited by the high cost and operational complexity of industrial-grade platforms. We present the Intelligent Robotic Imaging System (IRIS), a task-specific 6-DOF manipulator designed for autonomous, learning-driven cinematic motion control. IRIS integrates a lightweight, fully 3D-printed hardware design with a goal-conditioned visuomotor imitation learning framework based on Action Chunking with Transformers (ACT). The system learns object-aware and perceptually smooth camera trajectories directly from human demonstrations, eliminating the need for explicit geometric programming. The complete platform costs under $1,000 USD, supports a 1.5 kg payload, and achieves approximately 1 mm repeatability. Real-world experiments demonstrate accurate trajectory tracking, reliable autonomous execution, and generalization across diverse cinematic motions.
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