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.

翻译：机器人摄像系统能够实现超越人类能力的动态、可重复运动，然而工业级平台的高成本和操作复杂性限制了其广泛应用。本文提出智能机器人成像系统（IRIS），一种专为自主、学习驱动的电影运动控制设计的任务专用六自由度机械臂。IRIS将轻量化全3D打印硬件设计与基于Transformer动作分块（ACT）的目标条件视觉运动模仿学习框架相结合。该系统能够直接从人类演示中学习物体感知且感知平滑的摄像机轨迹，无需显式几何编程。完整平台成本低于1000美元，支持1.5千克有效载荷，并实现约1毫米的重复定位精度。真实场景实验验证了系统在精确轨迹跟踪、可靠自主执行以及多样化电影运动泛化方面的优异性能。