用毫米波雷达实现9种手势精准控制机械臂，无需接触且隐私安全。
Gesture-Based Robot Control Integrating Mm-wave Radar and Behavior Trees
- 融合毫米波雷达与行为树，实现手势识别与机器人控制一体化
- 9种手势识别准确率高，实时映射为机械臂动作指令
- 适合家庭与工业场景，隐私保护好、光照环境适应性强
随着机器人在家庭和工业场景中的普及，对直观高效的人机交互需求持续增长。手势识别提供了一种无需物理接触的自然控制方式，可借助多种传感技术实现。无线方案尤其灵活且侵入性低。尽管视觉系统常用，但常引发隐私担忧，并在复杂或光线不足环境下表现不佳。相比之下，雷达传感具有隐私保护优势，抗遮挡和光照干扰能力强，可获取距离、相对速度、角度等丰富空间信息。本文提出一种基于毫米波雷达的手势控制机械臂系统，实现可靠、无接触的动作识别。九种手势被准确识别并实时映射为控制命令。通过案例研究验证了系统的实用性、性能与可靠性。与以往将手势识别与机器人控制分离的工作不同，本系统将两者整合为实时处理流水线，实现无缝、非接触式人机交互。
原文摘要 · Abstract (English)
As robots become increasingly prevalent in both homes and industrial settings, the demand for intuitive and efficient human-machine interaction continues to rise. Gesture recognition offers an intuitive control method that does not require physical contact with devices and can be implemented using various sensing technologies. Wireless solutions are particularly flexible and minimally invasive. While camera-based vision systems are commonly used, they often raise privacy concerns and can struggle in complex or poorly lit environments. In contrast, radar sensing preserves privacy, is robust to occlusions and lighting, and provides rich spatial data such as distance, relative velocity, and angle. We present a gesture-controlled robotic arm using mm-wave radar for reliable, contactless motion recognition. Nine gestures are recognized and mapped to real-time commands with precision. Case studies are conducted to demonstrate the system practicality, performance and reliability for gesture-based robotic manipulation. Unlike prior work that treats gesture recognition and robotic control separately, our system unifies both into a real-time pipeline for seamless, contactless human-robot interaction.
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