机器人感知中先进光学技术的原理与应用

自21世纪以来，机器人技术已取得长足发展且已融入人们日常生活之中。类似于人类通过感官获得信息的方式，机器人的感知能力是其智能化的先决条件之一。在众多的感知技术中，光学感知技术被认为具有最大潜力。一方面，机器人所处环境中物质的光学特性、位置姿态以及运动状态等信息都可以通过光波携带的丰富信息维度进行感知和编码，从而使得机器人能够理解其周围环境。另一方面，在工业领域，激光的产生、调制、探测和集成等技术已经日趋成熟。因此，结合机器人特定的感知需求和先进的光学技术，可以创造性地增强机器人的感知能力并拓展其感知边界。

本文旨在研究以激光雷达为代表的主动光电感知技术，以解决机器人感知领域的实际问题。首先，本文建立了激光雷达系统级测距性能模型。该模型综合考虑了激光雷达的测量机制、光学过程、光收发器件、信号处理电路、算法以及不同天气条件等方面涉及的物理和数学模型。该模型可为激光雷达产业界提供指导，帮助研发人员从感知需求出发进行光机设计、波长选择、探测器选择、算法选择以及测量机制选择。该模型具有详实的理论支撑和高度可操作性的工程价值。

  其次，本文进行了光学感知机理和样机落地的新尝试。针对鸡尾酒会场景中的人机语音交互问题，本研究研制出名为激光实现的机器人耳朵（Robot Ear Accomplished by Laser，REAL）的样机。REAL利用振动表面散射光的光强变化，从说话人的口罩或喉咙表面无接触获取清晰的语音内容。该方法不受环境中的声学噪声影响，同时具备十几米的测量范围。该技术有望彻底解决语音交互领域的鸡尾酒会问题。

最后，本文进行了感知系统集成和算法开发的工作。针对无人机入侵问题，本文将非重复扫描的远距离激光雷达、相机和自研64通道非均匀麦克风阵列集成，研制了一套多模态小型无人机三维轨迹追踪系统（Multimodal Unmanned Aerial Vehicle 3D Trajectory Exposure System，MUTES）。MUTES同时具备麦克风阵列远量程宽视场角、相机像素精度高识别率高以及激光雷达测距精度高的优点。该系统采用了粗到精和被动到主动的定位策略，其有效性被现场实验验证。MUTES具备业界最远的探测范围（500米半径的半球）、最高的三维定位精度（小于距离的1.5%）、强大的抗干扰能力和可接受的成本，可应用于反无人机窃听、反无人机侦查和野外无人机高精度定位等任务。

通过上述研究工作，本论文在激光雷达的基本原理和系统建模、光学感知机理创新和样机开发、感知系统集成和算法开发等方面进行了深入研究和探索，为主动光电感知技术在机器人领域的应用提供了重要的理论和实践基础。

Since the 21st century, robot technology has made significant advances and has become integrated into people's daily lives. Similar to humans acquiring information through their senses, the perceptual ability of robots is one of the prerequisites for their intelligence. Among various perceptual technologies, optical sensing technology is considered to have the greatest potential. On the one hand, the rich information dimension carried by light waves allows for the perception and encoding of optical characteristics, position, posture, and motion of substances in the robot sensing environment, enabling the robot to understand its surroundings. On the other hand, in the industrial field, the generation, modulation, detection, and integration of lasers, technology has become increasingly mature. Therefore, by combining the specific perceptual needs of robots with advanced optical technology, the perceptual ability of robots can be creatively enhanced, and their perceptual boundaries expanded.

This thesis aims to investigate active optoelectronic sensing technology, particularly Lidar, to address practical problems in the field of robot perception. Firstly, a Lidar system-level ranging performance model is established, integrating physical and mathematical models related to Lidar's measurement mechanism, optical processes, transceiver components, signal processing circuits, algorithms, and diverse weather conditions. This model provides guidance for the Lidar industry, aiding research and development personnel in optical mechanical design, wavelength selection, detector selection, algorithm selection, and measurement mechanism selection based on sensing requirements. It offers substantial theoretical support and high practical engineering value.

Secondly, this thesis presents novel attempts in optical perception mechanisms and prototype development. To address human-robot speech interaction in a cocktail party scenario, we devised a prototype named Robot Ear Accomplished by Laser (REAL). REAL obtains clear speech content from the speaker's mask or throat surface without contact, using the intensity changes of scattered laser from the vibrating surface. This method is not affected by acoustic noise in the environment and has a measurement range of more than ten meters. This technology is expected to completely solve the cocktail party problem in the field of voice interaction.

Finally, this thesis conducted work on perception system integration and algorithm development. Focusing on the issue of unmanned aerial vehicle intrusion, the study integrated non-repetitive scanning long-range Lidar, a camera, and a self-developed 64-channel non-uniform microphone array to develop a Multimodal UAV (Unmanned Aerial Vehicle) 3D Trajectory Tracking System (MUTES). The MUTES has advantages of a long-range wide field of view of microphone array, high-resolution and high identification rate of camera, and high ranging precision of Lidar. The system applies a positioning strategy from coarse to fine and passive to active, and its effectiveness has been validated through experiments. The MUTES system has the industry's farthest detection range (a hemispherical radius of 500 meters), the highest three-dimensional positioning accuracy (less than 1.5% of the distance), strong anti-interference capability, and acceptable costs, making it applicable for tasks such as anti-drone eavesdropping, anti-drone reconnaissance, and high-precision positioning of drones in the field.

Through the aforementioned research work, this thesis extensively explores the basic principles and system modeling of Lidar, as well as mechanism innovation, prototype development, system integration, and algorithm development. These efforts provide a crucial theoretical and practical foundation for the application of active optoelectronic sensing technology in the field of robotics.

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