Liu Qiwei, Wang Xia, Xue Jiaan, Lv Shuaijun, Wei Ranfeng
Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of China, Beijing Institute of Technology, Beijing 100081, China.
Sensors (Basel). 2025 Apr 24;25(9):2708. doi: 10.3390/s25092708.
In response to the demand for small-size, high-precision, and real-time target distance measurement in platforms such as autonomous vehicles and drones, this paper investigates the multi-focal bionic compound eye (MFBCE) and its associated distance measurement algorithm. MFBCE was designed to integrate multiple lenses with different focal lengths and a CMOS array. Based on this system, a multi-eye distance measurement algorithm based on target detection was proposed. The algorithm derives the application of binocular distance measurement on cameras with different focal lengths, overcoming the limitation of traditional binocular algorithms that only work with identical cameras. By utilizing the multi-scale information obtained from multiple lenses with different focal lengths, the ranging accuracy of the MFBCE is improved. The telephoto lenses, with their narrow field of view, are beneficial for capturing detailed target information, while wide-angle lenses, with their larger field of view, are useful for acquiring information about the target's environment. Experiments using the least squares method for ranging targets at 100 cm yielded a mean absolute error (MAE) of 1.05, approximately one-half of the binocular distance measurement algorithm. The proposed MFBCE demonstrates significant potential for applications in near-range obstacle avoidance, robotic grasping, and assisted driving.
针对自动驾驶汽车和无人机等平台对小尺寸、高精度和实时目标距离测量的需求，本文研究了多焦点仿生复眼（MFBCE）及其相关的距离测量算法。MFBCE的设计是将多个不同焦距的透镜与一个CMOS阵列集成在一起。基于该系统，提出了一种基于目标检测的多眼距离测量算法。该算法推导了双目距离测量在不同焦距相机上的应用，克服了传统双目算法仅适用于相同相机的局限性。通过利用从多个不同焦距透镜获得的多尺度信息，提高了MFBCE的测距精度。长焦透镜视野窄，有利于捕捉目标细节信息，而广角透镜视野宽，有助于获取目标环境信息。使用最小二乘法对100厘米处的目标进行测距实验，平均绝对误差（MAE）为1.05，约为双目距离测量算法的一半。所提出的MFBCE在近程避障、机器人抓取和辅助驾驶等应用中显示出巨大潜力。
