Tong Ru, Wu Zhengxing, Wang Jinge, Huang Yupei, Chen Di, Yu Junzhi
Laboratory of Cognitive and Decision Intelligence for Complex System, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China.
Biomimetics (Basel). 2024 Mar 12;9(3):171. doi: 10.3390/biomimetics9030171.
Biological fish exhibit a remarkably broad-spectrum visual perception capability. Inspired by the eye arrangement of biological fish, we design a fish-like binocular vision system, thereby endowing underwater bionic robots with an exceptionally broad visual perception capacity. Firstly, based on the design principles of binocular visual field overlap and tangency to streamlined shapes, a fish-like vision system is developed for underwater robots, enabling wide-field underwater perception without a waterproof cover. Secondly, addressing the significant distortion and parallax of the vision system, a visual field stitching algorithm is proposed to merge the binocular fields of view and obtain a complete perception image. Thirdly, an orientation alignment method is proposed that draws scales for yaw and pitch angles in the stitched images to provide a reference for the orientation of objects of interest within the field of view. Finally, underwater experiments evaluate the perception capabilities of the fish-like vision system, confirming the effectiveness of the visual field stitching algorithm and the orientation alignment method. The results show that the constructed vision system, when used underwater, achieves a horizontal field of view of 306.56°. The conducted work advances the visual perception capabilities of underwater robots and presents a novel approach to and insight for fish-inspired visual systems.
生物鱼具有非常广泛的视觉感知能力。受生物鱼眼睛排列的启发,我们设计了一种类鱼双目视觉系统,从而赋予水下仿生机器人极其广泛的视觉感知能力。首先,基于双目视野重叠和与流线型形状相切的设计原则,为水下机器人开发了一种类鱼视觉系统,使其能够在不使用防水罩的情况下进行宽视野水下感知。其次,针对视觉系统的显著畸变和视差问题,提出了一种视野拼接算法,用于合并双目视野并获得完整的感知图像。第三,提出了一种方位对准方法,在拼接图像中绘制偏航角和俯仰角的刻度,为视野内感兴趣物体的方位提供参考。最后,通过水下实验评估了类鱼视觉系统的感知能力,证实了视野拼接算法和方位对准方法的有效性。结果表明,构建的视觉系统在水下使用时,水平视野达到306.56°。所开展的工作提升了水下机器人的视觉感知能力,并为受鱼启发的视觉系统提供了一种新方法和见解。