Zhang Fu, Sun Haoxuan, Wang Jiajia, Wang Xinyue, Qiu Yubo, Cui Xiahua, Ali Shaukat
College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, China.
Longmen Laboratory, Luoyang, China.
Front Vet Sci. 2024 Nov 20;11:1423453. doi: 10.3389/fvets.2024.1423453. eCollection 2024.
Inspired by the obstacle avoidance mechanism of goose neck, a theoretical design method of bionic robotic arm was proposed to solve the contradiction between high flexibility and strong bearing capacity in narrow space.
Taking the goose neck as the test object, a narrow space test environment with a width of 10 cm was built, and a 6 × 4 obstacle matrix was set up, to analyze the maximum value of joint angle, motion rate and trajectory in different target areas.
The test results showed that the goose neck movement has continuity and transmissibility. The overall posture of the goose neck was adjusted through the synergistic movement of the anterior, middle and posterior segments to move toward the target position. The regulating effect of the anterior segment was significantly stronger than that of the middle and posterior segments. Specifically, the anterior segment of goose neck exhibited mostly transverse movement, with significant horizontal regulation; the middle segment of the goose neck was coupled with longitudinal movement, with similar movement ability in all directions, the posterior segment of the goose neck has mostly longitudinal movement, with significant height regulation.
In addition, the YOLOv7-pose recognition network was used to recognize goose neck motion pose, which provides a new method for animal behavior research.
受鹅颈避障机制启发,提出一种仿生机器人手臂的理论设计方法,以解决狭窄空间中高灵活性与强承载能力之间的矛盾。
以鹅颈为测试对象,构建宽度为10厘米的狭窄空间测试环境,并设置6×4的障碍物矩阵,分析不同目标区域的关节角度、运动速率和轨迹的最大值。
测试结果表明,鹅颈运动具有连续性和传递性。鹅颈的整体姿态通过前段、中段和后段的协同运动进行调整,以朝着目标位置移动。前段的调节作用明显强于中段和后段。具体而言,鹅颈前段主要表现为横向运动,具有显著的水平调节作用;鹅颈中段与纵向运动耦合,各方向运动能力相似,鹅颈后段主要为纵向运动,具有显著的高度调节作用。
此外,采用YOLOv7姿态识别网络对鹅颈运动姿态进行识别,为动物行为研究提供了一种新方法。