导盲犬行走机构运动仿真及其视觉识别算法研究

Research on Motion Simulation and Visual Recognition Algorithm of Guide Dog Walking Mechanism

针对导盲犬训练成本高等系列问题,文中提出了一种具有视觉识别功能的行走装置,该装置能够实现单个步进电机驱动四足机构行走。通过对行走机构进行运动仿真,得到的数据显示四足相对于地面交替上升、交替落地,能够在较为复杂的非结构环境下平稳运行。以人行横道上的红绿灯的识别为例,提出了一种基于YOLO的机械导盲犬视觉识别算法,判断当前信号灯状态是否可通行。机械导盲犬识别绿灯准确率为87.96%,红灯准确率为89.38%,检测速度为23.5 frame·s^(-1),能实时检测并区分人行横道红绿灯信息。

In view of problems such as high training cost for guide dogs,this study proposes a walking mechanism with visual recognition function,which can realize a single stepper motor to drive a four-legged mechanism to walk.Through the simulation of the movement of the walking mechanism,the obtained data show that the four feet can alternately rise and fall relative to the ground,and can run smoothly in a more complex non-structural environment.Taking the recognition of the traffic lights on the crosswalk as an example,a visual recognition algorithm for mechanical guide dogs based on YOLO is proposed to determine whether the current signal status is passable.The mechanical guide dog recognizes 87.96%of the green light and 89.38%of the red light,and the detection speed is 23.5 frame·s^(-1),indicating that the mechanical guide dog can detect and distinguish the traffic light information of pedestrian crossings in real time.