Electronic Science and Technology ›› 2021, Vol. 34 ›› Issue (9): 66-72.doi: 10.16180/j.cnki.issn1007-7820.2021.09.012

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

ZHAO Chong1,CHI Mengmeng2,CHU Cong3,ZHANG Peng2   

  1. 1. Faculty of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming 650500,China
    2. School of Mechanical Engineering and Automation,Dalian Polytechnic University,Dalian 116034,China
    3. School of Information Science and Engineering,Dalian Polytechnic University,Dalian 116034,China
  • Received:2020-05-12 Online:2021-09-15 Published:2021-09-08
  • Supported by:
    Liaoning Education Department Fund(J2019020)


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.

Key words: Jansen mechanism, motion curve, unstructured environment, bionic degree, deep learning, feature fusion, target detection, loss function

CLC Number: 

  • TP391.41