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Robust visual line-following navigation system for humanoid robots

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Abstract

This paper implements a novel line-following system for humanoid robots. Camera embedded on the robot’s head captures the image and then extracts the line using a high-speed and high-accuracy rectangular search method. This method divides the search location into three sides of rectangle and performs image convolution by edge detection matrix. The extracted line is used to calculate relative parameters, including forward velocity, lateral velocity and angular velocity that drive line-following walking. A proposed path curvature estimation method generates the forward velocity and guidance reference point of the robot. A classical PID controller and a PID controller with angle compensation are then used to set the lateral velocity and angular velocity of the robot, improving the performance in tracking a curved line. Line-following experiments for various shapes were conducted using humanoid robot NAO. Experimental results demonstrate the robot can follow different line shapes with the tracking error remaining at a low level. This is a significant improvement from existing biped robot visual navigation systems.

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Acknowledgement

The authors deeply acknowledge the financial support from Xiamen University of Technology, Fujian, P.R. China under the Xiamen University of Technology Scientific Research Foundation for Talents plan.

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Authors and Affiliations

  1. School of Electrical Engineering and Automation, Xiamen University of Technology, No. 600, Ligong Road, Jimei, Xiamen, 361024, People’s Republic of China

    Li-Hong Juang

  2. Engineering College, HuaQiao University, No. 269,Chenghua North Road, Fengze District, Quanzhou, Fujian, 362021, People’s Republic of China

    Jian-Sen Zhang

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  1. Li-Hong Juang
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  2. Jian-Sen Zhang
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Contributions

The contributions of this paper are: (1) a line-following method that uses the Gaussian filter and a simple convolution kernel to extract line information and improves the processing speed by using rectangle search; (2) A curvature approximation method to generate forward velocity; and (3) a PID controller with angle compensation to adapt to different curves. When applied collectively, the humanoid robot NAO’s navigation performance was comparatively robust and accurate.

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Correspondence to Li-Hong Juang.

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Juang, LH., Zhang, JS. Robust visual line-following navigation system for humanoid robots. Artif Intell Rev 53, 653–670 (2020). https://doi.org/10.1007/s10462-018-9672-9

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