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Chen et al. Intell Robot 2024;4:179-95 Intelligence & Robotics
DOI: 10.20517/ir.2024.11

Research Article Open Access

Towards environment perception for walking-aid robots:
an improved staircase shape feature extraction method

Xinxing Chen , Yuxuan Wang, Chuheng Chen, Yuquan Leng , Chenglong Fu
Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities, Southern University of
Science and Technology, Shenzhen 518055, Guangdong, China.

Correspondence to: Prof. Chenglong Fu, Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation
Robotics in Universities, Southern University of Science and Technology, Xueyuan Road No.1088, Shenzhen 518055, Guangdong,
China. Email: fucl@sustech.edu.cn

Howtocitethis article: Chen X, Wang Y, Chen C, Leng Y, Fu C. Towards environment perception for walking-aidrobots: an improved
staircase shape feature extraction method. Intell Robot 2024;4(2):179-95. http://dx.doi.org/10.20517/ir.2024.11
Received: 23 Feb 2024 First Decision: 9 Apr 2024 Revised: 4 May 2024 Accepted: 6 May 2024 Published: 13 May 2024

Academic Editor: Simon X. Yang Copy Editor: Pei-Yun Wang Production Editor: Pei-Yun Wang

Abstract
This paper introduces an innovative staircase shape feature extraction method for walking-aid robots to enhance en-
vironmental perception and navigation. We present a robust method for accurate feature extraction of staircases
under various conditions, including restricted viewpoints and dynamic movement. Utilizing depth camera-mounted
robots, we transform three-dimensional (3D) environmental point cloud into two-dimensional (2D) representations,
focusing on identifying both convex and concave corners. Our approach integrates the Random Sample Consensus
algorithm with K-Nearest Neighbors (KNN)-augmented Iterative Closest Point (ICP) for efficient point cloud regis-
tration. The results show an improvement in trajectory accuracy, with errors within the centimeter range. This work
overcomes the limitations of previous approaches and is of great significance for improving the navigation and safety
of walking assistive robots, providing new possibilities for enhancing the autonomy and mobility of individuals with
physical disabilities.

Keywords: Walking-aid robots, environment perception, staircase recognition, computer vision, feature extraction

© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0
International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, shar-
ing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you
give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate
if changes were made.

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