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A review of the application of staircase scene recognition system in assisted motion.

Authors :
Kong, Weifeng
Tan, Zhiying
Fan, Wenbo
Tao, Xu
Wang, Meiling
Xu, Linsen
Xu, Xiaobin
Source :
Digital Signal Processing. Mar2024, Vol. 146, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

Staircase recognition is of great significance for exoskeleton robot mode switching and mobile robot foothold calculation, which can improve the overall performance of the robot in the staircase scene. As a common terrain, stairs are quite difficult for mobile robots or people with lower limb disabilities and visual impairment. However, there are still some problems from the sensor's characteristics and external interference limiting the development of this technology. Despite the growing demand for recognition in this area and the emergence of a large number of related methods, there is a lack of a systematic and comprehensive review. Therefore, this paper reviews and compares the advantages and disadvantages of various methods, and provides the next research hotspots and directions. This paper first analyzes and summarizes the current mainstream perception hardware from the perspective of scene information acquisition, including wearable sensors, photoelectric sensors, multi-sensor fusion and ultrasonic sensors, which can be installed on the head, chest, waist, knees and legs, and soles of feet, respectively. Then, the existing recognition methods of ascending and descending stairs are compared and analyzed from four aspects of sensor type, installation location, processing algorithm and recognition accuracy. The research progress of staircase scene recognition in auxiliary motion is introduced in detail. Finally, the application prospects and fields of staircase scene recognition are analyzed, and the future development direction is prospected. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10512004
Volume :
146
Database :
Academic Search Index
Journal :
Digital Signal Processing
Publication Type :
Periodical
Accession number :
175364527
Full Text :
https://doi.org/10.1016/j.dsp.2023.104362