Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Visual SLAM based on dynamic object removal

Liu, Hanjie, Liu, Guoliang, Tian, Guohui, Xin, Shiqing and Ji, Ze ORCID: 2019. Visual SLAM based on dynamic object removal. Presented at: IEEE Robio 2019, Dali, China, 6-8 December 2019. 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, pp. 596-601. 10.1109/ROBIO49542.2019.8961397

[thumbnail of Ji Z - 476.pdf] PDF - Accepted Post-Print Version
Download (2MB)


Visual simultaneous localization and mapping (SLAM) is the core of intelligent robot navigation system. Many traditional SLAM algorithms assume that the scene is static. When a dynamic object appears in the environment, the accuracy of visual SLAM can degrade due to the interference of dynamic features of moving objects. This strong hypothesis limits the SLAM applications for service robot or driverless car in the real dynamic environment. In this paper, a dynamic object removal algorithm that combines object recognition and optical flow techniques is proposed in the visual SLAM framework for dynamic scenes. The experimental results show that our new method can detect moving object effectively and improve the SLAM performance compared to the state of the art methods.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: IEEE
ISBN: 9781728163222
Date of First Compliant Deposit: 20 November 2019
Date of Acceptance: 1 November 2019
Last Modified: 07 Dec 2022 14:14

Citation Data

Cited 11 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics