Scene perception based visual navigation of mobile robot in indoor environment. (March 2021)

• Record Type: Journal Article
• Authors: Ran, T.; Yuan, L.; Zhang, J.b.
• Is Part Of: ISA transactions. Volume 109(2021)
• Page Start: 389
• Page End: 400
• Publication Date: 2021-03
• Subjects: Indoor mobile robot -- Visual navigation -- Convolution neural networks -- Scene perception -- Obstacle avoidance; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2020.10.023
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: Only vision-based navigation is the key of cost reduction and widespread application of indoor mobile robot. Consider the unpredictable nature of artificial environments, deep learning techniques can be used to perform navigation with its strong ability to abstract image features. In this paper, we proposed a low-cost way of only vision-based perception to realize indoor mobile robot navigation, converting the problem of visual navigation to scene classification. Existing related research based on deep scene classification network has lower accuracy and brings more computational burden. Additionally, the navigation system has not yet been fully assessed in the previous work. Therefore, we designed a shallow convolutional neural network (CNN) with higher scene classification accuracy and efficiency to process images captured by a monocular camera. Besides, we proposed an adaptive weighted control (AWC) algorithm and combined with regular control (RC) to improve the robot's motion performance. We demonstrated the capability and robustness of the proposed navigation method by performing extensive experiments in both static and dynamic unknown environments. The qualitative and quantitative results showed that the system performs better compared to previous related work in unknown environments. Highlights: The proposal of our low-cost scene perception based local visual indoor navigation. The design of a shallow and efficient CNN structure for scene perception. The adaptive weighted control algorithm that improved the local motion capability.