Robot Target Localization and Visual Navigation Based on Neural Network

Abstract

Deep neural network has been widely used in image analysis, speech recognition, target detection, semantic segmentation, face recognition, automatic driving, and other fields due to its excellent algorithm performance. In this research, the neural network is mainly used to simulate robot target localization and visual navigation. Firstly, the data set based on ICP algorithm is constructed, and then, the navigation and positioning of robot are simulated by using neural network. The results show that the combination of ICP algorithm and direct method can effectively solve the problem of pose loss and expand the indoor range of data collection. The method using artificial neural network is effective and has better robustness and stability than the method based on frame matching. From the perspective of vision, positioning and navigation based on a single RGB image are feasible, and the processing time is relatively short, which can meet the requirements of real time and has higher practical value in general indoor scenes.

High precision visual localization method of UAV based on feature matching

“…The descriptors obtained by the AKAZE's feature algorithm have rotation invariance, scale invariance, illumination invariance, space invariance, etc., and have high robustness, feature uniqueness, and feature accuracy. In view of the real-time requirements of the algorithm and the characteristics of rotation, scaling, and translation of the UAV operation images, this paper studies the UAV visual navigation (Cao et al, 2022 ; Guo et al, 2022 ; Qin et al, 2022 ; Zhao et al, 2022 ) algorithm based on the improved AKAZE algorithm, especially the precise hovering problem in UAV operation.…”

Retracted: Robot Target Localization and Visual Navigation Based on Neural Network

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”