Muhammad S. Alam^1,5,*, Farhan B. Mohamed^1,3, Ali Selamat², Faruk Ahmed⁴, AKM B. Hossain^6,7

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 417-436, 2024, DOI:10.32604/iasc.2024.051999 - 11 July 2024

Abstract Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems. The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed. This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence. An annotated image dataset trains the proposed system and predicts the camera pose in real-time. The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera More >

Lieping Zhang^1,2, Xiaoxu Shi^1,2, Liu Tang^1,2, Yilin Wang³, Jiansheng Peng⁴, Jianchu Zou^4,*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2111-2136, 2024, DOI:10.32604/cmc.2024.047235 - 27 February 2024

Abstract A Rapid-exploration Random Tree (RRT) autonomous detection algorithm based on the multi-guide-node deflection strategy and Karto Simultaneous Localization and Mapping (SLAM) algorithm was proposed to solve the problems of low efficiency of detecting frontier boundary points and drift distortion in the process of map building in the traditional RRT algorithm in the autonomous detection strategy of mobile robot. Firstly, an RRT global frontier boundary point detection algorithm based on the multi-guide-node deflection strategy was put forward, which introduces the reference value of guide nodes’ deflection probability into the random sampling function so that the global… More >

Jiansheng Peng^1,2,*, Qing Yang¹, Dunhua Chen¹, Chengjun Yang², Yong Xu², Yong Qin²

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 167-196, 2024, DOI:10.32604/cmc.2023.041900 - 30 January 2024

Abstract Dynamic Simultaneous Localization and Mapping (SLAM) in visual scenes is currently a major research area in fields such as robot navigation and autonomous driving. However, in the face of complex real-world environments, current dynamic SLAM systems struggle to achieve precise localization and map construction. With the advancement of deep learning, there has been increasing interest in the development of deep learning-based dynamic SLAM visual odometry in recent years, and more researchers are turning to deep learning techniques to address the challenges of dynamic SLAM. Compared to dynamic SLAM systems based on deep learning methods such… More >

Jiansheng Peng^1,2,*, Dunhua Chen¹, Qing Yang¹, Chengjun Yang², Yong Xu², Yong Qin²

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3209-3236, 2023, DOI:10.32604/cmc.2023.041898 - 26 December 2023

Abstract Visual simultaneous localization and mapping (SLAM) is crucial in robotics and autonomous driving. However, traditional visual SLAM faces challenges in dynamic environments. To address this issue, researchers have proposed semantic SLAM, which combines object detection, semantic segmentation, instance segmentation, and visual SLAM. Despite the growing body of literature on semantic SLAM, there is currently a lack of comprehensive research on the integration of object detection and visual SLAM. Therefore, this study aims to gather information from multiple databases and review relevant literature using specific keywords. It focuses on visual SLAM based on object detection, covering… More >

Jingtong Peng^*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2275-2291, 2023, DOI:10.32604/csse.2023.039272 - 28 July 2023

Abstract When applied to Unmanned Aerial Vehicles (UAVs), existing Simultaneous Localization and Mapping (SLAM) algorithms are constrained by several factors, notably the interference of dynamic outdoor objects, the limited computing performance of UAVs, and the holes caused by dynamic objects removal in the map. We proposed a new SLAM system for UAVs in dynamic environments to solve these problems based on ORB-SLAM2. We have improved the Pyramid Scene Parsing Network (PSPNet) using Depthwise Separable Convolution to reduce the model parameters. We also incorporated an auxiliary loss function to supervise the hidden layer to enhance accuracy. Then… More >

Gengyu Ge^1,2,*, Zhong Qin¹, Xin Chen¹

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6351-6369, 2023, DOI:10.32604/cmc.2023.035832 - 28 December 2022

Abstract Localization plays a vital role in the mobile robot navigation system and is a fundamental capability for the following path planning task. In an indoor environment where the global positioning system signal fails or becomes weak, the wireless sensor network (WSN) or simultaneous localization and mapping (SLAM) scheme gradually becomes a research hot spot. WSN method uses received signal strength indicator (RSSI) values to determine the position of the target signal node, however, the orientation of the target node is not clear. Besides, the distance error is large when the indoor signal receives interference. The… More >

Chang Zhao¹, Wei Sun^1,3,*, Xiaorui Zhang^2,3, Xiaozheng He⁴, Jun Zuo¹, Wei Zhao¹

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1083-1094, 2023, DOI:10.32604/csse.2023.032786 - 03 November 2022

Abstract The ORB-SLAM2 based on the constant velocity model is difficult to determine the search window of the reprojection of map points when the objects are in variable velocity motion, which leads to a false matching, with an inaccurate pose estimation or failed tracking. To address the challenge above, a new method of feature point matching is proposed in this paper, which combines the variable velocity model with the reverse optical flow method. First, the constant velocity model is extended to a new variable velocity model, and the expanded variable velocity model is used to provide… More >

Dahyeon Kim, Junho Ahn^*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1657-1671, 2023, DOI:10.32604/cmc.2023.029216 - 22 September 2022

Abstract When firefighters search inside a building that is at risk of collapse due to abandonment or disasters such as fire, they use old architectural drawings or a simple monitoring method involving a video device attached to a robot. However, using these methods, the disaster situation inside a building at risk of collapse is difficult to detect and identify. Therefore, we investigate the generation of digital maps for a disaster site to accurately analyze internal situations. In this study, a robot combined with a low-cost camera and two-dimensional light detection and ranging (2D-lidar) traverses across a… More >

Tingting Yang^1,*, Shuwen Jia¹, Ying Yu¹, Zhiyong Sui²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1691-1704, 2023, DOI:10.32604/iasc.2023.027466 - 19 July 2022

Abstract Augmented Reality (AR) tries to seamlessly integrate virtual content into the real world of the user. Ideally, the virtual content would behave exactly like real objects. This necessitates a correct and precise estimation of the user’s viewpoint (or that of a camera) with regard to the virtual content’s coordinate system. Therefore, the real-time establishment of 3-dimension (3D) maps in real scenes is particularly important for augmented reality technology. So in this paper, we integrate Simultaneous Localization and Mapping (SLAM) technology into augmented reality. Our research is to implement an augmented reality system without markers using… More >

Naigong Yu^*, Hejie Yu

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1147-1169, 2022, DOI:10.32604/cmes.2022.019430 - 14 March 2022

Abstract The entorhinal-hippocampus structure in the mammalian brain is the core area for realizing spatial cognition. However, the visual perception and loop detection methods in the current biomimetic robot navigation model still rely on traditional visual SLAM schemes and lack the process of exploring and applying biological visual methods. Based on this, we propose a map construction method that mimics the entorhinal-hippocampal cognitive mechanism of the rat brain according to the response of entorhinal cortex neurons to eye saccades in recent related studies. That is, when mammals are free to watch the scene, the entorhinal cortex… More >