To address issues such as low visual SLAM (Simultaneous Localization and Mapping) positioning accuracy and poor map construction robustness caused by light variations, foliage occlusion, and texture repetition in unstructured orchard environments, th...
Aiming to address the problems of fewer related studies on autonomous navigation algorithms based on multi-sensor fusion in complex scenarios in pastures, lower degrees of fusion, and insufficient cruising accuracy of the operation path in complex ou...
This study aimed to develop a real-time localization system for an AMR (autonomous mobile robot), which utilizes the Robot Operating System (ROS) Noetic version in the Ubuntu 20.04 operating system. RTAB-MAP (Real-Time Appearance-Based Mapping) is em...
In urban underground projects, such as urban drainage systems, the real-time acquisition and generation of 3D models of pipes can provide an important foundation for pipe safety inspection and maintenance. The simultaneous localization and mapping (S...
The present work proposes a method to characterize, calibrate, and compare, any 2D SLAM algorithm, providing strong statistical evidence, based on descriptive and inferential statistics to bring confidence levels about overall behavior of the algorit...
A kind of multi feature points matching algorithm fusing local geometric constraints is proposed for the purpose of quickly loop closing detection in RGB-D Simultaneous Localization and Mapping (SLAM). The visual feature is encoded with BRAND (binary...
The autonomous positioning of tunneling equipment is the key to intellectualization and robotization of a tunneling face. In this paper, a method based on simultaneous localization and mapping (SLAM) to estimate the body pose of a roadheader and buil...
Recent advancements in deep learning techniques have accelerated the growth of robotic vision systems. One way this technology can be applied is to use a mobile robot to automatically generate a 3D map and identify objects within it. This paper addre...
This research presents a comprehensive comparative analysis of SLAM algorithms and Deep Neural Network (DNN)-based Behavior Cloning (BC) navigation in outdoor agricultural environments. The study categorizes SLAM algorithms into laser-based and visio...
This paper presents an enhanced Simultaneous Localization and Mapping (SLAM) framework for mobile robot navigation. It integrates RGB-D cameras and 2D LiDAR sensors to improve both mapping accuracy and localization efficiency. We propose a data fusio...
The fast evolution in computational and sensor technologies brings previously niche solutions to a wider userbase. As such, 3D reconstruction technologies are reaching new use-cases in scientific and everyday areas where they were not present before....
In this paper, we present the exploration of indoor positioning technologies for UAVs, as well as navigation techniques for path planning and obstacle avoidance. The objective was to perform warehouse inventory tasks, using a drone to search for barc...
The utilization of stereo cameras in robotic applications is presented in this paper. The use of a stereo depth sensor is a principal step in robotics applications, since it is the first step in sequences of robotic actions where the intent is to det...
In industrial environments, providing intuitive spatial information via 3D maps is essential for maximizing the efficiency of teleoperation. However, existing SLAM algorithms generating 3D maps predominantly focus on improving robot localization accu...
Visual simultaneous localization and mapping is a widely used technology for mobile robots to carry out precise positioning in the environment of GNSS technology failure. However, as the robot moves around indoors, its position accuracy will graduall...