Research on Mobile Robot Positioning and Navigation System Based on Multi-sensor Fusion

He, Cheng; Ma, Renjie; Qu, Huaying; Gu, Runwei

doi:10.1088/1742-6596/1684/1/012011

Cited by 3 publications

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The binocular stereo vision system consists of two left and right cameras of the same specification [22], the cameras remain on the same plane, which ensures that the horizontal axes of the left and right cameras system are on the same line and parallel to the imaging plane [23]. The ( 1) is used to calculate the distance 𝐷 between the object 𝑃 and the two cameras, in which (x L , x R ) represent the coordinates of the corresponding pixel in the left and right image, and 𝑑 is the point 𝑃 disparity.…”

Section: Overview Of Stereo Vision System 21 Stereo Vision Algorithmmentioning

confidence: 99%

Parallel field programmable gate array implementation of the sum of absolute differences algorithm used in the stereoscopic system

et al. 2022

View full text Add to dashboard Cite

Stereo vision is a popular method for an artificial vision-based environment perception system used in various applications such as intelligent transportation. With two cameras, the disparity map is calculated to find the distance and depth of objects in front of a moving vehicle. The key element of the stereoscopic system is based on the sum of absolute differences (SAD) algorithm, which is the most repeated operation in the stereo matching subsystem; however, this algorithm requires a very intensive processing time, statistical analysis show that the SAD block can consume more than 80% of the overall processing time of the algorithm. In this paper we propose a highly efficient hardware architecture of the SAD algorithm for real time stereo matching, the proposed architecture is established by a hierarchical parallel architecture of the SAD block, and verified by simulation and successfully implemented in Cyclone IV field programmable gate array (FPGA), it provides a significant reduction of processing time and the performance of the stereo imaging system is able to achieve 30 frames per second of 640×480 resolution color images.

show abstract

Section: Overview Of Stereo Vision System 21 Stereo Vision Algorithmmentioning

confidence: 99%

Parallel field programmable gate array implementation of the sum of absolute differences algorithm used in the stereoscopic system

et al. 2022

View full text Add to dashboard Cite

show abstract

“…With the rapid development of robots, artificial intelligence, and multi-sensor fusion perception technologies, the perception capabilities of mobile robots have greatly expanded, resulting in more convenient, intelligent, and safe equipment, such as unmanned vehicles and aerial drones [1,2]. Similar to the "eyes" of robots, vision sensors play an important role in environmental perception.…”

Section: Introductionmentioning

confidence: 99%

Automatic Targetless Monocular Camera and LiDAR External Parameter Calibration Method for Mobile Robots

Yu,

Fan,

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

With the continuous development and popularization of sensor-fusion technology for mobile robots, the application of camera and light detection and ranging (LiDAR) fusion perception has become particularly important. Moreover, the calibration of extrinsic parameters between the camera and LiDAR is a crucial prerequisite for fusion. Although traditional target-based calibration methods have been widely adopted, their cumbersome operation and high costs necessitate the development of more efficient and flexible calibration methods. To address this problem, this study proposed a two-stage calibration method based on motion and edge matching. In the first stage, the preliminary estimation of the extrinsic parameters between the camera and LiDAR was performed by matching visual odometry and LiDAR odometry using a hand–eye target method. In the second stage, the calibration results from the first stage were further refined by matching the image edges and discontinuous depth point clouds. The calibration system was then tested in both simulated and actual environments. The experimental results showed that this method, which did not require specially structured targets, could achieve highly flexible and robust automated calibration. Compared to other advanced methods, the accuracy of the proposed method was higher.

show abstract

Mobile Robot Localization and Environment Perception Technology Based on Multi-Sensor Information Fusion

李

2024

AIRR

View full text Add to dashboard Cite

Research on Mobile Robot Positioning and Navigation System Based on Multi-sensor Fusion

Cited by 3 publications

References 3 publications

Parallel field programmable gate array implementation of the sum of absolute differences algorithm used in the stereoscopic system

Parallel field programmable gate array implementation of the sum of absolute differences algorithm used in the stereoscopic system

Automatic Targetless Monocular Camera and LiDAR External Parameter Calibration Method for Mobile Robots

Mobile Robot Localization and Environment Perception Technology Based on Multi-Sensor Information Fusion

Contact Info

Product

Resources

About