Underwater Localization and Mapping Based on Multi-Beam Forward Looking Sonar

Cheng, Chensheng; Wang, Can; Yang, Dianyu; Liu, Weidong; Zhang, Feihu

doi:10.3389/fnbot.2021.801956

Cited by 20 publications

(8 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Aiming at the underwater environments with low signal-to-noise power ratios (SNRs), Lee et al. [ 100 ] proposed a USBL positioning method based on deep learning. The simulation results have shown that the proposed method has positioning performance that was up to 50 times better than the conventional methods.…”

Section: Key Technologies Of the Uvmsmentioning

confidence: 99%

Underwater Robots and Key Technologies for Operation Control

Sun,

Wang,

Hui

et al. 2024

Cyborg Bionic Syst

View full text Add to dashboard Cite

Over time, the utilization of the Underwater Vehicle-Manipulator System (UVMS) has steadily increased in exploring and harnessing marine resources. However, the underwater environment poses big challenges for controlling, navigating, and communicating with UVMS. These challenges have not only spurred the continuous advancement of related technologies, but also made the development of the UVMS even more captivating. This article firstly provides a review of development status of the UVMS and discusses the current limitations and future directions, and then reviews in detail the dynamic and hydrodynamic modeling methods, and analyzes the principles, advantages, and disadvantages of various approaches. Then, we try to review 2 key technologies of operation control methods, including underwater positioning and navigation technologies and vehicle-manipulator coordinated control approaches. Finally, a reasonable prospect for the future development of UVMS is given.

show abstract

Section: Key Technologies Of the Uvmsmentioning

confidence: 99%

Underwater Robots and Key Technologies for Operation Control

Sun,

Wang,

Hui

et al. 2024

Cyborg Bionic Syst

View full text Add to dashboard Cite

show abstract

“…To speed up the computation speed of multi-sensor SLAM, researchers have conducted some work in this area. C. Cheng et al [134] fused sonar, IMUs, and DVLs into the SLAM framework and used MFLS to accelerate the processing of sonar information. They verified the performance of the positioning and mapping system in a simulated maze map environment.…”

Section: Multi-sensor Fusion Slam Localizationmentioning

confidence: 99%

A Review of Underwater Robot Localization in Confined Spaces

Wu,

Chen,

Yang

et al. 2024

JMSE

View full text Add to dashboard Cite

Underwater robots often encounter the influence of confined underwater environments during underwater exploration. These environments include underwater caves, sunken ships, submerged houses, and pipeline structures. Robot positioning in these environments is strongly disturbed, leading not only to the failure of some commonly used positioning methods but also to an increase in errors in positioning systems that normally function well in open water. In order to overcome the limitations of positioning methods in confined underwater environments, researchers have studied different underwater positioning methods and have selected suitable methods for positioning in such environments. These methods can achieve high-precision positioning without relying on assistance from other platforms and are referred to as autonomous positioning methods. Autonomous positioning methods for underwater robots mainly include SINS/DR positioning and SLAM positioning. In addition, in recent years, researchers have developed some bio-inspired autonomous positioning methods. This article introduces applicable robot positioning methods and sensors in confined underwater environments and discusses the research directions of robot positioning methods in such environments.

show abstract

“…It divides the surrounding environment into multiple grids, with each grid storing occupancy or elevation information. For typical scenarios, a two-dimensional grid map is commonly used, where the color of each grid cell represents the state of that area [24].…”

Section: Grid Mapmentioning

confidence: 99%

Cognitive Enhancement of Robot Path Planning and Environmental Perception Based on Gmapping Algorithm Optimization

Liu,

Gong,

et al. 2024

Electronics

View full text Add to dashboard Cite

In the logistics warehouse environment, the autonomous navigation and environment perception of the logistics sorting robot are two key challenges. To deal with the complex obstacles and cargo layout in a warehouse, this study focuses on improving the robot perception and navigation system to achieve efficient path planning and safe motion control. For this purpose, a scheme based on an improved Gmapping algorithm is proposed to construct a high-precision map inside a warehouse through the efficient scanning and processing of environmental data by robots. While the improved algorithm effectively integrates sensor data with robot position information to realize the real-time modeling and analysis of warehouse environments. Consequently, the precise mapping results provide a reliable navigation basis for the robot, enabling it to make intelligent path planning and obstacle avoidance decisions in unknown or dynamic environments. The experimental results show that the robot using the improved Gmapping algorithm has high accuracy and robustness in identifying obstacles and an effectively reduced navigation error, thus improving the intelligence level and efficiency of logistics operations. The improved algorithm significantly enhances obstacle detection rates, increasing them by 4.05%. Simultaneously, it successfully reduces map size accuracy errors by 1.4% and angle accuracy errors by 0.5%. Additionally, the accuracy of the robot’s travel distance improves by 2.4%, and the mapping time is reduced by nine seconds. Significant progress has been made in achieving high-precision environmental perception and intelligent navigation, providing reliable technical support and solutions for autonomous operations in logistics warehouses.

show abstract

Underwater Localization and Mapping Based on Multi-Beam Forward Looking Sonar

Cited by 20 publications

References 23 publications

Underwater Robots and Key Technologies for Operation Control

Underwater Robots and Key Technologies for Operation Control

A Review of Underwater Robot Localization in Confined Spaces

Cognitive Enhancement of Robot Path Planning and Environmental Perception Based on Gmapping Algorithm Optimization

Contact Info

Product

Resources

About