检索结果-内蒙古大学图书馆

Improvement of Localization Algorithm for Indoor and Outdoor Navigation of autonomous Robots

Journal of Institute of Control, robotics and Systems 2025年第5期31卷 502-509页

作者： Cho, Joonhyuk Kim, Bongsang Moon, Heechang Industrial Convergence Interdepartmental Program Autonomous Vehicle Intelligent Robotics The Graduate School of Hongik University Korea Republic of Mechanical & System Design Engineering Hongik University Korea Republic of

Location estimation for waypoint-based autonomous driving robots primarily relies on SLAM (Simultaneous Localization and Mapping) and GNSS (Global Navigation Satellite System) technologies. GNSS performs well in open areas but struggles with signal issues, while SLAM offers high accuracy in feature-rich environments but faces challenges in open spaces. This study integrates SLAM and GNSS, enabling seamless switching between systems when one encounters difficulties. The combined system ensures consistency by aligning coordinate systems and directional data. Experiments in indoor, forest, and open environments demonstrate that the switching algorithm enables stable autonomous driving in diverse conditions, effectively leveraging the strengths of both systems. © ICROS 2025.

关键词： Global positioning system

来源：评论

学校读者我要写书评

暂无评论

Merge LiDAR and High-precision Digital Map for Real-time Object Detection and GNSS Heading Calibration

引用

Journal of Institute of Control, robotics and Systems 2023年第4期29卷 301-307页

作者： Sim, Hongseok Baek, Seungbeom Lee, Jaewook Moon, Heechang Industrial Convergence Interdepartmental Program Autonomous Vehicle·Intelligent Robotics Hongik University Korea Republic of Mechanical and System Design Engineering Hongik University Korea Republic of

In this study, a method was proposed for correcting the object positioning error of light detection and ranging (LiDAR) due to the roll, pitch, and yaw data error of the inertial measurement unit sensor in the global navigation satellite system (GNSS) sensor by using a high-precision digital map. A real-time obstacle map was formed using Velodyne’s three-dimensional lines, VLP-32 and VLP-16. The high-precision digital map was then merged into the LiDAR map. The map obtained by combining LiDAR and high-precision digital maps did not match because of certain errors. To eliminate these errors, a method of fitting a map with high precision on the XY plane was established, and fittable criteria were determined. Algorithm verification was performed during actual driving, and errors were removed in real time. Various autonomous driving technologies can be developed using the sensor error data preprocessing process. Copyright© ICROS 2023.

关键词： Errors

来源：评论

学校读者我要写书评

暂无评论

Recognition of Real-time Traffic Signals Using the Algorithm Fusion of On-board Graphic Chip-based Machine Learning and Deep Learning

引用

Journal of Institute of Control, robotics and Systems 2022年第2期28卷 88-94页

作者： Lee, Jaewook Baek, Seungbeom Choi, Eunji Moon, Heechang Industrial Convergence Interdepartmental Program Autonomous Vehicle·Intelligent Robotics Hongik University Korea Republic of Mechanical and System Design Engineering Hongik University Korea Republic of

The recognition of traffic light in unmanned autonomous driving is one of the key functions. In general, to achieve this goal, deep learning and image processing technology are mainly used in autonomous driving industry. Both technologies have high recognition rates alone, but misrecognition can occur because of interference of the environment. misrecognitions are considered important problem because it may lead to big accidents. In this paper, we suggest using machine learning based on LabVIEW and deep running grounded in Python to increase recognition rate at intersection. By using both technologies, we can minimize the impact of the environment on traffic light recognition and reduce misrecognition. © ICROS 2022.

关键词： Image processing

来源：评论

学校读者我要写书评

暂无评论

Real-time Path Planning Algorithm based on Ridge Detection for Solid-State LiDAR-based autonomous Agricultural Robot

引用

Journal of Institute of Control, robotics and Systems 2022年第2期28卷 146-152页

作者： Baek, Seungbeom Kim, Bongsang Lee, Jaewook Moon, Heechang Industrial Convergence Interdepartmental Program Autonomous Vehicle·Intelligent Robotics The Graduate School of Hongik University Korea Republic of Mechanical & System Design Engineering Hongik University Korea Republic of

autonomous robots driving in agricultural environments need to create accurate routes to prevent damaging farmland. Herein, a real-time path planning algorithm based on ridge detection using the Livox Mid70 LiDAR is proposed. The field has a steep slope between the furrow and the ridge, and we find data corresponding to this slope from the lidar data. Using two Mid70 LiDARs, we collect the left and right slope data and linearly fit the slope data using the RANSAC algorithm. Finally, the driving route is obtained from the average of the two straight lines. To verify the algorithm, the steering angle needed to follow the driving path was calculated, and an autonomous driving test was conducted in the actual field environment: it was observed that the robot drove stably. Additional tests will be conducted in more rugged terrain. © ICROS 2022.

关键词： Optical radar

来源：评论

学校读者我要写书评

暂无评论

Docking Assistance System Between Trailer and Tractor Using UWB Measuring Module

引用

Journal of Institute of Control, robotics and Systems 2024年第1期30卷 59-65页

作者： Park, Jong Hak Heo, Jeong Woong Moon, Hee Chang Industrial Convergence Interdepartmental Program Autonomous Vehicle･Intelligent Robotics The Graduate School of Hongik University Korea Republic of Mechanical and System Design Engineering Hongik University Korea Republic of

Trailers, which are used to load equipment such as containers and construction materials, are towed by the power of tractors to transport the equipment. The tractor, the towing vehicle, and the trailer, the towed vehicle, are independent systems, and the tractor can combine and separate by replacing the trailer for various purposes. To dock the trailer and tractor, the tractor should be backward with the posture and position of the rear of the tractor in line with the front of the trailer. The tractor driver shall be mounted based on the driver’s cognitive judgment, with a rear-view camera and mirror to determine the matching position of the trailer. We implemented and explored a system that could determine the length of this combination of systems using UWB, a positioning system, rather than driver recognition judgment, and used it to determine the position and posture of the trailer reference tractor using a square geometric approach. © ICROS 2024.

关键词： Light trailers

来源：评论

学校读者我要写书评

暂无评论

Black ice danger area estimation and active speed control research by utilizing road condition sensor

引用

Journal of Institute of Control, robotics and Systems 2021年第11期27卷 815-823页

作者： Hwang, Daekyu Kim, Bongsang Lee, Kyuho Sim, Hongseok Moon, Heechang Industrial Convergence Interdepartmental Program Autonomous Vehicle･Intelligent Robotics The Graduate School of Hongik University Korea Republic of Mechanical & System Design Engineering Hongik University Korea Republic of

This study was performed to verify the feasibility of using a black ice danger area estimation function based on the wetness data acquired by a piezoelectric based RCS (Road Condition Sensor) through real road tests under each environment and real vehicle conditions. The techniques and system implementation are considered for the prevention of accidents caused by black ice, which primarily causes critical issues in winter every year. System detects the value of wetness on the road during (or right after) rain and snow using an RCS then can estimate the possibility of the presence of black ice on the forward path at low temperatures by combining with those obtained using the ambient temperature sensor and GIS (GPS and map). Accident avoidance and damage minimization effect is expected by securing safe driving conditions through active speed control. © ICROS 2021.

关键词： Ice

来源：评论

学校读者我要写书评

暂无评论

vehicle Speed Control in the Dilemma Zone Using Deep Learning

引用

Journal of Institute of Control, robotics and Systems 2022年第3期28卷 209-217页

作者： Lee, Jaewook Kim, Bongsang Sim, Hongseok Choi, Hyohyuk Moon, Heechang Industrial Convergence Interdepartmental Program Autonomous Vehicle･Intelligent Robotics The Graduate School of Hongik University Korea Republic of Mechanical and System Design Engineering Hongik University Korea Republic of

The dilemma zone refers to the area where a vehicle approaching an intersection as the light turns yellow must decide whether to stop or not. Often, the vehicle’s speed is too fast for it to stop at the stop line before the light turns red, but the vehicle cannot completely clear the intersection before the three-second yellow signal ends. This can lead to a major accident as the departing vehicle has not cleared the intersection before the opposite light changes to a green signal and cars on the other side of the intersection start to move. To prepare for this situation, traffic light patterns were modified using pre-trained data sets, then the traffic patterns at these lights were recorded using cameras. autonomous vehicles were introduced into these areas and their speed was controlled based on the recognized traffic light patterns. This paper explores whether deep learning algorithms can effectively control vehicle speed when autonomous vehicles face the dilemma zone. © ICROS 2022.

关键词： autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：