A New Roadside Detection Method Based on Obstacle Detection

2012 ◽  
Vol 429 ◽  
pp. 324-328
Author(s):  
Chun He Yu ◽  
Dan Ping Zhang ◽  
Rui Guo
Keyword(s):  
Mobile Robot ◽  
High Stability ◽  
Detection Method ◽  
Detection Algorithm ◽  
Obstacle Detection ◽  
Laser Radar ◽  
The Road ◽  
Straight Lines

In order to provide road information for outdoor mobile robot in a complicated environment, a new roadside detection method is proposed based on obstacle detection by applying a four-layer laser radar LD_ML. Because roadside obstacles distribute alone a road, theirs fitting straight lines are parallel to the road. The roadsides detection algorithm includes four steps: first, judge if there are obstacles along roadside or not; second, extract obstacles which belong to roadsides; third, build fitting straight lines through the roadside obstacles; at last, in order to obtain steady and precise roadsides, a EKF method is performed to track the roadsides. The results of experiment have testified the road roadsides detection algorithm has high stability and reliability.

Smooth Track-Keeping and Real Time Obstacle Detection Algorithm and its PID Controller Implementation for an Automated Wheeled Line Following Robot

2011 ◽  
Vol 201-203 ◽  
pp. 1966-1971 ◽  
Author(s):  
Mohammad Rokonuzzaman ◽  
Shah Muhammad Ferdous ◽  
Enaiyat Ghani Ovy ◽  
Md. Ashraful Hoque
Keyword(s):  
Mobile Robot ◽  
Pid Controller ◽  
Material Handling ◽  
Moving Objects ◽  
Detection Algorithm ◽  
Acute Angle ◽  
Obstacle Detection ◽  
Response Position ◽  
Wavy Line ◽  
Line Following

Line following automated robots is extensively used in industries for smooth running of production. This paper presents a simple and effective solution for path tracking problem for a wheeled automated mobile robot which can be used for material handling in industries. A PID controller has been used for controlling the robot which is capable of moving safely by smooth track-keeping in partially structured environment without any collision with static or moving objects. The purpose of the project is to build a mobile robot which will provide fast, smooth, accurate and safe movement in any given line or track. A straight or wavy line would be simple to follow whereas aT-junction, 90 degree bends, acute angle bends and grid junctions would be difficult to navigate through. This is due to the physical kinematics constraints which are limited to motor response, position and turning radius of the robot. A line sensor configuration has been proposed to improve the navigation reliability of the mobile robot which uses differential drive system. A dynamic algorithm has been developed for detecting and following a specified line which ensures the reliable and safe movement of the robot.

ROAD RECOGNITION TECHNOLOGY OF AGRICULTURAL NAVIGATION ROBOT BASED ON ROAD EDGE MOVEMENT OBSTACLE DETECTION ALGORITHM

2020 ◽  
Vol 61 (2) ◽  
pp. 281-292 ◽  
Author(s):  
Na Yu ◽  
Qing Wang ◽  
Shichao Cao
Keyword(s):  
Motion Capture ◽  
Target Location ◽  
Detection Algorithm ◽  
Obstacle Detection ◽  
Working Environment ◽  
Outdoor Environment ◽  
Analysis Model ◽  
Agricultural Robots ◽  
The Road ◽  
The Mean

In order to recognize the road effectively, agricultural robots mainly rely on the tracking and detection data of road obstacles. Traditional obstacle detection mainly studies how to use multiple fusion methods such as vision and laser to analyse structured and simplified indoor scenes. The working environment of agricultural robots is a typical unstructured outdoor environment. Therefore, based on the environmental characteristics of agricultural robot navigation, the mean displacement algorithm is introduced to detect and study the obstacles aiming at the road edge. After explaining the advantages and principle flow of the mean displacement algorithm to effectively realize motion capture, the feasibility of target location and tracking research is discussed. After that, the bottom data acquisition and analysis model is constructed based on the road navigation data of agricultural robots. To capture the movement obstacles of road edge and build the foundation of road recognition technology. In order to improve the effectiveness of motion obstacle capture and detection, a moving target detection algorithm is proposed to optimize and update the mean displacement algorithm, and constructs a feature-oriented hybrid algorithm motion capture model. The simulation results indicate that the proposed optimization model can effectively improve the tracking efficiency of non-rigid targets in outdoor environment, and the number of evaluation iterations can reach 3.5621 times per frame, which shows that the research has good theoretical and practical value.

A Study on Computational Time Reduction of Road Obstacle Detection by Parallel Image Processor

2014 ◽  
Vol 18 (5) ◽  
pp. 849-855 ◽  
Author(s):  
Yutaro Okamoto ◽  
◽  
Chinthaka Premachandra ◽  
Kiyotaka Kato
Keyword(s):  
Detection Algorithm ◽  
Obstacle Detection ◽  
Transport Systems ◽  
Computational Time ◽  
Intelligent Transport Systems ◽  
Image Processor ◽  
Intelligent Transport ◽  
The Road ◽  
Parallel Image ◽  
Time Reduction

Automatic road obstacle detection is one of the significant problem in Intelligent Transport Systems (ITS). Many studies have been conducted for this interesting problem by using on-vehicle cameras. However, those methods still needs a dozens ofmillisecondsfor image processing. To develop the quick obstacle avoidance devices for vehicles, further computational time reduction is expected. Furthermore, regarding the applications, compact hardware is also expected for implementation. Thus, we study on computational time reduction of the road obstacle detection by using a small-type parallel image processor. Here, computational time is reduced by developing an obstacle detection algorithm which is appropriated to parallel processing concept of that hardware. According to the experimental evaluation of the new proposal, we could limit computational time for eleven milliseconds with a good obstacle detection performance.

scholarly journals A Study on Building a “Real-Time Vehicle Accident and Road Obstacle Notification Model” Using AI CCTV

2021 ◽  
Vol 11 (17) ◽  
pp. 8210
Author(s):  
Chaeyoung Lee ◽  
Hyomin Kim ◽  
Sejong Oh ◽  
Illchul Doo
Keyword(s):  
Deep Learning ◽  
Traffic Safety ◽  
Research Direction ◽  
Detection Algorithm ◽  
Obstacle Detection ◽  
Video Data ◽  
Future Research ◽  
The Road ◽  
Detection Model ◽  
On The Road

This research produced a model that detects abnormal phenomena on the road, based on deep learning, and proposes a service that can prevent accidents because of other cars and traffic congestion. After extracting accident images based on traffic accident video data by using FFmpeg for model production, car collision types are classified, and only the head-on collision types are processed by using the deep learning object-detection algorithm YOLO (You Only Look Once). Using the car accident detection model that we built and the provided road obstacle-detection model, we programmed, for when the model detects abnormalities on the road, warning notification and photos that captures the accidents or obstacles, which are then transferred to the application. The proposed service was verified through application notification simulations and virtual experiments using CCTVs in Daegu, Busan, and Gwangju. By providing services, the goal is to improve traffic safety and achieve the development of a self-driving vehicle sector. As a future research direction, it is suggested that an efficient CCTV control system be introduced for the transportation environment.

A REAL-TIME DETECTION ALGORITHM FOR VISION-BASED PEDESTRIAN PROTECTION

2008 ◽  
Vol 05 (01) ◽  
pp. 11-30 ◽  
Author(s):  
GUANGLIN MA ◽  
SU-BIRM PARK ◽  
ALEXANDER IOFFE ◽  
STEFAN MÜLLER-SCHNEIDERS ◽  
ANTON KUMMERT
Keyword(s):  
Real Time ◽  
Pedestrian Detection ◽  
Ground Plane ◽  
Detection Algorithm ◽  
Obstacle Detection ◽  
Low Contrast ◽  
The Road ◽  
Novel Approach ◽  
Real Time Detection ◽  
Flat Ground

This paper discusses the robust, real-time detection of stationary and moving pedestrians utilizing a single car-mounted monochrome camera. First, the system detects potential pedestrians above the ground plane by combining conventional Inverse Perspective Mapping (IPM)-based obstacle detection with the vertical 1D profile evaluation of the IPM detection result. Usage of the vertical profile increases the robustness of detection in low-contrast images as well as the detection of distant pedestrians significantly. A fast digital image stabilization algorithm is used to compensate for erroneous detections whenever the flat ground plane assumption is an inaccurate model of the road surface. Finally, a low-level pedestrian-oriented segmentation and fast symmetry search on the leg region of pedestrians is also presented. A novel approach termed Pedestrian Detection Strip (PDS) is used to improve the calculation time by a factor of six compared to conventional approaches.

Research on the Lane Detection Algorithm Based on Zoning Hough Transformation

2012 ◽  
Vol 490-495 ◽  
pp. 1862-1866 ◽  
Author(s):  
Chao Fan ◽  
Li Long Hou ◽  
Shuai Di ◽  
Jing Bo Xu
Keyword(s):  
Hough Transform ◽  
Ambient Noise ◽  
Detection Method ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Dominant Position ◽  
Hough Transformation ◽  
The Road ◽  
Lane Marking ◽  
Sobel Operators

In order to improve the adaptability of the lane detection algorithm under complex conditions such as damaged lane lines, covered shadow, insufficient light, the rainy day etc. Lane detection algorithm based on Zoning Hough Transform is proposed in this paper. The road images are processed by the improved ±45° Sobel operators and the two-dimension Otsu algorithm. To eliminate the interference of ambient noise, highlight the dominant position of the lane, the Zoning Hough Transform is used, which can obtain the parameters and identify the lane accurately. The experiment results show the lane detection method can extract the lane marking parameters accurately even for which are badly broken, and covered by shadow or rainwater completely, and the algorithm has good robustness.

Consecutive Scanning Scheme: Application to Localization and Dynamic Obstacle Detection for a Mobile Robot

2002 ◽  
Author(s):  
Jae-Yong Lee ◽  
Sooyong Lee
Keyword(s):  
Mobile Robot ◽  
Detection Algorithm ◽  
Obstacle Detection ◽  
Data Sets ◽  
Data Set ◽  
Characteristic Points ◽  
Scanning Scheme ◽  
Mobile Robot Localization ◽  
Robot Configuration ◽  
Dynamic Obstacle

This paper presents the mobile robot localization and obstacle detection algorithm using the consecutive range sensor scanning scheme. For known environment, a mobile robot scans the environment using which can rotate 360°. The environment is rebuild using characteristic points which means nodes of two adjacent walls, and obstacle is detected by comparing characteristic points of both original environment and scanned data set. If scanning is done densely for a certain position, inaccuracy of sensor can be overcome to some extent. It is very useful algorithm in detecting the moving obstacle. By comparing two data sets, the movement of an obstacle can be picked out. Furthermore, consecutive scanning data set provides additional localization information so that we can get the robot configuration more precisely.

Development and Application of Quality Control System for Highway Subgrade Construction

2019 ◽  
Vol 2 (5) ◽  
Author(s):  
Tong Wang
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Detection Method ◽  
System Development ◽  
Effective Control ◽  
Construction Process ◽  
Development Mode ◽  
The Road ◽  
Whole Process

The compaction quality of the subgrade is directly related to the service life of the road. Effective control of the subgrade construction process is the key to ensuring the compaction quality of the subgrade. Therefore, real-time, comprehensive, rapid and accurate prediction of construction compaction quality through informatization detection method is an important guarantee for speeding up construction progress and ensuring subgrade compaction quality. Based on the function of the system, this paper puts forward the principle of system development and the development mode used in system development, and displays the development system in real-time to achieve the whole process control of subgrade construction quality.

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