Research on Real-Time Laser Range Finding System

2013 ◽  
Vol 347-350 ◽  
pp. 1053-1058
Author(s):  
Fang Xiu Jia ◽  
Ji Yan Yu ◽  
Zhen Liang Ding ◽  
Feng Yuan

Phase shift laser range finder, as a large-scale, high-precision measurement method, is widely used in industrial and military fields. The traditional laser range finder can not meet the need of real-time, high resolution measurement because of its low anti-jamming capability and time-consuming measurement. Owing to this, multi-channel transmitting and receiving system for phase shift laser range finder based on parallel DSP was designed. Multi-frequency modulation laser can be transmitted and received at the same time, improving the measurement speed and avoiding the wrong data fusion because of target moving. The distance was got by measuring the phase difference between the measurement signal and reference signal, and the Doppler velocity of the target is got by measuring the measurement signals frequency, The measurement signals reference signals were acquired by parallel AD convertors, the phase difference between them was calculated adopting all-phase FFT(apFFT). A new frequency correction method was proposed according to the amplitude spectrum acquired by apFFT, Amplitude spectrum is expanded into Taylor series and the correction value of frequency is calculated by relationship of spectrum lines. Monte Carlo simulation results proved that the new frequency correction method had higher resolution and better stability than Rife method and centro-baric method. The experiments is implemented on a precision guide of 3m-long, on the condition that the sampling frequency of AD converter is 937.5KHz, the apFFT transform point number is 4096, distance and velocity results can be obtained each 10ms, experiments prove that the distance measurement standard deviation better than 0.09mm and the velocity measurement standard deviation better than 0.022m/s are obtained. The system can meet the need of high accuracy ,real-time distance measurement of moving target.

Author(s):  
Dmitry A. Kolchaev ◽  
Yevgeniy R. Muratov ◽  
Michael B. Nikiforov ◽  
Sergei V. Orlov

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3694
Author(s):  
Mohammed A. H. Ali ◽  
Musa Mailah ◽  
Waheb A. Jabbar ◽  
Khaja Moiduddin ◽  
Wadea Ameen ◽  
...  

A real-time roundabout detection and navigation system for smart vehicles and cities using laser simulator–fuzzy logic algorithms and sensor fusion in a road environment is presented in this paper. A wheeled mobile robot (WMR) is supposed to navigate autonomously on the road in real-time and reach a predefined goal while discovering and detecting the road roundabout. A complete modeling and path planning of the road’s roundabout intersection was derived to enable the WMR to navigate autonomously in indoor and outdoor terrains. A new algorithm, called Laser Simulator, has been introduced to detect various entities in a road roundabout setting, which is later integrated with fuzzy logic algorithm for making the right decision about the existence of the roundabout. The sensor fusion process involving the use of a Wi-Fi camera, laser range finder, and odometry was implemented to generate the robot’s path planning and localization within the road environment. The local maps were built using the extracted data from the camera and laser range finder to estimate the road parameters such as road width, side curbs, and roundabout center, all in two-dimensional space. The path generation algorithm was fully derived within the local maps and tested with a WMR platform in real-time.


2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Abdul Hadi Abd Rahman ◽  
Hairi Zamzuri ◽  
Saiful Amri Mazlan ◽  
Mohd Azizi Abdul Rahman ◽  
Yoshio Yamamoto ◽  
...  

Real time pedestrian tracking could be one of the important features for autonomous navigation. Laser Range Finder (LRF) produces accurate pedestrian data but a problem occurs when a pedestrian is represented by multiple clusters which affect the overall tracking process. Multiple Hypothesis Tracking (MHT) is a proven method to solve tracking problem but suffers a large computational cost. In this paper, a multilevel clustering of LRF data is proposed to improve the accuracy of a tracking system by adding another clustering level after the feature extraction process. A Dynamic Track Management (DTM) is introduced in MHT with multiple motion models to perform a track creation, association, and deletion. The experimental results from real time implementation prove that the proposed multiclustering is capable of producing a better performance with less computational complexity for a track management process. The proposed Dynamic Track Management is able to solve the tracking problem with lower computation time when dealing with occlusion, crossed track, and track deletion.


Author(s):  
Soo-Yong Jung ◽  
Seong Ro Lee ◽  
Min A Jeong ◽  
Chang-Soo Park

2014 ◽  
Vol 670-671 ◽  
pp. 1342-1345 ◽  
Author(s):  
Li Xian Wang ◽  
Rui Jun Yan ◽  
Long Sheng

This paper presents a method to track and follow target person. A laser range finder (LRF) is used to measure highly accurate distance of objects with the range of 180 degrees. First of all, the erroneous data are excluded due to the error of LRF. Then all the raw sensor data are separated into many groups when the difference of the measuring distances of two adjacent laser points are beyond a limited value. For each group, the width is calculated, and it is considered as human legs if the defined conditions are satisfied. Finally, a real-time human following experiment with a SICK LRF and PIONEER mobile robot is done to validate our proposed method.


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