Journal of Sensor Science and Technology (센서학회지)

The Korean Sensors Society (한국센서학회)
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Realization of Object Detection Algorithm and Eight-channel LiDAR sensor for Autonomous Vehicles

자율주행자동차를 위한 8채널 LiDAR 센서 및 객체 검출 알고리즘의 구현

  • Kim, Ju-Young (Sensor Research Team, Gyeongbuk Institute of IT Convergence Industry Technology) ;
  • Woo, Seong Tak (Sensor Research Team, Gyeongbuk Institute of IT Convergence Industry Technology) ;
  • Yoo, Jong-Ho (Sensor Research Team, Gyeongbuk Institute of IT Convergence Industry Technology) ;
  • Park, Young-Bin (Sensor Research Team, Gyeongbuk Institute of IT Convergence Industry Technology) ;
  • Lee, Joong-Hee (Sensor Research Team, Gyeongbuk Institute of IT Convergence Industry Technology) ;
  • Cho, Hyun-Chang (IT Convergence Components Research Center) ;
  • Choi, Hyun-Yong (IT Convergence Components Research Center)
  • 김주영 ((재)경북IT융합산업기술원 센서연구팀) ;
  • 우승탁 ((재)경북IT융합산업기술원 센서연구팀) ;
  • 유종호 ((재)경북IT융합산업기술원 센서연구팀) ;
  • 박영빈 ((재)경북IT융합산업기술원 센서연구팀) ;
  • 이중희 ((재)경북IT융합산업기술원 센서연구팀) ;
  • 조현창 (전자부품연구원 IT융합부품연구센터) ;
  • 최현용 (전자부품연구원 IT융합부품연구센터)
  • Received : 2019.03.25
  • Accepted : 2019.05.03
  • Published : 2019.05.31
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Abstract

The LiDAR sensor, which is widely regarded as one of the most important sensors, has recently undergone active commercialization owing to the significant growth in the production of ADAS and autonomous vehicle components. The LiDAR sensor technology involves radiating a laser beam at a particular angle and acquiring a three-dimensional image by measuring the lapsed time of the laser beam that has returned after being reflected. The LiDAR sensor has been incorporated and utilized in various devices such as drones and robots. This study focuses on object detection and recognition by employing sensor fusion. Object detection and recognition can be executed as a single function by incorporating sensors capable of recognition, such as image sensors, optical sensors, and propagation sensors. However, a single sensor has limitations with respect to object detection and recognition, and such limitations can be overcome by employing multiple sensors. In this paper, the performance of an eight-channel scanning LiDAR was evaluated and an object detection algorithm based on it was implemented. Furthermore, object detection characteristics during daytime and nighttime in a real road environment were verified. Obtained experimental results corroborate that an excellent detection performance of 92.87% can be achieved.

Keywords

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Fig. 1. Schematics of 8-ch scanning LiDAR based on a rotating mirror.

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Fig. 2. Block-diagram for operating of 8-ch scanning LiDAR based on the object detection algorithm.

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Fig. 3. Photogragh of the fabricated 8-ch scanning LiDAR.

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Fig. 4. Fabricated 8-ch scanning LiDAR; (a) The motor scanning speed and (b) laser frequency.

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Fig. 5. Experimental schematic about detection distance of the fabricated 8-ch scanning LiDAR.

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Fig. 8. Object mapping results for detection target base on coordinate system.

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Fig. 9. Experimental environment picture for object detection verification base on 8-ch scanning LiDAR and algorithm.

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Fig. 10. Object detection results of the day time.

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Fig. 11. Object detection results of the night time.

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Fig. 6. (a) Experimental picture and (b) the results of reflection as the distance.

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Fig. 7. Diagram of the signal processing based on object detection algorithm.

Table 1. The specifications of our developed LiDAR and conventional LiDAR sensor.

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Table 2. The calculation formula for object recognition.

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Table 3. Object detection results base on the calculation formula.

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