The Journal of the Korea institute of electronic communication sciences (한국전자통신학회논문지)

Korea Institute of Electronic Communication Science (한국전자통신학회)
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Detection of Nearest Points without Obstacle Segmentation using Active Min-Depth Filter

Active Min-Depth Filter를 이용한 비분할 장애물 최근접 점 검출

  • Received : 2022.12.09
  • Accepted : 2023.02.17
  • Published : 2023.02.28
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Abstract

In autonomous robots, obstacle avoidance is a key feature. Potential Field is the most widely used method in this field. Such method requires real-time calculation of the nearest point of the obstacle from the robot, which involves difficulty of reliably segmenting the obstacle region from the distance sensor data profile. In this paper, Active Min-Depth Filter is introduced to obtain the nearest point of each obstacle using real-time calculation but without segmentation. Through simulations on various sensor noise environments, the robustness of the Active Min-Depth Filter could be confirmed, and successful results were obtained by applying real-world moving robots.

자율 주행 로봇에서 장애물 회피 기능은 핵심적인 것이다. 포텐셜 필드는 이 분야에 가장 많이 사용되어온 방법이다. 이것은 장애물의 최근접 점을 실시간으로 계산해야 하는데 이를 위해 거리 센서 데이터 프로파일로 부터 안정적으로 장애물 영역을 분할해야 하는 어려움이 있다. 본 논문에서는 분할 없이 각 장애물의 최근접 점을 실시간으로 구할 수 있는 Active Min-Depth Filter를 제안한다. 다양한 센서 노이즈 환경에 대한 시뮬레이션을 통해 Active Min-Depth Filter의 강인성을 확인할 수 있었고 실제 이동 로봇 적용하여 성공적인 결과를 얻었다.

Keywords

Acknowledgement

이 논문은 2021년도 정부(교육과학기술부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(No. 2021R1F1A106465212)

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