An Effective Vision-based Self-Navigation System for Autonomous Indoor Vehicle

국문 초록 (Abstract)

스마트 시티는 스마트 빌딩의 개발에서부터 시작해 인간 삶의 질 향상을 목표로 발전해 나가고 있다. 특히, 자율주행 실내 로봇은 스마트 빌딩의 운영을 위한 혁신적인 요소가 될 것으로 예측된다. 이를 실현하기 위해 본 논문에서는 영상 기반의 센싱 및 하드웨어 제어 메커니즘을 활용한 자가 탐색형 이동 로봇을 개발하였다. 먼저, 복도의 양 끝 가장자리를 슬라이딩 윈도우 라인 검출 방법을 이용하여 인식하게 되면, 방향 가중치 알고리즘을 통해 복도의 가운데를 인식해 로봇의 방향을 예측할 수 있게 된다. 본 제안 기법을 실제 로봇에 제안 탐색 기법을 적용하여 다양한 실험을 진행한 결과 실시간으로 자율주행로봇이 장애물 회피가 가능함을 보였다.

다국어 초록 (Multilingual Abstract)

The advancements in a smart city have paved a way towards the development of smart buildings with an aim to improve the resident environment and quality of life. Apparently, autonomous indoor robots are considered as a critical factor for the operation of smart buildings. In the present work, we have developed a self-navigation system for mobile robots that utilize vision-based sensing and hardware control mechanism. First, sliding window line detection method is used to find the polynomial fit to two lines of the hallway, and then direction weight estimation algorithm predicts the direction of the robot with respect to the center of the two estimated lines. The results relying on real robot experiments show that the proposed navigation system can enhance the in-front obstacle for the real-time task in autonomous indoor robots.

목차 (Table of Contents)

• 요약
• Abstract
• 1. Introduction
• 2. The Overall Navigation System
• 3. The Proposed Algorithm
• 4. Experiments
• 5. Conclusions
• References

참고문헌 (Reference)

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8 "Hough Transform"

9 G. Tsai, "Dynamic visual understanding of the local environment for an indoor navigating robot" 4695-4701, 2012

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12 P. Mukhopadhyay, "A survey of Hough Transform" 48 (48): 993-1010, 2015