음성인식과 딥러닝 기반 객체 인식 기술이 접목된 모바일 매니퓰레이터 통합 시스템
Integrated System of Mobile Manipulator with Speech Recognition and Deep Learning-based Object Detection
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Most of the initial forms of cooperative robots were intended to repeat simple tasks in a given space. So, they showed no significant difference from industrial robots. However, research for improving worker’s productivity and supplementing human’s limited working hours is expanding. Also, there have been active attempts to use it as a service robot by applying AI technology. In line with these social changes, we produced a mobile manipulator that can improve the worker’s efficiency and completely replace one person. First, we combined cooperative robot with mobile robot. Second, we applied speech recognition technology and deep learning based object detection. Finally, we integrated all the systems by ROS (robot operating system). This system can communicate with workers by voice and drive autonomously and perform the Pick & Place task.
Abstract
Most of the initial forms of cooperative robots were intended to repeat simple tasks in a given space. So, they showed no significant difference from industrial robots. However, research for improving worker’s productivity and supplementing human’s limited working hours is expanding. Also, there have been active attempts to use it as a service robot by applying AI technology. In line with these social changes, we produced a mobile manipulator that can improve the worker’s efficiency and completely replace one person. First, we combined cooperative robot with mobile robot. Second, we applied speech recognition technology and deep learning based object detection. Finally, we integrated all the systems by ROS (robot operating system). This system can communicate with workers by voice and drive autonomously and perform the Pick & Place task.
참고문헌 (9)
- "Collaborative robot for manufacturing"[URL]
- "ICT Spot Issue (2017-06) The Next Big Thing, Trend and implication of Service Robot"[URL]
- D. Hu, "Deep ChArUco : Dark ChArUco Marker Pose Estimation", IEEE, 2019, 8436~8444
- J. Denavit, "A Kinematic Notation for Lower-Pair Mechanisms Based on Matrices", Journal of Applied Mechanics, 22(2), pp.215~221 (1955), ASME International[DOI]
- K. He, "Mask R-CNN", IEEE International Conference on Computer Vision (ICCV), pp.2961~2969 (2017)
- "Center of mass – Wikipedia"[URL]
- 최승주, "음성 인식 오픈 API의 음성 인식 정확도 비교 분석", 예술인문사회 융합 멀티미디어 논문지, 7(8), pp.411~418 (2017), 사단법인 인문사회과학기술융합학회[DOI]
- F. Spenrath, "Gripping Point Determination for Bin Picking Using Heuristic Search", 10th CIRP Conference on Intelligent Computation in Manufacturing Engineering-CIRP ICME '16, pp.606~611 (2017)