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진용식,이민호,Jin, Yongsik,Lee, Minho 대한임베디드공학회 2017 대한임베디드공학회논문지 Vol.12 No.1
We propose a face recognition and notification system that can transform visual face information into tactile signals in order to help visually impaired people. The proposed system consists of a glasses type camera, a mobile computer and an electronic cane. The glasses type camera captures the frontal view of the user, and sends this image to mobile computer. The mobile computer starts to search for human's face in the image when obstacles are detected by ultrasonic sensors. In a case that human's face is detected, the mobile computer identifies detected face. At this time, Adaboost and compressive sensing are used as a detector and a classifier, respectively. After the identification procedures of the detected face, the identified face information is sent to controller attached to a cane using a Bluetooth communication. The controller generates motor control signals using Pulse Width Modulation (PWM) according to the recognized face labels. The vibration motor generates vibration patterns to inform the visually impaired person of the face recognition result. The experimental results of face recognition and notification system show that proposed system is helpful for visually impaired people by providing person identification results in front of him/her.
휴머노이드 로봇의 거리 추정능력과 행동 개선을 위한 자율학습 알고리즘
진용식(Yongsik Jin),이민호(Minho Lee) 대한전자공학회 2016 대한전자공학회 학술대회 Vol.2016 No.11
In this paper, we propose a new action and perception cycle learning framework for improving action and perception simultaneously. In the leaning of depth estimation, the sensory invariance driven action is used to provide useful sensory data to a robot. At this time, object size information is used as a clue of target distance, and gives suitable timing for depth estimation learning. By using improved depth estimation, the robot can perceive current spatial state in surrounding environment more accurately. Thus, the action generation of robot can be improved. The proposed learning framework is implemented in humanoid robot (Nao) which is additionally mounted two cameras. Experimental results shows that the proposed learning framework can improve depth estimation and action generation performance simultaneously.
[자율이동체 정보처리] 다중 센서를 가지는 상태추정기 기반의 자율 이동로봇 추적제어 시스템 구현
진용식(Yongsik Jin),한승용(Seungyong Han),이상문(Sangmoon Lee) 대한전기학회 2019 전기학회논문지 Vol.68 No.5
In this paper, we propose a tracking control method for autonomous mobile robot based on state estimation with multi-sensor. The proposed system consists of a camera and encoder to measure the accurate position and orientation of a robot. In order to fuse data obtained from different sensors, we designed a state estimator with multi-rate sampled-data. The performance of the tracking control is guaranteed by the explicit model predictive control method which is employed for real-time implementation. For autonomous navigation, we implemented camera based sign recognition, obstacle location determination, and path generation algorithm using rider data. The proposed autonomous tracking control system for mobile robot is developed in the embedded environment based on the robot operating system (ROS). Virtual simulations and real experiments are performed to show the effectiveness and validity of the proposed method.
웨어러블 스마트 헬스케어를 위한 광용적맥파 기반 실시간 혈압 추정 연구
김민성(Kim Minseong),진용식(Jin Yongsik),김규형(Kim Kyu Hyung) 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.6
본 논문에서는 기존의 일회성 혈압측정 방식의 단점을 보완하고자 광용적맥파 기반의 무구속 커프리스(Cuffless)방식 실시간 연속 혈압 추정 알고리즘을 구현하였다. 또한 선형회귀 기반의 혈압 추정 알고리즘에서 광용적맥파의 각 특징점 별 혈압 추정 성능을 비교하였다.