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코파일럿 시스템을 위한 다중 2D LiDAR 융합기반 차량 주변 동적 장애물 추적 모듈 개발
나기인(Ki-in Na),변재민(Jaemin Byun),노명찬(Myoungchan Rho),서범수(Bumsu Seo) 한국자동차공학회 2014 한국자동차공학회 부문종합 학술대회 Vol.2014 No.5
This paper introduces the development of moving obstacles perception module using multiple 2D LiDARs. This can estimate both position and velocity of dynamic objects around vehicles. Projecting point cloud data from 2D LiDARs to range image structure, they are partitioned to particular observations with connectivity based region growing segmentation. In sequence, observations from segmentation steps are associated with the predicted tracks employing NNSF based on Kalman filter. Furthermore, the associated tracks are continuously updated, extraneous observations are generated to new tracks and missing tracks are removed. This developed module was installed on Co-Pilot system and the experiments tracking several moving obstacles at the same time were performed to show this module working.
Real-time 3D multi-pedestrian detection and tracking using 3D LiDAR point cloud for mobile robot
나기인,박병재 한국전자통신연구원 2023 ETRI Journal Vol.45 No.5
Mobile robots are used in modern life; however, object recognition is still insufficient to realize robot navigation in crowded environments. Mobile robots must rapidly and accurately recognize the movements and shapes of pedestrians to navigate safely in pedestrian-rich spaces. This study proposes real-time, accurate, three-dimensional (3D) multi-pedestrian detection and tracking using a 3D light detection and ranging (LiDAR) point cloud in crowded environments. The pedestrian detection quickly segments a sparse 3D point cloud into individual pedestrians using a lightweight convolutional autoencoder and connected-component algorithm. The multi-pedestrian tracking identifies the same pedestrians considering motion and appearance cues in continuing frames. In addition, it estimates pedestrians' dynamic movements with various patterns by adaptively mixing heterogeneous motion models. We evaluate the computational speed and accuracy of each module using the KITTI dataset. We demonstrate that our integrated system, which rapidly and accurately recognizes pedestrian movement and appearance using a sparse 3D LiDAR, is applicable for robot navigation in crowded spaces.
자율 주행 차량의 레이저 기반 환경인식 모듈 설계 및 데이터 수집 시스템 구축
나기인(Ki-In Na),변재민(Jaemin Byun),노명찬(Myoungchan Roh),손주찬(Joochan Sohn),서범수(Bumsoo Seo),김성훈(Sunghoon Kim) 한국자동차공학회 2013 한국자동차공학회 부문종합 학술대회 Vol.2013 No.5
Architecture of the environmental perception module has been designed and specifically, the LiDAR based obstacle perception module has been designed and described with applicable algorithms. Moreover, the data logging system has been developed by vehicle, LiDAR and ROS packages for testing perception algorithms. The developed data logging system has been tested around ETRI and the logged data have been played back.
Interface Application of a Virtual Assistant Agent in an Immersive Virtual Environment
Giri Na(나기리),Jinmo Kim(김진모) 한국컴퓨터그래픽스학회 2024 컴퓨터그래픽스학회논문지 Vol.30 No.1
본 연구는 혼합현실과 가상현실을 포함하는 몰입형 가상환경에서 OpenAI의 ChatGPT를 활용한 가상 보조 에이전트의 인터페이스 응용에 관한 새로운 방법을 제안한다. 제안하는 응용 방법은 사용자의 질의에 응답하는 정보 에이전트와 사용자의 요구에 맞춰 가상 객체, 환경 등을 제어하는 제어 에이전트로 구성된다. 이를 위해, Unity 3D 엔진, OpenAI, 그리고 가상현실과 혼합현실 사용자 참여를 위한 패키지 및 개발 도구를 통합하는 개발환경을 설정한다. 그리고 음성 입력으로부터 질문 쿼리에서 답변 쿼리, 또는 제어 요구 쿼리에서 제어 스크립트로 생성으로 연결되는 작업 흐름을 설정한다. 이를 기반으로 혼합현실, 가상현실 체험 환경을 직접 제작하고 에이전트의 성능 확인을 위한 실험을 정보 에이전트의 반응 시간, 제어 에이전트의 정확도로 나누어 진행하였다. 결과적으로 제안하는 인터페이스 응용을 통해 사용자 친화적이고 단순하고 반복적인 작업에서의 효율을 높이는데 유용할 수 있음을 확인하였다. 우리는 새롭게 제안하는 인터페이스를 통해 몰입형 가상환경에서 인터페이스로의 응용에 관한 새로운 방향성을 제시하고 발견된 문제점과 현재까지의 한계점을 분명히 밝힌다. In immersive virtual environments including mixed reality (MR) and virtual reality (VR), avatars or agents, which are virtual humans, are being studied and applied in various ways as factors that increase users social presence. Recently, studies are being conducted to apply generative AI as an agent to improve user learning effects or suggest a collaborative environment in an immersive virtual environment. This study proposes a novel method for interface application of a virtual assistant agent (VAA) using OpenAI’s ChatGPT in an immersive virtual environment including VR and MR. The proposed method consists of an information agent that responds to user queries and a control agent that controls virtual objects and environments according to user needs. We set up a development environment that integrates the Unity 3D engine, OpenAI, and packages and development tools for user participation in MR and VR. Additionally, we set up a workflow that leads from voice input to the creation of a question query to an answer query, or a control request query to a control script. Based on this, MR and VR experience environments were produced, and experiments to confirm the performance of VAA were divided into response time of information agent and accuracy of control agent. It was confirmed that the interface application of the proposed VAA can increase efficiency in simple and repetitive tasks along with user-friendly features. We present a novel direction for the interface application of an immersive virtual environment through the proposed VAA and clarify the discovered problems and limitations so far.
신호철,나기인,장지호,엄태영 한국전자통신연구원 2022 ETRI Journal Vol.44 No.2
Smart cities are expected to provide residents with convenience via various agents such as CCTV, delivery robots, security robots, and unmanned shuttles. Environmental data collected by various agents can be used for various purposes, including advertising and security monitoring. This study suggests a surveillance map data framework for efficient and integrated multimodal data representation from multi-agents. The suggested surveillance map is a multilayered global information grid, which is integrated from the multimodal data of each agent. To confirm this, we collected surveillance map data for 4 months, and the behavior patterns of humans and vehicles, distribution changes of elevation, and temperature were analyzed. Moreover, we represent an anomaly detection algorithm based on a surveillance map for security service. A two-stage anomaly detection algorithm for unusual situations was developed. With this, abnormal situations such as unusual crowds and pedestrians, vehicle movement, unusual objects, and temperature change were detected. Because the surveillance map enables efficient and integrated processing of large multimodal data from a multi-agent, the suggested data framework can be used for various applications in the smart city.