Background: Stroke patients commonly suffer from balance impairments that limit functional activities, such as walking difficulties. Robot-assisted gait training is gaining attention as an effective rehabilitation strategy for balance and gait in stroke rehabilitation. Objects: The purpose of this study was to investigate the effects of progressive velocity robot-assisted gait training (PRG) on balance and gait abilities in stroke patients. Methods: All subjects were randomly divided into three groups: PRG (n = 12); comfortable speed robot-assisted gait training (CRG) (n = 12); and control group (n = 16). Subjects in PRG and CRG underwent robot-assisted gait training for 30 minutes, three times a week for six weeks. And the control group performed overground gait training using a treadmill at the same frequency and for the same amount of time as the experimental group. All Subjects were assessed for muscle strength, balance, gait and motor function pre- and post-intervention. Results: The study results showed that all subjects showed significant differences in all measurements post-intervention (p < 0.05). Additionally, PRG was found to significantly improve in Medical Research Council (MRC) and Fugl-Meyer Assessment (FMA) compared to CRG, and CRG showed significant differences compared to the control group in MRC, Berg Balance Scale (BBS) and Timed Up and Go test (TUG) (p < 0.05). PRG exhibited significant differences in all areas in the between-group comparison with the control group (p < 0.05). Conclusion: These results suggest that PRG may be effective strategy to improve balance and gait ability for with stroke.

본 논문에서는 2자유도 매니퓰레이터(manipulator)가 탑재된 지상형 이동 로봇을 활용한 균열 지도 작성 기법을 소개한다. 로봇의 앞·측면에 각각 스테레오 비전 센서를 설치하였으며, 앞면에 설치된 센서의 포인트 클라우드 정보를 이용하여 로봇의 위치를 인식하 고 지도를 작성하며, 측면에 설치된 센서의 영상 정보를 바탕으로 벽면 내 균열을 검출한다. 이때, 두 센서의 좌표계를 좌표 변환식을 통해 통일하여 정합 및 검출된 균열 정보를 생성된 지도에 실시간으로 표기하고, 손상의 정보가 기록 및 관리될 수 있도록 하였다. 2자 유도 움직임이 가능한 매니퓰레이터 장치를 이동로봇에 탑재하고 사각지역의 제한 없이 로봇의 진행 방향을 벗어난 균열을 촬영할 수 있도록 하였다. 촬영된 영상 내 딥러닝 기법을 적용하여 균열을 검출하고, 해당 균열이 촬영된 영상 내 일부만 존재한다고 판단하 는 경우 매니퓰레이터를 동작하여 남은 균열의 위치를 추정 및 추가 촬영, 스티칭할 수 있도록 하였다. 본 시스템의 성능 확인을 위하 여 실내 환경에서 실험을 진행하였으며, IoU기반 검출율 0.6 이상의 정확도로 실시간 균열 정보를 구축된 지도 위에 작성하는 것을 확 인하였다.

Background: Stroke patients commonly experience functional declines in balance and gait due to decreased muscle strength and coordination issues caused by brain damage. Through repetitive training, robot-assisted gait training (RAGT) can aid in promoting neuroplasticity in stroke patients and help them acquire effective gait patterns. Additionally, convalescent rehabilitation hospitals help to ensure rapid recovery through intensive rehabilitation training. Objects: This study investigated the effects of RAGT frequency on gait and balance recovery in stroke patients in convalescent rehabilitation hospitals, providing data to optimize rehabilitation efficiency, enhance functional recovery, and support the development of personalized strategies to ensure safer and more rapid returns to daily life. Methods: This study compared the frequency of RAGT by analyzing a group receiving two units of RAGT per day for 5 days per week with a group receiving two units of RAGT per week as part of a comprehensive rehabilitation program, totaling 16 units daily, in a convalescent rehabilitation hospital. Results: In the 10-minute walking test, statistical significance was observed both within and between groups, whereas the Functional Ambulation Category, Fugl-Meyer Assessment–lower extremities, Berg Balance Scale, and timed up-and-go tests showed significance only within groups. Conclusion: End-effector RAGT and traditional gait training significantly improve gait ability, balance, and lower limb function in stroke patients.

Robots equipped with artificial intelligence technology include learning functions. Purely inductive learning methods formulate general hypotheses by finding empirical regularities over the trainning examples. Purely analytical methods use prior knowledge to derive general hypotheses deductively. Therefore, when the physical environment of a robot is complex, there is a problem of increased computational time required for information processing. In particular, when a large number of robots transmit information, more computational time is required for information processing. The distance-based topological method proposed in this paper first constructs the topology based on the distances between robots, and then generates information weights according to the stages of the topology. The technique proposed in this paper has been experimentally confirmed to have excellent performance in environments with a large number of robots and complex physical conditions.

In this study, power generation characteristics based on water flow dynamics in a pipe system with a mobile firefighting robot were analyzed using 3D CAD modeling and computational fluid dynamics(CFD) simulations. The water flow field which is significantly affected by applied pressure, generates mechanical torque at the turbine blades, enabling power generation. The inlet pressure of the flow field was set to approximately 6 to 12 bar, and the flow characteristics such as velocity, pressure, and mass flow rate, along with power generation characteristics, were analyzed under various turbine rotational velocities. It was observed that higher inlet pressures resulted in increased torque and mechanical power output at the turbine blades. This research is expected to serve as a fundamental design and data reference to improve the performance of firefighting robots at fire sites.

본 연구의 목적은 로봇 제작 프로그램이 초등 저학년의 사회성 향상에 미치는 영향을 알아보는 것이다. 연구 대상은 U시의 J교육원에서 또래관 계의 어려움을 경험하고 있는 초등학교 저학년을 대상으로 하였다. 아동 과 보호자의 동의를 받은 최종 20명을 실험집단 10명, 통제집단 10명으 로 구성하였다. 실험집단에게는 로봇 제작 프로그램을 주 2회(회기 당 60분) 총 12회기를 실시하였으며, 실험·통제집단 모두에게 프로그램 효 과성을 검증하기 위해 사회성 검사를 프로그램 전후로 실시하고, 프로그 램 종료 후 4주 뒤에 추후 검사를 통해 효과의 지속성을 확인하였다. 로 봇 제작 프로그램을 실시한 결과 실험집단의 사회성이 향상되었으며 프 로그램 종결 후에도 효과가 지속되는 것으로 나타났다. 따라서 로봇 제 작 프로그램으로 아동의 사회성 향상을 위한 다양한 연구와 교육 현장과 보건복지부의 지원 사업 중 아동의 정서 및 심리의 문제를 해결할 수 있 는 프로그램으로 활용 될 수 있을 것으로 기대한다.