• Title/Summary/Keyword: Unmanned Robot

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Self-driving quarantine robot with chlorine dioxide system (이산화염소 시스템을 적용한 자율주행 방역 로봇)

  • Bang, Gul-Won
    • Journal of Digital Convergence
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    • v.19 no.12
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    • pp.145-150
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    • 2021
  • In order to continuously perform quarantine in public places, it is not easy to secure manpower, but using self-driving-based robots can solve problems caused by manpower. Self-driving-based quarantine robots can continuously prevent the spread of harmful viruses and diseases in public institutions and hospitals without additional manpower. The location of the autonomous driving function was estimated by applying the Pinnacle filter algorithm, and the UV sterilization system and chlorine dioxide injection system were applied for quarantine. The driving time is more than 3 hours and the position error is 0.5m.Soon, the stop-avoidance function was operated at 95% and the obstacle detection distance was 1.5 m, and the automatic charge recovery was charged by moving to the charging cradle at the remaining 10% of the battery capacity. As a result of quarantine with an unmanned quarantine system, UV sterilization is 99% and chlorine dioxide is sterilized more than 95%, which can contribute to reducing enormous social costs.

A study on the mold opening stroke according to the control method of the injection molding machine (사출성형기의 속도제어 방식에 따른 형개거리에 관한 연구)

  • Jung, Hyun-Suk;Lee, Chun-Kyu
    • Design & Manufacturing
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    • v.15 no.3
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    • pp.56-61
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    • 2021
  • The increase in automation facilities in the injection molding industry is a very important process control item. The most important item when constructing an unmanned machine using a take-out robot is the "mold opening stroke" of the mold. The injection molding machine control method is divided into hydraulic type and electric type, and there have been few studies on the mold opening distance according to the control method. In this study, the correlation was confirmed by increasing the injection speed to 20, 50, 80, and 100% for the three types of hydraulic control method, open loop and close loop, and electric control method. Through the experiment, the following results were obtained. (1) It can be seen that the reproducibility is excellent with the electric, close loop, and open loop control methods. (2) When the injection speed is set to 50%, the mold opening distance is 263.10~263.27 mm, which is the most reproducible. (3) As a result of ANOVA, both injection speed and mold opening distance showed a significant difference in the hydraulic control method (p<0.05), but it was verified through experiments that there was no significant difference in the electric control method. Based on these results, when electric control is selected rather than hydraulic control, the reproducibility of the mold opening distance is excellent, so it is thought that the taking-out robot can take the object out of the mold more safely.

Cooperative Multi-agent Reinforcement Learning on Sparse Reward Battlefield Environment using QMIX and RND in Ray RLlib

  • Minkyoung Kim
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.1
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    • pp.11-19
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    • 2024
  • Multi-agent systems can be utilized in various real-world cooperative environments such as battlefield engagements and unmanned transport vehicles. In the context of battlefield engagements, where dense reward design faces challenges due to limited domain knowledge, it is crucial to consider situations that are learned through explicit sparse rewards. This paper explores the collaborative potential among allied agents in a battlefield scenario. Utilizing the Multi-Robot Warehouse Environment(RWARE) as a sparse reward environment, we define analogous problems and establish evaluation criteria. Constructing a learning environment with the QMIX algorithm from the reinforcement learning library Ray RLlib, we enhance the Agent Network of QMIX and integrate Random Network Distillation(RND). This enables the extraction of patterns and temporal features from partial observations of agents, confirming the potential for improving the acquisition of sparse reward experiences through intrinsic rewards.

Interference Cancelation Method for Intelligent Vehicle Radar (차량용 레이더 간섭 제거 신호처리 방법)

  • Hyun, Eu-Gin;Lee, Jong-Hun
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.45 no.6
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    • pp.35-41
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    • 2008
  • The most important requirement for the automotive radars is the simultaneous target range and velocity measurement under environment of multi-target, clutters, multi-path, and so on. If the many vehicles with 77GHz FMCW(Frequency Modulation Continuous Wave) radar system are in the near area we should consider the interference signals occurred by other radar systems because these signals reduce exact detection of range and velocity. In this paper, we propose the interference cancellation method, which each vehicle radar transmits chirp trains with the different frequency sweep shapes. The proposed method is applied into the various applications such as an intelligent vehicle, Robot, and UGV(Unmanned Ground Vehicle).

Terrain Information Extraction for Traversability Analysis of Unmaned Robots (무인로봇의 주행성 분석을 위한 지형정보 추출)

  • Jin, Gang-Gyoo;Lee, Hyun-Sik;Lee, Yun-Hyung;So, Myung-Ok;Chae, Jeong-Sook;Lee, Young-Il
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2008.04a
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    • pp.233-236
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    • 2008
  • Recently, the development and application of unmaned robots are increasing in various fields including surveillance and reconnaissance, planet exploration and disaster relief. Unmaned robots are usually controlled from distance using radio communications but they should be equipped with autonomous travelling function to cope with unexpected terrains and obstacles. This means that unmanned robots should be able to evaluate terrain's characteristics quantitatively using mounted sensors so as to traverse harsh natural terrains autonomously. For this purpose, this paper presents an algorithm for extracting terrain information from elevation maps as an early step of traversability analysis. Slope and roughness information are extracted from a world terrain map based on least squares method and fractal theory, respectively. The effectiveness of the proposed algorithm is verified on both fractal and real terrain maps.

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Wireless Extension of Profibus Network Using IEEE 802.0111 and Its Performance Evaluation (IEEE 802.11을 이용한 Profibus 네트워크의 무선 확장 및 성능 평가)

  • Lee, Kyung-Chang;Kang, Song;Lee, Suk;Lee, Man-Hyung
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.4
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    • pp.326-333
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    • 2001
  • This paper focuses on a method to connect mobile devices such as mobile robot. Automated Guided Vehicle (AGV) and Unmanned Container Transporter(UCT) to a fieldbus. In this paper, the IEEE 802.11 wireless LAN is used to extend a Profibus network for the mobile devices. In order to integrate these two networks, a gateway is developed using two threads and an internal buffer. Furthermore, a polling algorithm is applied at the gateway in order to satisfy real-time requirements on data communication, Finally, the performance measures such as data latency and throughput are experimentally evaluated on a wirelessly-extended Profibus network. The results shows the feasibility of the wireless extension of Profilbus for various mobile device.

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Deep Learning-Based Smart Meter Wattage Prediction Analysis Platform

  • Jang, Seonghoon;Shin, Seung-Jung
    • International journal of advanced smart convergence
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    • v.9 no.4
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    • pp.173-178
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    • 2020
  • As the fourth industrial revolution, in which people, objects, and information are connected as one, various fields such as smart energy, smart cities, artificial intelligence, the Internet of Things, unmanned cars, and robot industries are becoming the mainstream, drawing attention to big data. Among them, Smart Grid is a technology that maximizes energy efficiency by converging information and communication technologies into the power grid to establish a smart grid that can know electricity usage, supply volume, and power line conditions. Smart meters are equient that monitors and communicates power usage. We start with the goal of building a virtual smart grid and constructing a virtual environment in which real-time data is generated to accommodate large volumes of data that are small in capacity but regularly generated. A major role is given in creating a software/hardware architecture deployment environment suitable for the system for test operations. It is necessary to identify the advantages and disadvantages of the software according to the characteristics of the collected data and select sub-projects suitable for the purpose. The collected data was collected/loaded/processed/analyzed by the Hadoop ecosystem-based big data platform, and used to predict power demand through deep learning.

Mission Planning for Underwater Survey with Autonomous Marine Vehicles

  • Jang, Junwoo;Do, Haggi;Kim, Jinwhan
    • Journal of Ocean Engineering and Technology
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    • v.36 no.1
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    • pp.41-49
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    • 2022
  • With the advancement of intelligent vehicles and unmanned systems, there is a growing interest in underwater surveys using autonomous marine vehicles (AMVs). This study presents an automated planning strategy for a long-term survey mission using a fleet of AMVs consisting of autonomous surface vehicles and autonomous underwater vehicles. Due to the complex nature of the mission, the actions of the vehicle must be of high-level abstraction, which means that the actions indicate not only motion of the vehicle but also symbols and semantics, such as those corresponding to deploy, charge, and survey. For automated planning, the planning domain definition language (PDDL) was employed to construct a mission planner for realizing a powerful and flexible planning system. Despite being able to handle abstract actions, such high-level planners have difficulty in efficiently optimizing numerical objectives such as obtaining the shortest route given multiple destinations. To alleviate this issue, a widely known technique in operations research was additionally employed, which limited the solution space so that the high-level planner could devise efficient plans. For a comprehensive evaluation of the proposed method, various PDDL-based planners with different parameter settings were implemented, and their performances were compared through simulation. The simulation result shows that the proposed method outperformed the baseline solutions by yielding plans that completed the missions more quickly, thereby demonstrating the efficacy of the proposed methodology.

Development of Tire Test Bed for Dynamic Behavior Analysis of Vehicles on Off-roads (비포장노면 차량 거동 분석을 위한 타이어 테스트베드 개발)

  • Lee, Dae-Kyung;Sohn, Jeong-Hyun
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.21 no.3
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    • pp.29-35
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    • 2022
  • When a vehicle is driven off a road surface, the deformations of the road surface and tire are combined. Consequently, the dynamic behavior of wheel movement becomes difficult to predict and control. Herein, we propose a tire test bed to capture the dynamic behavior of tires moving on sand and soil. Based on this study, it is discovered that the slip rate can be controlled, and the vertical force can be measured using a load cell. The test results show that this test bed can be useful for capturing the dynamic behavior of the tire and validating dynamic simulations. In fact, the tire test bed developed in this study can be used to verify the results of computer simulations. In addition, it can be used for basic experiments pertaining to the speed control of unmanned autonomous vehicles.

Multimodal layer surveillance map based on anomaly detection using multi-agents for smart city security

  • Shin, Hochul;Na, Ki-In;Chang, Jiho;Uhm, Taeyoung
    • ETRI Journal
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    • v.44 no.2
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    • pp.183-193
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    • 2022
  • 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.