• 제목/요약/키워드: multi-agent robot system

검색결과 50건 처리시간 0.031초

Simultaneous Localization and Mobile Robot Navigation using a Sensor Network

  • Jin Tae-Seok;Bashimoto Hideki
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제6권2호
    • /
    • pp.161-166
    • /
    • 2006
  • Localization of mobile agent within a sensing network is a fundamental requirement for many applications, using networked navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, This paper describes a networked sensor-based navigation method in an indoor environment for an autonomous mobile robot which can navigate and avoid obstacle. In this method, the self-localization of the robot is done with a model-based vision system using networked sensors, and nonstop navigation is realized by a Kalman filter-based STSF(Space and Time Sensor Fusion) method. Stationary obstacles and moving obstacles are avoided with networked sensor data such as CCD camera and sonar ring. We will report on experiments in a hallway using the Pioneer-DX robot. In addition to that, the localization has inevitable uncertainties in the features and in the robot position estimation. Kalman filter scheme is used for the estimation of the mobile robot localization. And Extensive experiments with a robot and a sensor network confirm the validity of the approach.

지능로봇에서 에이전트와 ESB를 사용한 서비스 지향 애플리케이션의 자가 재구성 (Self-Reconfiguration of Service-Oriented Application using Agent and ESB in Intelligent Robot)

  • 이재정;김진한;이창호;이병정
    • 한국정보과학회논문지:컴퓨팅의 실제 및 레터
    • /
    • 제14권8호
    • /
    • pp.813-817
    • /
    • 2008
  • 지능로봇(Intelligent Robot)은 주변환경을 감지하는 센서로부터 실시간 정보를 수집하고 지능적인 기능을 수행한다. 지능로봇의 자가 재구성(Self-Reconfiguration) 능력은 외부 환경의 변화에 대응하기 위해 기능을 재구성하고, 오류가 발생하였을 때 중지 없이 스스로 회복할 수 있는 중요한 요소이다. 본 논문에서는 ESB(Enterprise Service Bus)를 사용한 지능로봇의 에이전트 기반 자가 재구성 프레임워크를 제안한다. 본 논문의 프궤임워크는 멀티에이전트 시스템을 이용한 서비스 지향 애플리케이션의 동적인 발견과 자가 재구성에 초점을 맞춘다. 지능로봇이 예외적인 상황을 만났을 때, 지능로봇은 외부의 서비스 저장소로부터 새로운 서비스를 다운로드 후 실행시켜 상황을 해결한다. 에이전트 기술은 로봇들이 상호작용하기 위한 지능적인 접근법을 제공하고, ESB는 분산된 서비스 또는 지식을 활용하고 조직하기 위한 방법을 제공한다. 또한 본 연구의 유효성을 보여주기 위해 프로토타입을 구현하였다.

A Navigation System for Mobile Robot

  • 장원량;정길도
    • 대한전자공학회:학술대회논문집
    • /
    • 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
    • /
    • pp.118-120
    • /
    • 2009
  • In this paper, we present the Q-learning method for adaptive traffic signal control on the basis of multi-agent technology. The structure is composed of sixphase agents and one intersection agent. Wireless communication network provides the possibility of the cooperation of agents. As one kind of reinforcement learning, Q-learning is adopted as the algorithm of the control mechanism, which can acquire optical control strategies from delayed reward; furthermore, we adopt dynamic learning method instead of static method, which is more practical. Simulation result indicates that it is more effective than traditional signal system.

  • PDF

Human Robot Interaction via Evolutionary Network Intelligence

  • Yamaguchi, Toru
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 제어로봇시스템학회 2002년도 ICCAS
    • /
    • pp.49.2-49
    • /
    • 2002
  • This paper describes the configuration of a multi-agent system that can recognize human intentions. This system constructs ontologies of human intentions and enables knowledge acquisition and sharing between intelligent agents operating in different environments. This is achieved by using a bi-directional associative memory network. The process of intention recognition is based on fuzzy association inferences. This paper shows the process of information sharing by using ontologies. The purpose of this research is to create human-centered systems that can provide a natural interface in their interaction with people.

  • PDF

다중에이전트 경로탐색(MAPF) 기반의 실내배송로봇 군집제어 구현 (Implementation of MAPF-based Fleet Management System)

  • 신동철;문형일;강성규;이성원;양현석;박찬욱;남문식;정길수;김영재
    • 로봇학회논문지
    • /
    • 제17권4호
    • /
    • pp.407-416
    • /
    • 2022
  • Multiple AMRs have been proved to be effective in improving warehouse productivity by eliminating workers' wasteful walking time. Although Multi-agent Path Finding (MAPF)-based solution is an optimal approach for this task, its deployment in practice is challenging mainly due to its imperfect plan-execution capabilities and insufficient computing resources for high-density environments. In this paper, we present a MAPF-based fleet management system architecture that robustly manages multiple robots by re-computing their paths whenever it is necessary. To achieve this, we defined four events that trigger our MAPF solver framework to generate new paths. These paths are then delivered to each AMR through ROS2 message topic. We also optimized a graph structure that effectively captures spatial information of the warehouse. By using this graph structure we can reduce computational burden while keeping its rescheduling functionality. With proposed MAPF-based fleet management system, we can control AMRs without collision or deadlock. We applied our fleet management system to the real logistics warehouse with 10 AMRs and observed that it works without a problem. We also present the usage statistic of adopting AMRs with proposed fleet management system to the warehouse. We show that it is useful over 25% of daily working time.

IR 센서와 영상정보를 이용한 다 개체 로봇의 장애물 회피 방법 (Obstacle Avoidance Method for Multi-Agent Robots Using IR Sensor and Image Information)

  • 전병승;이도영;최인환;모영학;박정민;임묘택
    • 제어로봇시스템학회논문지
    • /
    • 제18권12호
    • /
    • pp.1122-1131
    • /
    • 2012
  • This paper presents obstacle avoidance method for scout robot or industrial robot in unknown environment by using IR sensor and vision system. In the proposed method, robots share the information where the obstacles are located in real-time, thus the robots can choose the best path for obstacle avoidance. Using IR sensor and vision system, multiple robots efficiently evade the obstacles by the proposed cooperation method. No landmark is used at wall or floor in experiment environment. The obstacles don't have specific color or shape. To get the information of the obstacle, vision system extracts the obstacle coordinate by using an image labeling method. The information obtained by IR sensor is about the obstacle range and the locomotion direction to decide the optimal path for avoiding obstacle. The experiment was conducted in $7m{\times}7m$ indoor environment with two-wheeled mobile robots. It is shown that multiple robots efficiently move along the optimal path in cooperation with each other in the space where obstacles are located.

지능형 멀티 에이전트 로봇시스템을 위한 통신시스템의 설계 (Design of Communication System for Intelligent Multi Agent Robot System)

  • 김준엽;박승민;고광은;장인훈;심귀보
    • 제어로봇시스템학회논문지
    • /
    • 제18권8호
    • /
    • pp.758-767
    • /
    • 2012
  • In the ad-hoc wireless network environment, that the fixed sensor nodes and the sensor nodes to move are mixed, as the number of the sensor nodes with mobility are getting more, the costs to recover and maintain the whole network will increase more and more. This paper proposed the CDSR (Cost based Dynamic Source Routing) algorithm being motivated from the typical DSR algorithm, that is one of the reactive routing protocol. The cost function is defined through measuring the cost which any sensor node pays to participate in the whole network for communication. It is also showed in this paper that the proposed routing algorithm will increase the efficiency and life of whole sensor network through a series of experiments.

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
    • /
    • 제44권2호
    • /
    • pp.183-193
    • /
    • 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.

A HARMS-based heterogeneous human-robot team for gathering and collecting

  • Kim, Miae;Koh, Inseok;Jeon, Hyewon;Choi, Jiyeong;Min, Byung Cheol;Matson, Eric T.;Gallagher, John
    • Advances in robotics research
    • /
    • 제2권3호
    • /
    • pp.201-217
    • /
    • 2018
  • Agriculture production is a critical human intensive task, which takes place in all regions of the world. The process to grow and harvest crops is labor intensive in many countries due to the lack of automation and advanced technology. Much of the difficult, dangerous and dirty labor of crop production can be automated with intelligent and robotic platforms. We propose an intelligent, agent-oriented robotic team, which can enable the process of harvesting, gathering and collecting crops and fruits, of many types, from agricultural fields. This paper describes a novel robotic organization enabling humans, robots and agents to work together for automation of gathering and collection functions. The focus of the research is a model, called HARMS, which can enable Humans, software Agents, Robots, Machines and Sensors to work together indistinguishably. With this model, any capability-based human-like organization can be conceived and modeled, such as in manufacturing or agriculture. In this research, we model, design and implement a technology application of knowledge-based robot-to-robot and human-to-robot collaboration for an agricultural gathering and collection function. The gathering and collection functions were chosen as they are some of the most labor intensive and least automated processes in the process acquisition of agricultural products. The use of robotic organizations can reduce human labor and increase efficiency allowing people to focus on higher level tasks and minimizing the backbreaking tasks of agricultural production in the future. In this work, the HARMS model was applied to three different robotic instances and an integrated test was completed with satisfactory results that show the basic promise of this research.

Passive RFID 시스템을 이용한 효율적인 영역 탐색 기법 (Passive RFID system for Efficient Area Coverage Algorithm)

  • 이상엽;이충용;조원서;남상엽;김동한
    • 전자공학회논문지
    • /
    • 제51권2호
    • /
    • pp.220-226
    • /
    • 2014
  • 본 논문에서는 Passive RFID system으로 구성된 Smart Floor 환경에서 다 개체 로봇의 효율적인 영역 탐색 방법을 제안한다. 연구에서 사용된 Passive RFID system 은 RF 안테나의 인식 범위 내에 있는 RF 태그에 사용자가 원하는 정보를 저장하고 읽을 수 있다. 본 연구에서는 명시적인 위치정보를 저장한 RF 태그를 바닥에 매설한 Smart Floor 라는 환경을 구축하였고, 로봇에 설치되어 있는 안테나를 통하여 태그로부터 받아들인 위치정보를 논문에서 제안하는 방법으로 가공하여 모바일 로봇의 위치를 추정함과 동시에 Smart Floor 내의 다른 로봇에게 자신의 이동 흔적을 남김으로써 기존 탐색 기법에 비해 전체 영역 탐색 시간을 단축하여 효율을 높였다. 본 논문에서는 Smart Floor 환경을 활용하여 모바일 로봇의 효율적인 이동 알고리즘을 제안한다.