• Title/Summary/Keyword: Robot simulator

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Development of Attack Intention Extractor for Soccer Robot system (축구 로봇의 공격 의도 추출기 설계)

  • 박해리;정진우;변증남
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.40 no.4
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    • pp.193-205
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    • 2003
  • There has been so many research activities about robot soccer system in the many research fields, for example, intelligent control, communication, computer technology, sensor technology, image processing, mechatronics. Especially researchers research strategy for attacking in the field of strategy, and develop intelligent strategy. Then, soccer robots cannot defense completely and efficiently by using simple defense strategy. Therefore, intention extraction of attacker is needed for efficient defense. In this thesis, intention extractor of soccer robots is designed and developed based on FMMNN(Fuzzy Min-Max Neural networks ). First, intention for soccer robot system is defined, and intention extraction for soccer robot system is explained.. Next, FMMNN based intention extractor for soccer robot system is determined. FMMNN is one of the pattern classification method and have several advantages: on-line adaptation, short training time, soft decision. Therefore, FMMNN is suitable for soccer robot system having dynamic environment. Observer extracts attack intention of opponents by using this intention exactor, and this intention extractor is also used for analyzing strategy of opponent team. The capability of developed intention extractor is verified by simulation of 3 vs. 3 robot succor simulator. It was confirmed that the rates of intention extraction each experiment increase.

ROV Manipulation from Observation and Exploration using Deep Reinforcement Learning

  • Jadhav, Yashashree Rajendra;Moon, Yong Seon
    • Journal of Advanced Research in Ocean Engineering
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    • v.3 no.3
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    • pp.136-148
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    • 2017
  • The paper presents dual arm ROV manipulation using deep reinforcement learning. The purpose of this underwater manipulator is to investigate and excavate natural resources in ocean, finding lost aircraft blackboxes and for performing other extremely dangerous tasks without endangering humans. This research work emphasizes on a self-learning approach using Deep Reinforcement Learning (DRL). DRL technique allows ROV to learn the policy of performing manipulation task directly, from raw image data. Our proposed architecture maps the visual inputs (images) to control actions (output) and get reward after each action, which allows an agent to learn manipulation skill through trial and error method. We have trained our network in simulation. The raw images and rewards are directly provided by our simple Lua simulator. Our simulator achieve accuracy by considering underwater dynamic environmental conditions. Major goal of this research is to provide a smart self-learning way to achieve manipulation in highly dynamic underwater environment. The results showed that a dual robotic arm trained for a 3DOF movement successfully achieved target reaching task in a 2D space by considering real environmental factor.

Analyzing the Acoustic Elements and Emotion Recognition from Speech Signal Based on DRNN (음향적 요소분석과 DRNN을 이용한 음성신호의 감성 인식)

  • Sim, Kwee-Bo;Park, Chang-Hyun;Joo, Young-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.1
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    • pp.45-50
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    • 2003
  • Recently, robots technique has been developed remarkably. Emotion recognition is necessary to make an intimate robot. This paper shows the simulator and simulation result which recognize or classify emotions by learning pitch pattern. Also, because the pitch is not sufficient for recognizing emotion, we added acoustic elements. For that reason, we analyze the relation between emotion and acoustic elements. The simulator is composed of the DRNN(Dynamic Recurrent Neural Network), Feature extraction. DRNN is a learning algorithm for pitch pattern.

Vision-based Ground Test for Active Debris Removal

  • Lim, Seong-Min;Kim, Hae-Dong;Seong, Jae-Dong
    • Journal of Astronomy and Space Sciences
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    • v.30 no.4
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    • pp.279-290
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    • 2013
  • Due to the continuous space development by mankind, the number of space objects including space debris in orbits around the Earth has increased, and accordingly, difficulties of space development and activities are expected in the near future. In this study, among the stages for space debris removal, the implementation of a vision-based approach technique for approaching space debris from a far-range rendezvous state to a proximity state, and the ground test performance results were described. For the vision-based object tracking, the CAM-shift algorithm with high speed and strong performance, and the Kalman filter were combined and utilized. For measuring the distance to a tracking object, a stereo camera was used. For the construction of a low-cost space environment simulation test bed, a sun simulator was used, and in the case of the platform for approaching, a two-dimensional mobile robot was used. The tracking status was examined while changing the position of the sun simulator, and the results indicated that the CAM-shift showed a tracking rate of about 87% and the relative distance could be measured down to 0.9 m. In addition, considerations for future space environment simulation tests were proposed.

Development of a prototype simulator for dental education (치의학 교육을 위한 프로토타입 시뮬레이터의 개발)

  • Mi-El Kim;Jaehoon Sim;Aein Mon;Myung-Joo Kim;Young-Seok Park;Ho-Beom Kwon;Jaeheung Park
    • The Journal of Korean Academy of Prosthodontics
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    • v.61 no.4
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    • pp.257-267
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    • 2023
  • Purpose. The purpose of the study was to fabricate a prototype robotic simulator for dental education, to test whether it could simulate mandibular movements, and to assess the possibility of the stimulator responding to stimuli during dental practice. Materials and methods. A virtual simulator model was developed based on segmentation of the hard tissues using cone-beam computed tomography (CBCT) data. The simulator frame was 3D printed using polylactic acid (PLA) material, and dentiforms and silicone face skin were also inserted. Servo actuators were used to control the movements of the simulator, and the simulator's response to dental stimuli was created by pressure and water level sensors. A water level test was performed to determine the specific threshold of the water level sensor. The mandibular movements and mandibular range of motion of the simulator were tested through computer simulation and the actual model. Results. The prototype robotic simulator consisted of an operational unit, an upper body with an electric device, a head with a temporomandibular joint (TMJ) and dentiforms. The TMJ of the simulator was capable of driving two degrees of freedom, implementing rotational and translational movements. In the water level test, the specific threshold of the water level sensor was 10.35 ml. The mandibular range of motion of the simulator was 50 mm in both computer simulation and the actual model. Conclusion. Although further advancements are still required to improve its efficiency and stability, the upper-body prototype simulator has the potential to be useful in dental practice education.

Side Scan Sonar based Pose-graph SLAM (사이드 스캔 소나 기반 Pose-graph SLAM)

  • Gwon, Dae-Hyeon;Kim, Joowan;Kim, Moon Hwan;Park, Ho Gyu;Kim, Tae Yeong;Kim, Ayoung
    • The Journal of Korea Robotics Society
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    • v.12 no.4
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    • pp.385-394
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    • 2017
  • Side scanning sonar (SSS) provides valuable information for robot navigation. However using the side scanning sonar images in the navigation was not fully studied. In this paper, we use range data, and side scanning sonar images from UnderWater Simulator (UWSim) and propose measurement models in a feature based simultaneous localization and mapping (SLAM) framework. The range data is obtained by echosounder and sidescanning sonar images from side scan sonar module for UWSim. For the feature, we used the A-KAZE feature for the SSS image matching and adjusting the relative robot pose by SSS bundle adjustment (BA) with Ceres solver. We use BA for the loop closure constraint of pose-graph SLAM. We used the Incremental Smoothing and Mapping (iSAM) to optimize the graph. The optimized trajectory was compared against the dead reckoning (DR).

Transformer-Based MUM-T Situation Awareness: Agent Status Prediction (트랜스포머 기반 MUM-T 상황인식 기술: 에이전트 상태 예측)

  • Jaeuk Baek;Sungwoo Jun;Kwang-Yong Kim;Chang-Eun Lee
    • The Journal of Korea Robotics Society
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    • v.18 no.4
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    • pp.436-443
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    • 2023
  • With the advancement of robot intelligence, the concept of man and unmanned teaming (MUM-T) has garnered considerable attention in military research. In this paper, we present a transformer-based architecture for predicting the health status of agents, with the help of multi-head attention mechanism to effectively capture the dynamic interaction between friendly and enemy forces. To this end, we first introduce a framework for generating a dataset of battlefield situations. These situations are simulated on a virtual simulator, allowing for a wide range of scenarios without any restrictions on the number of agents, their missions, or their actions. Then, we define the crucial elements for identifying the battlefield, with a specific emphasis on agents' status. The battlefield data is fed into the transformer architecture, with classification headers on top of the transformer encoding layers to categorize health status of agent. We conduct ablation tests to assess the significance of various factors in determining agents' health status in battlefield scenarios. We conduct 3-Fold corss validation and the experimental results demonstrate that our model achieves a prediction accuracy of over 98%. In addition, the performance of our model are compared with that of other models such as convolutional neural network (CNN) and multi layer perceptron (MLP), and the results establish the superiority of our model.

Development of Universal Sports Simulator Fusing 5 Senses (범용 오감 융합형 스포츠 시뮬레이터의 개발)

  • Lee, Young-Dae;Lee, Won-Sik;Kang, Jeong-Jin
    • The Journal of the Convergence on Culture Technology
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    • v.1 no.1
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    • pp.73-77
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    • 2015
  • Existing sports simulators on the market focus on the motion of platform or reality expression using basic visual contents, and are limited to entertainment products. Therefore, the stimulus on 5 senses is not good enough to be applied on high virtual reality. Moreover, there are not enough professional contents to be applied to an educational sports simulator. In this paper, we developed a sport platform by separating the multi axis based common platform module and the sports application module. We designed the common platform which has 4 degrees of freedom such as surge, sway, heave and yaw motion. This platform has the purpose of stabilizing motion and minimizing interference. The changeable sport module which is attached to the common module has 2 degrees of freedom such as roll and pitch, so that it can be applied to the various fields of 2 degrees of freedom virtual reality sports such as horse riding and yacht.

Ontology-based User Intention Recognition for Proactive Planning of Intelligent Robot Behavior (지능형로봇 행동의 능동적 계획수립을 위한 온톨로지 기반 사용자 의도인식)

  • Jeon, Ho-Cheol;Choi, Joong-Min
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.1
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    • pp.86-99
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    • 2011
  • Due to the uncertainty of intention recognition for behaviors of users, the intention is differently recognized according to the situation for the same behavior by the same user, the accuracy of user intention recognition by minimizing the uncertainty is able to be improved. This paper suggests a novel ontology-based method to recognize user intentions, and able to minimize the uncertainties that are the obstacles against the precise recognition of user intention. This approach creates ontology for user intention, makes a hierarchy and relationship among user intentions by using RuleML as well as Dynamic Bayesian Network, and improves the accuracy of user intention recognition by using the defined RuleML as well as the gathered sensor data such as temperature, humidity, vision, and auditory. To evaluate the performance of robot proactive planning mechanism, we developed a simulator, carried out some experiments to measure the accuracy of user intention recognition for all possible situations, and analyzed and detailed described the results. The result of our experiments represented relatively high level the accuracy of user intention recognition. On the other hand, the result of experiments tells us the fact that the actions including the uncertainty get in the way the precise user intention recognition.

A study on the development of Electro-hydraulic servo Excavator(1) -Simulation of the trajectory tracking control using VSS- (전기-유압서보에 의한 자동유압굴삭기의 개발에 관한 연구(1) -가변구조에 의한 궤도추종제어 시뮬레이션-)

  • Heo, Jun-Yeong;Ha, Seok-Hong;Lee, Jin-Geol
    • Journal of the Korean Society for Precision Engineering
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    • v.6 no.2
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    • pp.65-76
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    • 1989
  • The objective of this paper is to design the variable structure system(VSS) controller for the tracking control of excavator which is driven by electro-hydraulic servomechansim. It is generally agreed that the dynamic characteristics of the robot arm such as excavator are coupled, time varying, and highly nonlinear, and also hydraulic system contains nonlinear characteristics in itself, so performing exact position control and trajectory tracking control need remarkable consideration. To solve this porblem, this system was designed as a variable structure system. The salient feature of VSS is that the sliding mode occur on a switching surface. While in sliding mode, the system remains insensitive to parameter variations and disturbances. This control algorithm was applied to a hydraulic excavator by simulaltion and to a simulator by experiment. And its effectiveness was verified. And the results of VSS for the electro-hydraulic excavator was compared with that of the PID when load disturbances and system parameter variations exist.

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