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Image Enhancement Method for detection in Logistics Loading and Unloading robots

IEEE Access 2024年 1-1页

作者： Kang, Jeon-Seong Kang, Jin Kyu Son, Soeun Park, Sung Ho Jung, Eui-Jung Cho, Gun rae AI Robotics R&D Division Korea Institute of Robotics & Technology Convergence Seoul Republic of Korea Independent Researcher Seoul Republic of Korea Autonomous Systems R&D Division Korea Institute of Robotics & Technology Convergence Pohang Republic of Korea

This paper presents a novel method in the field of robotic vision, specifically designed to operate effectively under various lighting conditions. We propose an Image Enhancement Method for parcel loading status recognition, which addresses the challenge of insufficient lighting inside freight trucks without requiring lighting adjustments. Our approach integrates GAN and YOLO v5 into an end-to-end structure, where the detection network’s outputs influence the training of the generative network. Unlike traditional methods that focus solely on enhancing low-light image visibility, our method is optimized to maximize detection accuracy. To demonstrate the superiority of our approach, we constructed a setup resembling a freight truck, collected a dataset under varying lighting conditions, and conducted extensive experiments. The latter sections of the paper review relevant studies on vision data control in computer vision, provide a detailed explanation of our method, describe the experimental setup and database acquisition process, and discuss the results and analyses. The conclusion is presented in Section 6. Authors

关键词： Lighting

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Low Impedance rendering Toward Safe Human-robot Interaction 25

Low Impedance Rendering Toward Safe Human-Robot Interaction

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ACM/IEEE International Conference on Human-robot Interaction (HrI)

作者： Wonbum Yun Kiyoung Choi Junyoung Kim Sehoon Oh HyunJoon Chung AI Robotics R&D Division Korea Institute of Robot and Convergence Pohang Korea Robotics and Mechatronics Engineering DGIST Daegu Korea

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

This study proposes a novel approach for low-impedance rendering in robots to ensure safe human-robot interaction. Low-impedance control enhances safety by enabling robots to respond flexibly to physical contact with humans. However, real-world disturbances such as friction often necessitate high impedance, creating a trade-off between safety and task precision. To address this challenge, a modified disturbance observer (dOB)-based control framework is introduced, designed to prevent external contact forces from being treated as disturbances. Experimental results demonstrate significant improvements in impedance rendering performance under various conditions, ensuring precise and safe robot operations in dynamic shared environments.

关键词： robust control Friction Human-robot interaction rendering (computer graphics) disturbance observers Safety recycling Impedance reliability robots

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Enhancing GAN-Based Motion data Augmentation Through dynamic Time Warping distance Filtering

Enhancing GAN-Based Motion Data Augmentation Through Dynamic...

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International Conference on Artificial Intelligence in Information and Communication (ICaiIC)

作者： Junwon Yoon Hyun-Joon Chung Jeon-Seong Kang Jung-Jun Kim Kwang-Woo Jeon SeungWoo Kim Myounghoon Shim Jae-Kwan ryu AI Robotics R&D Division Korea Institute of Robotics & Technology Convergence Seoul Republic of Korea Unmanned/Intelligent Robotic Systems R&D LIG Nexl Seongnam Republic of Korea

Motion capture data is crucial but creating a large dataset can be challenging due to complexities in acquisition. Generative Adversarial Network (GAN)-based motion data augmentation offers a potential solution to this issue. However, GANs often struggle with learning from limited data, resulting in poor quality output. In this study, we propose a dynamic Time Warping (dTW) filtering method that filters out generated data significantly deviating from real-world examples. Through this approach, we have achieved an improvement in the fidelity of the generated data, even with dataset size constraints, as evidenced by an increase in action recognition accuracy.

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Optimal Placement of Foot Pressure Sensors for Lower-Limb Exoskeletons Based on Multi-Objective Particle Swarm Optimization Algorithm

Optimal Placement of Foot Pressure Sensors for Lower-Limb Ex...

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International Conference on Artificial Intelligence in Information and Communication (ICaiIC)

作者： Ha-Yoon Song Hyun-Joon Chung Kwang-Woo Jeon Tae-Hwan Kim Junyoung Kim Jin-Yeol Yoo Jae-Kwan ryu AI Robotics R&D Division Korea Institute of Robotics & Technology Convergence Seoul Republic of Korea Unmanned/Intelligent Robotic Systems R&D LIG Nex1 Seongnam Republic of Korea

This study proposes an optimization method for sensor placement in lower-limb exoskeleton robots, aiming to improve the accuracy of the Center of Pressure (CoP) estimation during various human activities. Utilizing the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, the proposed method identifies an optimal sensor count, as the root Mean Square Error (rMSE) decelerates when the sensor count exceeds 6. Application of this method resulted in a reduction of the Mean Absolute Error (MAE) to 4.13 mm and 8.92 mm on the mediolateral and anteroposterior axes respectively, a 22.8% improvement in CoP estimation accuracy compared to traditional anatomical methods. Further analysis revealed that weight parameters influence the CoP estimation accuracy, suggesting an enhancement in sensor placement efficiency through the adjustment of individual objectives' significance. The proposed sensor placement optimization method is expected to significantly enhance the performance of lower-limb exoskeleton robots and increase user satisfaction. Moreover, it could substantially contribute to the enhancement of human-computer interaction in robot control by providing a more accurate reflection of the user's intentions. These findings highlight the importance of continuing research in the field of lower-limb exoskeleton robots.

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design of a Manned-Unmanned Teaming System and Forward-Formation Control for Crevasse detection in the Path of a Human-driven Vehicle

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IEEE Access 2025年

作者： Kwon, Ji-Wook Lee, Hyoujun Uhm, Taeyoung Lee, Jongdeuk Lee, Na-Hyun Choi, Young-Ho Korea Institute of Robotics and Technology Convergence Smart Mobility R&D Division Pohang37666 Korea Republic of

This paper proposes a Man-Unmanned Teaming (MUM-T) system, which is designed to protect manned vehicles traveling in Antarctica from hazards such as crevasse by collaborating with a crevasse exploration robot. Additionally, it introduces a forward-formation between the manned vehicle and the exploration robot within the MUM-T system. In the forward-formation, the exploration robot, acting as the follower, moves ahead of the manned vehicle, which serves as the leader of the formation, to explore crevasses along the anticipated route. The follower predicts the leader’s expected path using its state information, generates a desired position, and tracks that position. For the tracking control of the crevasse exploration robot, the kinematic model based velocity command is employed. The stability and performance of the proposed MUM-T system, forward-formation, and motion control algorithm are validated through simulations. Especially, the forward-formation demonstrated more than an 86% improvement in predicting and mimicking the leader’s trajectory compared to conventional formation strategies. Finally, the field test results in Antarctica confirmed the high practical applicability of the proposed forward-formation-based MUM-T system. © 2013 IEEE.

关键词： Tracking (position)

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

Multimodal layer surveillance map based on anomaly detection...

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作者： Shin, Hochul Na, Ki-In Chang, Jiho Uhm, Taeyoung Department of Intelligent Robotics Electronics and Telecommunications of Research Institute Daejeon Korea Republic of Intelligent Robotics R&D Division Korea Institute of Robotics and Technology Convergence Pohang Korea Republic of

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 multi-layered 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. 1225-6463/$ © 2022 ETrI.

关键词： Modal analysis

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Operational Space Fomulation of Time delay Control for Underwater Vehicles and its Extension to diver Guidance

Operational Space Fomulation of Time Delay Control for Under...

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International Symposium on Underwater Technology

作者： Gun rae Cho Hyungjoo Kang Min-Gyu Kim Sungho Park Hansol Jin Seongho Jin Autonomous Systems R&D Division Korea Institute of Robotics and Techonology Convergence Pohang Republic of Korea

ISBN: (数字)9798331534189

ISBN: (纸本)9798331534196

In this study, we propose a method for designing a robust controller for underwater vehicles when the control input space and workspace differ. To achieve this, we formulate the Time delay Control (TdC) in operational space, which is efficient yet has a simple structure. The proposed controller maintains the robustness against disturbances and structural simplicity inherent in the conventional TdC while effectively addressing the situation where the workspace differs from the control input space. Additionally, we propose a method for applying the proposed controller to the task of guiding divers to their destinations using underwater vehicles. Underwater environments often have limited visibility due to issues such as turbidity, so we design the controller and reference trajectories based on the diver's field of view. Through simulations, we demonstrate that the proposed control method effectively operates in various workspaces, including world-coordinate-based workspaces and diver's field of view-based workspaces.

关键词： Space vehicles delay effects Turbidity Aerospace electronics Stability analysis robustness Trajectory Underwater technology Underwater vehicles Standards

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Tracking Error Based Fault Tolerant Scheme for Marine Vehicles with Thruster redundancy

Tracking Error Based Fault Tolerant Scheme for Marine Vehicl...

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International Symposium on Underwater Technology

作者： Ji-Hong Li Hyungjoo Kang Min-Gyu Kim Mun-Jik Lee Han-Sol Jin Gun rae Cho Autonomous Systems R&D Division KIRO Korea Institute of Robotics and Technology Convergence Pohang Republic of Korea

ISBN: (数字)9798331534189

ISBN: (纸本)9798331534196

This paper proposes an active model-based fault and failure tolerant control scheme for a class of marine vehicles with thruster redundancy. Unlike widely used state and parameter estimation methods, where the estimation errors are utilized to generate residual, in this paper we directly apply the trajectory tracking error terms to construct residual and detect thruster fault and failure in the steady state of the tracking system. As for identification or diagnosis, this paper proposes a novel scheme through a detailed examination of the tracking error trends and the combinations of thruster configurations. Since this fault detection and identification operates within the same closed-loop of the tracking control system, control reconfiguration can be easily achieved by adjusting the weight parameter of the isolated thruster to minimize tracking errors or residual. Numerical studies with the real world vehicle model is also carried out to verify the effectiveness of the proposed method.

关键词： Underwater cables Attitude control redundancy Fault tolerant systems Fault location Market research Control systems Numerical models Underwater technology Underwater vehicles

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OGM Based real-time Obstacle detection and Avoidance using Multibeam FLS

OGM Based Real-time Obstacle Detection and Avoidance using M...

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Mechatronics, Control and robotics (ICMCr), International Conference on

作者： Han-Sol Jin Hyungjoo Kang Min-Gyu Kim Mun-Jik Lee Seongho Jin Gun rae Cho Ji-Hong Li Autonomous Systems R&D Division Korea Institute of Robotics & Technology Convergence Pohang Republic of Korea

This paper presents an obstacle detection and avoidance algorithm based on OGM (occupancy grid map) method and its experimental studies. At each time step (5Hz), given the current frame of FLS (forward looking sonar) image, each of its cloud point is transformed into the reference frame and upgrade the density of the grid where the point is located. during this upgrade, weights were applied to both the current density of the grid and the cloud point intensity. With this OGM, each grid whose density surpass certain threshold is taken as obstacle and counted in the path planning using general potential field method. A series of experimental studies have been carried out in the sea port environment, whereas we can investigate and analysis the effects of the design parameters in both of OGM construction and obstacle avoidance algorithms. This paper shows some of these preliminary results.

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research of Battery Pack and Bolt recognition for Battery Pack disassembly Automation System

Research of Battery Pack and Bolt Recognition for Battery Pa...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Na-Hyun Lee Sung-Jo Yun HyoGon Kim JeongWoo Park Jongdeuk Lee Smart Mobility R&D Division Korea Institute of Robotics & Technology Convergence (KIRO) Pohang Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

In this paper, we describe research on the battery pack disassembly automation system necessary for recycling waste batteries generated due to the increase in electric vehicles. In particular, it describes the recognition process among the steps required to remove the cover of the battery pack during the automated disassembly process. The recognition process includes recognizing the battery pack through a global camera and recognizing the bolt through a local camera attached to each manipulator. In other words, the approximate location information of the bolt is obtained through the battery pack recognition process, and the exact location of the bolt is obtained using the manipulator's local camera to release the bolt. In the battery pack recognition process, the position and posture of the battery pack were estimated by matching point cloud data through the ICP(Iterative Closet Point) algorithm. The bolt recognition process was learned using the yolo v5 model, and the recognition rate was increased by classifying and tagging misrecognized objects into different classes.

关键词： Point cloud compression Automation Fasteners Tagging Cameras Manipulators Electric vehicles Control systems Batteries recycling

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