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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Kim, Yewon Jeon, Haein Kang, Bo-Yeong Kyungpook National University Dept. of Artificial Intelligence Daegu41566 Korea Republic of Kyungpook National University Dept. of Robot and Smart System Engineering Daegu41566 Korea Republic of

ISBN: (纸本)9798350324136

robots with machine learning are expanding their application fields, such as serving robots and guiding robots, but applying machine learning to robots has a high labor cost due to human intervention. This paper proposes interactive robot-robot reinforcement learning technology to minimize human intervention in learning tasks that successfully balance objects between two robots. In this proposed technique, the teacher and student robot guide and learn object balancing based on reinforcement learning. Teacher robot teaches knowledge that has not been learned in advance to student robot, and teaches more effectively by providing various positive and negative text feedback on the training results. In virtual simulations, the training results of the student robot converge to the optimal policy as an evaluation result of the proposed method, and the trained student robot performs appropriate actions according to various table states by the teacher's random action. Through our experimental results, the application possibility of robot-robot learning is verified being as good as human-robot learning. Our proposed method could be utilized to seamlessly transfer the learned knowledge when it is challenging to apply the learning model to a heterogeneous robot or an agent in an IoT environment. © 2024 IEEE.

关键词： cooperative robot interactive reinforcement learning reinforcement learning robot-robot learning

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A study on the functional design to improve torque transmission of soft actuators in soft wearable suit

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Journal of Institute of Control, robotics and systems 2021年第3期27卷 271-276页

作者： Lee, Jong-Il Koo, Jaewan Park, Min-Ro Hahm, Jehun Sohn, Dong-Seop Seo, Kap-Ho Korea Republic of Korea Republic of Dept. of Robot and Smart System Engineering Kyungpook National University Korea Republic of

This paper proposes a functional design to improve the torque transmission of a wearable suit for walking assistance. The proposed functional design includes a soft actuator, lower-limb support module, and their fastening method. First, the features and functions of the soft actuator and lower-limb support module are described. In addition, according to the elasticity of the fixed band and the relative positions of the fixed band, soft actuator, and lower-limb support module, a fastening method to maximize the torque transmission performance was determined experimentally. Thus, an optimal fastening method was derived, and the functional design of a soft wearable suit applying this method was developed. © ICROS 2021.

关键词： Actuators

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Machine Learning-Based Batch Processing for Calibration of Model and Noise Parameters

Machine Learning-Based Batch Processing for Calibration of M...

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Conference on Digital Avionics systems (DASC)

作者： Kyuman Lee Dept. of Robot and Smart System Engineering Kyungpook National University Daegu Rep. of Korea

Non-Gaussian or non-whiteness of noise sources often occurs in many digital avionics systems. Incorrect modeling of the system degrades the performance of parametric model-based estimators and controllers. To calibrate the model and noise parameters, this paper proposes a machine learning-based batch processing approach. We first mathematically formulate a state augmentation system containing three types of noise: color noise, state-dependent noise, and correlation noise. Next, we define accessible process and measurement residuals to create the training data set. Finally, we propose offline batch processing that recursively utilizes a machine learning technique to calibrate the model and noise parameters. Simulation results under various conditions validate the calibration performance of the proposed approach.

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Interactive robot-robot Reinforcement Learning for Object Balancing Task

Interactive Robot-Robot Reinforcement Learning for Object Ba...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Yewon Kim Haein Jeon Bo-Yeong Kang the Dept. of Artificial Intelligence Kyungpook National University Daegu South Korea the Dept. of Robot and Smart System Engineering Kyungpook National University Daegu South Korea

robots with machine learning are expanding their application fields, such as serving robots and guiding robots, but applying machine learning to robots has a high labor cost due to human intervention. This paper proposes interactive robot-robot reinforcement learning technology to minimize human intervention in learning tasks that successfully balance objects between two robots. In this proposed technique, the teacher and student robot guide and learn object balancing based on reinforcement learning. Teacher robot teaches knowledge that has not been learned in advance to student robot, and teaches more effectively by providing various positive and negative text feedback on the training results. In virtual simulations, the training results of the student robot converge to the optimal policy as an evaluation result of the proposed method, and the trained student robot performs appropriate actions according to various table states by the teacher’s random action. Through our experimental results, the application possibility of robot-robot learning is verified being as good as human-robot learning. Our proposed method could be utilized to seamlessly transfer the learned knowledge when it is challenging to apply the learning model to a heterogeneous robot or an agent in an IoT environment.

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Examination of an independently actuated multi-air pad mattress for preventing pressure ulcers

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Journal of Institute of Control, robotics and systems 2021年第10期27卷 695-702页

作者： Yang, Kyon-Mo Park, Min-Ro Koo, Jaewan Lee, Jong-Il Gwak, Donggi Lee, Seokjae Sohn, Dong-Seop Kim, Min-Gyu Seo, Kap-Ho Korea Institute of Robotics & Technology Convergence Korea Republic of Dept. of Robot and Smart System Engineering Kyungpook National University Korea Republic of Korea Republic of

This study examined the structure of an independently actuated multi-air pad mattress for preventing pressure ulcers, owing to lower body pressure, in specific locations of the body where pressure sores can occur. The contributions of this study are as follows: 1) The parameters were derived and simulations were performed to design air pad units of different sizes with similar heights. 2) The mattress was manufactured by examining the bending of the folding bed, with 36 air pads and three different sizes. 3) Each air pad was independently controlled to inflate, contract, and retain to reduce the pressure on specific body positions. 4) Finally, using the fabricated prototype, the proposed designs were experimentally verified. © ICROS 2021.

关键词： Diseases

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Design of a prosthetic finger for a patient with a partially amputated finger

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Journal of Institute of Control, robotics and systems 2021年第10期27卷 736-744页

作者： Koo, Jaewan Park, Min-Ro Yang, Kyon-Mo Kim, Min-Gyu Song, Min-Geol Jang, Woong Kim, Byung-Kon Song, Jun-Chan Lee, Joonwoo Seo, Kap-Ho Korea Republic of Dept. of Robot and Smart System Engineering Kyungpook National University Korea Republic of GFLEE IN CO.Ltd. China Dept. of Industrial Design Daegu University Korea Republic of Dept. of Physical Therapy Daegu Health College Korea Republic of Dept. of Electrical Engineering Kyungpook National University Daegu41566 Korea Republic of School of Electronic and Electrical Engineering Kyungpook National University Daegu41566 Korea Republic of Korea Republic of

This study proposed the design of a prosthetic finger that can perform functions, such as motion and gripping, without patients (with amputated fingers) needing an additional actuator. The contributions and contents of this study are as follows: First, the structure of a prosthetic finger, which could be operated by the patient’s own volition without an external actuator, was introduced. Second, the mathematical relationship for effectively designing the proposed structure was explained. In addition, by using this mathematical relationship, the trend of the fingertip trajectory, according to the link length and angle (the design variables) was analyzed. Through this analysis, an optimal design was achieved to determine the link length at which the root mean square error with the target trajectory was minimized. Third, a design method reflecting the finger size and anatomical structure was proposed. Finally, using the fabricated prototype, the proposed design was tested, and the prosthetic finger, having free motion and the ability to grip objects of various sizes, was experimentally verified. © ICROS 2021.

关键词： Design

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Carrying the uncarriable: a deformation-agnostic and human-cooperative framework for unwieldy objects using multiple robots

Carrying the uncarriable: a deformation-agnostic and human-c...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Doganay Sirintuna Idil Ozdamar Arash Ajoudani Human-Robot Interfaces and Interaction Laboratory Istituto Italiano di Tecnologia Genoa Italy Dept. of Informatics Bioengineering Robotics and System Engineering University of Genoa Genoa Italy

This manuscript introduces an object deformability-agnostic framework for co-carrying tasks that are shared between a person and multiple robots. Our approach allows the full control of the co-carrying trajectories by the person while sharing the load with multiple robots depending on the size and the weight of the object. This is achieved by merging the haptic information transferred through the object and the human motion information obtained from a motion capture system. One important advantage of the framework is that no strict internal communication is required between the robots, regardless of the object size and deformation characteristics. We validate the framework with two challenging real-world scenarios: co-transportation of a wooden rigid closet and a bulky box on top of forklift moving straps, with the latter characterizing deformable objects. In order to evaluate the generalizability of the proposed framework, a heterogenous team of two mobile manipulators that consist of an Omni-directional mobile base and a collaborative robotic arm with different DoFs is chosen for the experiments. The qualitative comparison between our controller and the baseline controller (i.e., an admittance controller) during these experiments demonstrated the effectiveness of the proposed framework especially when co-carrying deformable objects. Furthermore, we believe that the performance of our framework during the experiment with the lifting straps offers a promising solution for the co-transportation of bulky and ungraspable objects.

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Enhancing Human-robot Collaboration Transportation through Obstacle-Aware Vibrotactile Feedback

arXiv

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arXiv 2023年

作者： Sirintuna, Doganay Ozdamar, Idil Gandarias, Juan M. Ajoudani, Arash Human-Robot Interfaces and Interaction Laboratory Istituto Italiano di Tecnologia Genoa Italy Dept. of Informatics Bioengineering Robotics and System Engineering University of Genoa Genoa Italy

Transporting large and heavy objects can benefit from Human-robot Collaboration (HRC), increasing the contribution of robots to our daily tasks and reducing the risk of injuries to the human operator. This approach usually posits the human collaborator as the leader, while the robot has the follower role. Hence, it is essential for the leader to be aware of the environmental situation. However, when transporting a large object, the operator's situational awareness can be compromised as the object may occlude different parts of the environment. This paper proposes a novel haptic-based environmental awareness module for a collaborative transportation framework that informs the human operator about surrounding obstacles. The robot uses two LIDARs to detect the obstacles in the surroundings. The warning module alerts the operator through a haptic belt with four vibrotactile devices that provide feedback about the location and proximity of the obstacles. By enhancing the operator's awareness of the surroundings, the proposed module improves the safety of the human-robot team in co-carrying scenarios by preventing collisions. Experiments with two non-expert subjects in two different situations are conducted. The results show that the human partner can successfully lead the co-transportation system in an unknown environment with hidden obstacles thanks to the haptic feedback. Copyright © 2023, The Authors. All rights reserved.

关键词： robots

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Carrying the uncarriable: a deformation-agnostic and human-cooperative framework for unwieldy objects using multiple robots

arXiv

引用

arXiv 2022年

作者： Sirintuna, Doganay Ozdamar, Idil Ajoudani, Arash Human-Robot Interfaces and Interaction Laboratory Istituto Italiano di Tecnologia Genoa Italy Dept. of Informatics Bioengineering Robotics and System Engineering University of Genoa Genoa Italy

— This manuscript introduces an object deformability-agnostic framework for co-carrying tasks that are shared between a person and multiple robots. Our approach allows the full control of the co-carrying trajectories by the person while sharing the load with multiple robots depending on the size and the weight of the object. This is achieved by merging the haptic information transferred through the object and the human motion information obtained from a motion capture system. One important advantage of the framework is that no strict internal communication is required between the robots, regardless of the object size and deformation characteristics. We validate the framework with two challenging real-world scenarios: co-transportation of a wooden rigid closet and a bulky box on top of forklift moving straps, with the latter characterizing deformable objects. In order to evaluate the generalizability of the proposed framework, a heterogenous team of two mobile manipulators that consist of an Omni-directional mobile base and a collaborative robotic arm with different DoFs is chosen for the experiments. The qualitative comparison between our controller and the baseline controller (i.e., an admittance controller) during these experiments demonstrated the effectiveness of the proposed framework especially when co-carrying deformable objects. Furthermore, we believe that the performance of our framework during the experiment with the lifting straps offers a promising solution for the co-transportation of bulky and ungraspable objects. Copyright © 2022, The Authors. All rights reserved.

关键词： Controllers

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Mitigating Compensatory Movements in Prosthesis Users via Adaptive Collaborative robotics

arXiv

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arXiv 2025年

作者： Lagomarsino, Marta Arbaud, Robin Tassi, Francesco Ajoudani, Arash Human-Robot Interfaces and Interaction Istituto Italiano di Tecnologia Genoa Italy Dept. of Informatics Bioengineering Robotics and System Engineering University of Genoa Genoa Italy

Prosthesis users can regain partial limb functionality, however, full natural limb mobility is rarely restored, often resulting in compensatory movements that lead to discomfort, inefficiency, and long-term physical strain. To address this issue, we propose a novel human-robot collaboration framework to mitigate compensatory mechanisms in upper-limb prosthesis users by exploiting their residual motion capabilities while respecting task requirements. Our approach introduces a personalised mobility model that quantifies joint-specific functional limitations and the cost of compensatory movements. This model is integrated into a constrained optimisation framework that computes optimal user postures for task performance, balancing functionality and comfort. The solution guides a collaborative robot to reconfigure the task environment, promoting effective interaction. We validated the framework using a new body-powered prosthetic device for single-finger amputation, which enhances grasping capabilities through synergistic closure with the hand but imposes wrist constraints. Initial experiments with healthy subjects wearing the prosthesis as a supernumerary finger demonstrated that a robotic assistant embedding the user-specific mobility model outperformed human partners in handover tasks, improving both the efficiency of the prosthesis user’s grasp and reducing compensatory movements in functioning joints. These results highlight the potential of collaborative robots as effective workplace and caregiving assistants, promoting inclusion and better integration of prosthetic devices into daily tasks. Copyright © 2025, The Authors. All rights reserved.

关键词： Collaborative robots

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