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K. Moselund - IEEE Xplore Author Profile

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Author details

K. Moselund

Also published under: Kirsten Moselund, K. E. Moselund, Kirsten E. Moselund, Kirsten Emilie Moselund, Kirsten Emile Moselund

Publications

86

Citations

1,008

Publications by Year

20042023

Co-Authors:

David AtienzaMichael BaumannY. BaumgartnerFrancesco BellandoMohamed Haykel Ben Jamaa

Show All Co-Authors (112)

K. Moselund

Also published under: Kirsten Moselund, K. E. Moselund, Kirsten E. Moselund, Kirsten Emilie Moselund, Kirsten Emile Moselund

Affiliation

Paul Scherrer Institut, Villigen, Switzerland

EPFL, Lausanne, Switzerland

Publication Topics

Photonic Integrated Circuits,
Waveguide,
Metal Organic Chemical Vapor Deposition,
Nanorods,
1D Photonic Crystal,
Direct Gap,
Epitaxial,
Finite Element Analysis,
Lattice Mismatch,
Lattice Topology,
Nanocavity Lasers,
Photonic Bandgap

Biography

Kirsten E. Moselund (SM’13) received the M.Sc. degree in engineering from the Technical University of Denmark, Kongens Lyngby, Denmark, and the Ph.D. degree in microelectronics from the Swiss Federal Institute of Technology in Lausanne (EPFL), Lausanne, Switzerland, in 2003 and 2008, respectively. In 2008, she joined IBM Research—Zurich, Zurich, Switzerland, where she is working as a Research Staff Member with Materials Integration and Nanoscale Devices Group. Her research interests include semiconductor physics, advanced transistor concepts, and nanoelectronic fabrication technology.(Based on document published on 6 January 2015).

Publications

86

Citations

1,008

Publications by Year

20042023

Co-Authors:

David Atienza
Michael Baumann
Y. Baumgartner
Francesco Bellando
Mohamed Haykel Ben Jamaa

Show All Co-Authors (112)

Author's Published Works

Search History

Showing 1-25 of 1,135 resultsfor "Index Terms":Dexterous manipulation

Conferences (794)

Journals (321)

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Early Access Articles (6)

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School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China(11)
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China(8)
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IEEE Robotics and Automation Letters(153)
IEEE Transactions on Robotics(55)
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Within-Hand Manipulation with an Underactuated Dexterous Hand Based on Pre-Trained Reinforcement Learning

Xin Li;Wenrui Chen;Yaonan Wang;Qiang Diao;Sijie Wu;Fan Yang

2023 China Automation Congress (CAC)

Year: 2023 | Conference Paper |

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This paper investigates a dexterous manipulation method for multi-fingered hands based on the approximate policy optimization (PPO) algorithm. First, a prior knowledge base of dexterous manipulation demonstration data is provided for the PPO algorithm, and the original model is pre-trained to guide fast network training. Second, a new reward function is proposed to optimize rotational manipulation...Show More

Within-Hand Manipulation with an Underactuated Dexterous Hand Based on Pre-Trained Reinforcement Learning

Xin Li;Wenrui Chen;Yaonan Wang;Qiang Diao;Sijie Wu;Fan Yang

2023 China Automation Congress (CAC)

Year: 2023 | Conference Paper |

Tactile Manipulation With a TacThumb Integrated on the Open-Hand M2 Gripper

Benjamin Ward-Cherrier;Luke Cramphorn;Nathan F. Lepora

IEEE Robotics and Automation Letters

Year: 2016 | Volume: 1, Issue: 1 | Journal Article |

Cited by: Papers (50)

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Tactile manipulation will be essential for automating industrial and service tasks currently done by humans. However, the application of tactile feedback to dexterous manipulation remains a challenging unsolved problem, with robot capabilities lagging far behind those of humans. Here, we present the tactile thumb (TacThumb): a cheap, robust, 3-D-printed optical tactile sensor integrated on the Yal...Show More

Tactile Manipulation With a TacThumb Integrated on the Open-Hand M2 Gripper

Benjamin Ward-Cherrier;Luke Cramphorn;Nathan F. Lepora

IEEE Robotics and Automation Letters

Year: 2016 | Volume: 1, Issue: 1 | Journal Article |

Stable In-Hand Manipulation With Finger-Specific Multi-Agent Shadow Critic Consensus and Information Sharing

Lingfeng Tao;Jiucai Zhang;Xiaoli Zhang

IEEE Robotics and Automation Letters

Year: 2025 | Volume: 10, Issue: 3 | Journal Article |

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Deep Reinforcement Learning (DRL) has shown its capability to solve the high degrees of freedom in control and the complex interaction with the object in the multi-finger dexterous in-hand manipulation tasks. Current DRL approaches lack behavior constraints during the learning process, leading to aggressive and unstable policies that are insufficient for safety-critical in-hand manipulation tasks....Show More

Stable In-Hand Manipulation With Finger-Specific Multi-Agent Shadow Critic Consensus and Information Sharing

Lingfeng Tao;Jiucai Zhang;Xiaoli Zhang

IEEE Robotics and Automation Letters

Year: 2025 | Volume: 10, Issue: 3 | Journal Article |

Gross Motion Analysis of Fingertip-Based Within-Hand Manipulation

Nicolas Rojas;Aaron M. Dollar

IEEE Transactions on Robotics

Year: 2016 | Volume: 32, Issue: 4 | Journal Article |

Cited by: Papers (12)

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Fingertip-based within-hand manipulation, also called precision manipulation, refers to the repositioning of a grasped object within the workspace of a multifingered robot hand without breaking or changing the contact type between each fingertip and the object. Given a robot hand architecture and a set of assumed contact models, this paper presents a method to perform a gross motion analysis of it...Show More

Gross Motion Analysis of Fingertip-Based Within-Hand Manipulation

Nicolas Rojas;Aaron M. Dollar

IEEE Transactions on Robotics

Year: 2016 | Volume: 32, Issue: 4 | Journal Article |

Soft-Material-Based Highly Reliable Tri-Axis Tactile Thin-Film Sensors for Robotic Manipulation Tasks

Kei Tsukamoto;Akira Ebisui;Tetsuro Goto;Yoshiaki Sakakura;Ken Kobayashi;Satoshi Sato;Takahiro Kamei;Yutaka Imai;Kazumasa Nomoto

2021 IEEE Sensors

Year: 2021 | Conference Paper |

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Tactile sensing is essential for intelligent robot control such as for dexterous manipulation tasks. To provide reliable sensors that can withstand industrial applications, we have developed a soft and thin-film tactile sensor capable of detecting tri-axis force components including normal and shear forces. The thickness of the sensor is 5.5 mm, and the sensor can be easily attached on an end-effe...Show More

Soft-Material-Based Highly Reliable Tri-Axis Tactile Thin-Film Sensors for Robotic Manipulation Tasks

Kei Tsukamoto;Akira Ebisui;Tetsuro Goto;Yoshiaki Sakakura;Ken Kobayashi;Satoshi Sato;Takahiro Kamei;Yutaka Imai;Kazumasa Nomoto

2021 IEEE Sensors

Year: 2021 | Conference Paper |

A Virtual Hand Based Manipulation Learning Framework for Dexterous Hand

Luyue Zhou;Yumeng Hu;Mengxiang Lin

2023 14th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)

Year: 2023 | Conference Paper |

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Dexterous hand programming is considered to be generally difficult suffering from high degree of freedom. Vision-based manipulation learning provides an efficient way to support automatic programming by human demonstration. However, complex visual perception is tightly coupled with the kinematics structure of dexterous hand in existing solutions, which makes it hard to migrate the developed algori...Show More

A Virtual Hand Based Manipulation Learning Framework for Dexterous Hand

Luyue Zhou;Yumeng Hu;Mengxiang Lin

2023 14th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)

Year: 2023 | Conference Paper |

Development of UB Hand 3: Early Results

F. Lotti;P. Tiezzi;G. Vassura;L. Biagiotti;G. Palli;C. Melchiorri

Proceedings of the 2005 IEEE International Conference on Robotics and Automation

Year: 2005 | Conference Paper |

Cited by: Papers (139)

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The first part of this paper describes the development of a humanoid robot hand based on an endoskeleton made of rigid links connected with elastic hinges, actuated by sheath routed tendons and covered by continuous compliant pulps. The project is called UB Hand 3 (University of Bologna Hand, 3rd version) and aims to reduce the mechanical complexity of robotic end effectors yet maintaining full an...Show More

Development of UB Hand 3: Early Results

F. Lotti;P. Tiezzi;G. Vassura;L. Biagiotti;G. Palli;C. Melchiorri

Proceedings of the 2005 IEEE International Conference on Robotics and Automation

Year: 2005 | Conference Paper |

A Bimanual Teleoperation System of Humanoid Robots for Dexterous Manipulation

Kunpeng Wu;Zhenghong Lu;Xiaoqi Chen

2024 IEEE International Conference on Robotics and Biomimetics (ROBIO)

Year: 2024 | Conference Paper |

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Remote control of robots is usually used to accomplish complex tasks in unstructured environments that are inaccessible or hazardous for humans (e.g., disaster recovery). Teleoperaton of humanoid robots is commonly achieved by employing motion tracking, which simplifies the complexity of manually controlling by reducing the degrees of freedom (DOF). High-quality demonstrations are also crucial for...Show More

A Bimanual Teleoperation System of Humanoid Robots for Dexterous Manipulation

Kunpeng Wu;Zhenghong Lu;Xiaoqi Chen

2024 IEEE International Conference on Robotics and Biomimetics (ROBIO)

Year: 2024 | Conference Paper |

Force distribution measurement to investigate dexterous manipulation of hand

Hiroshi Hashimoto;Akinori Sasaki;Sho Yokota;Yasuhiro Ohyama;Chihiro Ishii

2011 IEEE International Conference on Mechatronics

Year: 2011 | Conference Paper |

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This paper presents a force distribution measurement system to investigate dexterous manipulation of hand. The purpose of this measurement is to find good shape designs not away from the hand easily when the object is dexterously manipulated by hand. To do this, it is necessary to examine the force distribution generating on a contact point between the hand and the object. We have developed the me...Show More

Force distribution measurement to investigate dexterous manipulation of hand

Hiroshi Hashimoto;Akinori Sasaki;Sho Yokota;Yasuhiro Ohyama;Chihiro Ishii

2011 IEEE International Conference on Mechatronics

Year: 2011 | Conference Paper |

Mobile Robot Manipulation System with a Reconfigurable Robotic Arm: Design and Experiment

Peng Kang;Liang Han;Wenfu Xu;Peng Wang;Guo Yang

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)

Year: 2019 | Conference Paper |

Cited by: Papers (2)

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Working in unknown environment has become a fundamental requirement of mobile robot manipulation system. This application scenarios require robots to have some basic capabilities, such as the fast and flexible locomotion, dexterous manipulation, and environmental interaction. However, most studies have only focus on just one of the aspects, which restricts the actual applications. This paper attem...Show More

Mobile Robot Manipulation System with a Reconfigurable Robotic Arm: Design and Experiment

Peng Kang;Liang Han;Wenfu Xu;Peng Wang;Guo Yang

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)

Year: 2019 | Conference Paper |

Towards Complex and Continuous Manipulation: A Gesture Based Anthropomorphic Robotic Hand Design

Li Tian;Hanhui Li;Qifa Wang;Xuezeng Du;Jialin Tao;Jordan Sia Chong;Nadia Magnenat Thalmann;Jianmin Zheng

IEEE Robotics and Automation Letters

Year: 2021 | Volume: 6, Issue: 3 | Journal Article |

Cited by: Papers (11)

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Most current anthropomorphicrobotic hands can realize part of the human hand functions, particularly for object grasping. However, due to the complexity of the human hand, few current designs target at daily object manipulations, even for simple actions like rotating a pen. To tackle this problem, we introduce a gesture based framework, which adopts the widely-used 33 grasping gestures of Feix as ...Show More

Towards Complex and Continuous Manipulation: A Gesture Based Anthropomorphic Robotic Hand Design

Li Tian;Hanhui Li;Qifa Wang;Xuezeng Du;Jialin Tao;Jordan Sia Chong;Nadia Magnenat Thalmann;Jianmin Zheng

IEEE Robotics and Automation Letters

Year: 2021 | Volume: 6, Issue: 3 | Journal Article |

Goal-Conditioned Dual-Action Imitation Learning for Dexterous Dual-Arm Robot Manipulation

Heecheol Kim;Yoshiyuki Ohmura;Yasuo Kuniyoshi

IEEE Transactions on Robotics

Year: 2024 | Volume: 40 | Journal Article |

Cited by: Papers (7)

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Long-horizon dexterous robot manipulation of deformable objects, such as banana peeling, is a problematic task because of the difficulties in object modeling and a lack of knowledge about stable and dexterous manipulation skills. This article presents a goal-conditioned dual-action deep imitation learning (DIL) approach that can learn dexterous manipulation skills using human demonstration data. P...Show More

Goal-Conditioned Dual-Action Imitation Learning for Dexterous Dual-Arm Robot Manipulation

Heecheol Kim;Yoshiyuki Ohmura;Yasuo Kuniyoshi

IEEE Transactions on Robotics

Year: 2024 | Volume: 40 | Journal Article |

Laser-Actuated Multi-Fingered Hand for Dexterous Manipulation of Micro-Objects

Quang Minh Ta;Gulam Dastagir Khan;Xiang Li;Chien Chern Cheah

Year: 2023 | Volume: 11 | Journal Article |

Cited by: Papers (2)

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Dexterous robotic manipulation refers to the coordination of multiple fingers or manipulators to grasp and manipulate a target object. In past decades, various achievements have been established in dexterous robotic manipulation in the physical world. However, such dexterous ability is rarely found in nano/micro manipulation, which is mainly due to the difficulty in developing actuators and sensor...Show More

Laser-Actuated Multi-Fingered Hand for Dexterous Manipulation of Micro-Objects

Quang Minh Ta;Gulam Dastagir Khan;Xiang Li;Chien Chern Cheah

Year: 2023 | Volume: 11 | Journal Article |

Dexterous In-hand Manipulation by Guiding Exploration with Simple Sub-skill Controllers

Gagan Khandate;Cameron Paul Mehlman;Xingsheng Wei;Matei Ciocarlie

2024 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2024 | Conference Paper |

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Recently, reinforcement learning has led to dexterous manipulation skills of increasing complexity. Nonetheless, learning these skills in simulation still exhibits poor sample-efficiency which stems from the fact these skills are learned from scratch without the benefit of any domain expertise. In this work, we aim to improve the sample efficiency of learning dexterous in-hand manipulation skills ...Show More

Dexterous In-hand Manipulation by Guiding Exploration with Simple Sub-skill Controllers

Gagan Khandate;Cameron Paul Mehlman;Xingsheng Wei;Matei Ciocarlie

2024 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2024 | Conference Paper |

Enhancing Dexterity in Robotic Manipulation via Hierarchical Contact Exploration

Xianyi Cheng;Sarvesh Patil;Zeynep Temel;Oliver Kroemer;Matthew T. Mason

IEEE Robotics and Automation Letters

Year: 2024 | Volume: 9, Issue: 1 | Journal Article |

Cited by: Papers (6)

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Planning robot dexterity is challenging due to the non-smoothness introduced by contacts, intricate fine motions, and ever-changing scenarios. We present a hierarchical planning framework for dexterous robotic manipulation (HiDex). This framework explores in-hand and extrinsic dexterity by leveraging contacts. It generates rigid-body motions and complex contact sequences. Our framework is based on...Show More

Enhancing Dexterity in Robotic Manipulation via Hierarchical Contact Exploration

Xianyi Cheng;Sarvesh Patil;Zeynep Temel;Oliver Kroemer;Matthew T. Mason

IEEE Robotics and Automation Letters

Year: 2024 | Volume: 9, Issue: 1 | Journal Article |

Towards a functional evaluation of manipulation performance in dexterous robotic hand design

Maximo A. Roa;Zhaopeng Chen;Irene C. Staal;Jared N. Muirhead;Annika Maier;Benedikt Pleintinger;Christoph Borst;Neal Y. Lii

2014 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2014 | Conference Paper |

Cited by: Papers (8)

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Dexterous multifingered hands are the most complex and versatile variants of robotic end effectors. Compared to simpler grippers and underactuated hands, they should be more capable of grasping and, especially, manipulating different objects. This paper explores the relationship between kinematic design and manipulation performance of robotic hands. Some evaluation criteria frequently used by hand...Show More

Towards a functional evaluation of manipulation performance in dexterous robotic hand design

Maximo A. Roa;Zhaopeng Chen;Irene C. Staal;Jared N. Muirhead;Annika Maier;Benedikt Pleintinger;Christoph Borst;Neal Y. Lii

2014 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2014 | Conference Paper |

DeltaHands: A Synergistic Dexterous Hand Framework Based on Delta Robots

Zilin Si;Kevin Zhang;Oliver Kroemer;Fatma Zeynep Temel

IEEE Robotics and Automation Letters

Year: 2024 | Volume: 9, Issue: 2 | Journal Article |

Cited by: Papers (1)

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Dexterous robotic manipulation in unstructured environments can aid in everyday tasks such as cleaning and caretaking. Anthropomorphic robotic hands are highly dexterous and theoretically well-suited for working in human domains, but their complex designs and dynamics often make them difficult to control. By contrast, parallel-jaw grippers are easy to control and are used extensively in industrial...Show More

DeltaHands: A Synergistic Dexterous Hand Framework Based on Delta Robots

Zilin Si;Kevin Zhang;Oliver Kroemer;Fatma Zeynep Temel

IEEE Robotics and Automation Letters

Year: 2024 | Volume: 9, Issue: 2 | Journal Article |

Learning Continuous Grasping Function With a Dexterous Hand From Human Demonstrations

Jianglong Ye;Jiashun Wang;Binghao Huang;Yuzhe Qin;Xiaolong Wang

IEEE Robotics and Automation Letters

Year: 2023 | Volume: 8, Issue: 5 | Journal Article |

Cited by: Papers (25)

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We propose to learn to generate grasping motion for manipulation with a dexterous hand using implicit functions. With continuous time inputs, the model can generate a continuous and smooth grasping plan. We name the proposed model Continuous Grasping Function (CGF). CGF is learned via generative modeling with a Conditional Variational Autoencoder using 3D human demonstrations. We will first conver...Show More

Learning Continuous Grasping Function With a Dexterous Hand From Human Demonstrations

Jianglong Ye;Jiashun Wang;Binghao Huang;Yuzhe Qin;Xiaolong Wang

IEEE Robotics and Automation Letters

Year: 2023 | Volume: 8, Issue: 5 | Journal Article |

Toward Human-Like Grasp: Functional Grasp by Dexterous Robotic Hand Via Object-Hand Semantic Representation

Tianqiang Zhu;Rina Wu;Jinglue Hang;Xiangbo Lin;Yi Sun

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2023 | Volume: 45, Issue: 10 | Journal Article |

Cited by: Papers (7)

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Intelligent robotic manipulation is a challenging study of machine intelligence. Although many dexterous robotic hands have been designed to assist or replace human hands in executing various tasks, how to teach them to perform dexterous operations like human hands is still a challenge. This motivates us to conduct an in-depth analysis of human behavior in manipulating objects and propose an objec...Show More

Toward Human-Like Grasp: Functional Grasp by Dexterous Robotic Hand Via Object-Hand Semantic Representation

Tianqiang Zhu;Rina Wu;Jinglue Hang;Xiangbo Lin;Yi Sun

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2023 | Volume: 45, Issue: 10 | Journal Article |

A New Four-Fingered Robot Hand with Dual Turning Mechanism

M. Higashimori;Hieyong Jeong;I. Ishii;M. Kaneko;A. Namiki;M. Ishikawa

Proceedings of the 2005 IEEE International Conference on Robotics and Automation

Year: 2005 | Conference Paper |

Cited by: Papers (17)

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This paper newly proposes the four-fingered robot hand with dual turning mechanism where two and two other fingers can independently rotate inner and outer circles with the common center, respectively. Due to this mechanical configuration, it has the particular rotating axis where the manipulation around the axis can be completely decomposed into the velocity control around the axis and the intern...Show More

A New Four-Fingered Robot Hand with Dual Turning Mechanism

M. Higashimori;Hieyong Jeong;I. Ishii;M. Kaneko;A. Namiki;M. Ishikawa

Proceedings of the 2005 IEEE International Conference on Robotics and Automation

Year: 2005 | Conference Paper |

A new force/torque sensor for robotic applications based on optoelectronic components

C. Melchiorri;L. Moriello;G. Palli;U. Scarcia

2014 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2014 | Conference Paper |

Cited by: Papers (12)

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In this paper, a novel force/torque sensor is presented. The sensor is based on optoelectronic components and therefore its design is relatively simple and reliable. The sensor design make it suitable for the integration in different robotic systems, such as e.g. the fingers of robotic hands. The basic principle and the design of the sensor are described in this paper, along with a specific protot...Show More

A new force/torque sensor for robotic applications based on optoelectronic components

C. Melchiorri;L. Moriello;G. Palli;U. Scarcia

2014 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2014 | Conference Paper |

Study of dexterous robotic grasping for deformable objects manipulation

D. Mira;A. Delgado;C. M. Mateo;S. T. Puente;F. A. Candelas;F. Torres

2015 23rd Mediterranean Conference on Control and Automation (MED)

Year: 2015 | Conference Paper |

Cited by: Papers (8)

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Most works in dexterous manipulation consider Force Closure Grasp (FCG), not only for rigid object but also, for flexible ones, though in the second case a force readjustment is also necessary. However, there are situations in which FCG is nonviable. This paper deals with the situation of a flexible object that must be necessarily grasped from one of its sides, taking advantage of its flexibility....Show More

Study of dexterous robotic grasping for deformable objects manipulation

D. Mira;A. Delgado;C. M. Mateo;S. T. Puente;F. A. Candelas;F. Torres

2015 23rd Mediterranean Conference on Control and Automation (MED)

Year: 2015 | Conference Paper |

A Bio-inspired Method for Friction Estimation

Rosana Matuk Herrera

2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)

Year: 2007 | Conference Paper |

Cited by: Papers (3)

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Few years old children lift and manipulate unfamiliar objects more dexterously than todaypsilas robots. Therefore, it has arisen an interest at the artificial intelligence community to look for inspiration on neurophysiological studies to design better models for the robots. The estimation of the friction coefficient of the objectpsilas material is a crucial information in a human dexterous manipu...Show More

A Bio-inspired Method for Friction Estimation

Rosana Matuk Herrera

2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)

Year: 2007 | Conference Paper |

Parametrized 2D/3D Garment Model For Dexterous Robotic Manipulation

Cheong Hou Yew;Khairul Salleh Mohamed Sahari;Tze How Dickson Neoh

2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS)

Year: 2018 | Conference Paper |

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The home service robot becomes a new dominant challenge for robotic researches especially for the development of the smart home system. The home service robot are used for nursing care service purposes which also designed to handle multiple types of house tasks such as garment folding. This work considers the problem of recognizing the configuration of the garment that already crudely spread-out o...Show More

Parametrized 2D/3D Garment Model For Dexterous Robotic Manipulation

Cheong Hou Yew;Khairul Salleh Mohamed Sahari;Tze How Dickson Neoh

2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS)

Year: 2018 | Conference Paper |

Vision-Based Demonstration Data Collection Platform for Dexterous Robot Manipulation

Sunme Park;Mingi Jung;Seungwon Lee;Yeongki Baek;Jongbum Park

2024 24th International Conference on Control, Automation and Systems (ICCAS)

Year: 2024 | Conference Paper |

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This paper presents a vision-based demonstration data collection platform designed to facilitate dexterous robot manipulation for the relocation task. The platform comprises three stages: video capture, pose estimation, and retargeting to the robotic hand, which is then mapped into a simulation environment for behavior learning. To ensure the quality of data for reinforcement learning and imitatio...Show More

Vision-Based Demonstration Data Collection Platform for Dexterous Robot Manipulation

Sunme Park;Mingi Jung;Seungwon Lee;Yeongki Baek;Jongbum Park

2024 24th International Conference on Control, Automation and Systems (ICCAS)

Year: 2024 | Conference Paper |

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