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13th IEEE International Conference on Rehabilitation robotics (ICORR)

作者： Liarokapis, Minas V. Artemiadis, Panagiotis K. Kyriakopoulos, Kostas J. Natl Tech Univ Athens Sch Mech Engn Control Syst Lab 9 Heroon Polytech Str Athens 15780 Greece Arizona State Univ Ira A Fulton Sch Engn Sch Engn Matter Transport & Energy ASU Human Oriented Robot & Control HORC Lab Tempe AZ 85287 USA

ISBN: (纸本)9781467360241;9781467360227

A learning scheme based on Random Forests is used to discriminate the task to be executed using only myoelectric activity from the upper limb. Three different task features can be discriminated: subspace to move towards, object to be grasped and task to be executed (with the object). The discrimination between the different reach to grasp movements is accomplished with a random forests classifier, which is able to perform efficient features selection, helping us to reduce the number of EMG channels required for task discrimination. The proposed scheme can take advantage of both a classifier and a regressor that cooperate advantageously to split the task space, providing better estimation accuracy with task-specific EMG-based motion decoding models, as reported in [1] and [2]. The whole learning scheme can be used by a series of EMG-based interfaces, that can be found in rehabilitation cases and neural prostheses.

关键词： ElectroMyoGraphy (EMG) Learning Scheme Task Specificity Random Forests

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Quantifying Anthropomorphism of Robot Hands

Quantifying Anthropomorphism of Robot Hands

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IEEE International Conference on robotics and Automation (ICRA)

作者： Liarokapis, Minas V. Artemiadis, Panagiotis K. Kyriakopoulos, Kostas J. Natl Tech Univ Athens Sch Mech Engn Control Syst Lab 9 Heroon Polytech Str Athens 15780 Greece Arizona State Univ Ira A Fulton Sch Engn Tempe AZ 85287 USA Arizona State Univ ASU Human Oriented Robot & Control Lab Sch Engn Matter Tempe AZ 85287 USA

ISBN: (纸本)9781467356411;9781467356435

In this paper a comparative analysis between the human and three robotic hands is conducted. A series of metrics are introduced to quantify anthropomorphism and assess robot's ability to mimic the human hand. In order to quantify anthropomorphism we choose to compare human and robot hands in two different levels: comparing finger phalanges workspaces and comparing workspaces of the fingers base frames. The final score of anthropomorphism uses a set of weighting factors that can be adjusted according to the specifications of each study, providing always a normalized score between 0 (non-anthropomorphic) and 1 (human-identical). The proposed methodology can be used in order to grade the human-likeness of existing and new robotic hands, as well as to provide specifications for the design of the next generation of anthropomorphic hands. Those hands can be used for human robot interaction applications, humanoids or even prostheses.

关键词： Anthropomorphism Robot Hands Kinematics Workspace Analysis

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Telemanipulation with the DLR/HIT II Robot Hand Using a Dataglove and a Low Cost Force Feedback Device

Telemanipulation with the DLR/HIT II Robot Hand Using a Data...

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21st Mediterranean Conference on control and Automation (MED)

作者： Liarokapis, Minas V. Artemiadis, Panagiotis K. Kyriakopoulos, Kostas J. Natl Tech Univ Athens Sch Mech Engn Control Syst Lab 9 Heroon Polytechniou Str Athens 15780 Greece Arizona State Univ ASU Human Oriented Robot & Control HORC Lab Sch Engn Matter Taransport & Energy Tempe AZ 85287 USA Arizona State Univ Sch Engn Tempe AZ 85287 USA

ISBN: (纸本)9781479909957;9781479909971

In this paper a series of teleoperation and manipulation tasks are performed with the five fingered robot hand DLR/HIT II. Two different everyday life objects are used for the manipulation tasks;a small ball and a rectangular object. The joint-to-joint mapping methodology is used to map human to robot hand motion, taking into account existing kinematic constraints such as synergistic characteristics and joint couplings. The Cyberglove II motion capture dataglove is used to measure human hand kinematics. A robot hand specific fast calibration procedure is used to map raw dataglove sensor values to human joint angles and subsequently through the mapping procedure, to DLR/HIT II joint angles. A novel low cost force feedback device is developed, in order for the user to be able to detect contact and perceive the forces exerted by the robot fingertips, during manipulation tasks. The design of the force feedback device is based on RGB LEDs that provide visual feedback and vibration motors that provide vibrotactile feedback.

关键词： Telemanipulation Teleoperation Force Feedback Device Mapping human to Robot Motion

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Telemanipulation with the DLR/HIT II Robot Hand Using a Dataglove and a Low Cost Force Feedback Device

Telemanipulation with the DLR/HIT II Robot Hand Using a Data...

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Mediterranean Conference on control & Automation

作者： Minas V. Liarokapis Panagiotis K. Artemiadis Kostas J. Kyriakopoulos Control Systems Lab School of Mechanical Engineering National Technical University of Athens ASU Human-Oriented Robotics and Control (HORC) Lab School for Engineering of Matter Transport and Energy Ira A. Fulton Schools of Engineering Arizona State University

ISBN: (纸本)9781479909964

关键词： Telemanipulation Teleoperation Force Feedback Device Mapping human to Robot Motion

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A Learning Scheme for Reach to Grasp Movements: On EMG-Based Interfaces Using Task Specific Motion Decoding Models

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IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 2013年第5期17卷 915-921页

作者： Liarokapis, Minas V. Artemiadis, Panagiotis K. Kyriakopoulos, Kostas J. Manolakos, Elias S. Natl Tech Univ Athens Sch Mech Engn Control Syst Lab GR-10682 Athens Greece Arizona State Univ ASU Human Oriented Robot & Control HORC Lab Sch Engn Matter Transport & Energy Tempe AZ 85287 USA Univ Athens Dept Informat & Telecommun GR-10679 Athens Greece

A learning scheme based on random forests is used to discriminate between different reach to grasp movements in 3-D space, based on the myoelectric activity of human muscles of the upper-arm and the forearm. Task specificity for motion decoding is introduced in two different levels: Subspace to move toward and object to be grasped. The discrimination between the different reach to grasp strategies is accomplished with machine learning techniques for classification. The classification decision is then used in order to trigger an EMG-based task-specific motion decoding model. Task specific models manage to outperform "general" models providing better estimation accuracy. Thus, the proposed scheme takes advantage of a framework incorporating both a classifier and a regressor that cooperate advantageously in order to split the task space. The proposed learning scheme can be easily used to a series of EMG-based interfaces that must operate in real time, providing data-driven capabilities for multiclass problems, that occur in everyday life complex environments.

关键词： Electromyography (EMG) learning scheme random forests task specificity

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Quantifying anthropomorphism of robot hands

Quantifying anthropomorphism of robot hands

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IEEE International Conference on robotics and Automation (ICRA)

作者： Minas V. Liarokapis Panagiotis K. Artemiadis Kostas J. Kyriakopoulos Control Systems Laboratory School of Mechanical Engineering National Technical University of Athens Athens Greece ASU Human-Oriented Robotics and Control (HORC) Laboratory School for Engineering of Matter Transport andEnergy Ira A. Fulton Schools of Engineering Arizona State University Tempe AZ USA

ISBN: (纸本)9781467356404

关键词： Robots Anthropomorphism Thumb Indexes Kinematics Joints

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Mapping human to Robot Motion with Functional Anthropomorphism for Teleoperation and Telemanipulation with Robot Arm Hand Systems

Mapping Human to Robot Motion with Functional Anthropomorphi...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Minas V. Liarokapis Panagiotis K. Artemiadis Kostas J. Kyriakopoulos Control Systems Lab School of Mechanical Engineering National Technical University of Athens 9 Heroon Polytechniou Str Athens 15780 Greece ASU Human-Oriented Robotics and Control (HORC) Lab School for Engineering of Matter Transport and Energy Ira A. Fulton Schools of Engineering Arizona State University 501 E. Tyler Mall ECG 301 Tempe AZ 85287-6106 USA

ISBN: (纸本)9781467363563

In this paper teleoperation and telemanipulation with a robot arm (Mitsubishi PA-10) and a robot hand (DLR/HIT 2) is performed, using a human to robot motion mapping scheme that guarantees anthropomorphism. Two position trackers are used to capture position and orientation of human end-effector (wrist) and human elbow in 3D space and a dataglove to capture human hand kinematics. Then the inverse kinematics (IK) of the Mitsubishi PA-10 7-DoF robot arm are solved in an analytical manner, in order for the human's and the robot artifact's end-effectors to achieve same position and orientation in 3D space (functional constraint). Redundancy is handled in the solution space of the robot arm's IK, selecting the most anthropomorphic solution computed, with a criterion of "Functional Anthropomorphism". human hand motion is transformed to robot hand motion using the joint-to-joint mapping methodology. Finally in order for the user to be able to detect contact and "perceive" the forces exerted by the robot hand, a low-cost force feedback device, that provides a mixture of sensory information (visual and vibrotactile), was developed.

关键词： Robot Arm Hand Systems IK wrist

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Task Discrimination from Myoelectric Activity: A Learning Scheme for EMG-Based Interfaces.

Task Discrimination from Myoelectric Activity: A Learning Sc...

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IEEE International Conference on Rehabilitation robotics

作者： Minas V. Liarokapis Panagiotis K. Artemiadis Kostas J. Kyriakopoulos Control Systems Lab School of Mechanical Engineering National Technical University of Athens 9 Heroon Polytechniou Str Athens 15780 Greece. ASU Human-Oriented Robotics and Control (HORC) Lab School for Engineering of Matter Transport and Energy Ira A. Fulton Schools of Engineering Arizona State University 501 E. Tyler Mall ECG 301 Tempe AZ 85287-6106 USA.

ISBN: (纸本)9781467360210

关键词： Task Discrimination Activity

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Relating postural synergies to low-D muscular activations: Towards bio-inspired control of robotic hands

Relating postural synergies to low-D muscular activations: T...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： P. T. Katsiaris P. K. Artemiadis K. J. Kyriakopoulos Control Systems Lab National Technical University of Athens ASU Human-Oriented Robotics and Control Lab Arizona State University USA

Studying human motor control has received increased attention during the past decades. Both the design and control of robotic artifacts may benefit from observation of human behavior. In this paper a novel method for capturing the dynamic behavior of the human hand is presented. The low dimensional kinematics of the human hand, including the wrist, and the low dimensional representation of the muscular activations were correlated through a linear time invariant (LTI) state space model. A linear output regulation controller was used in order to drive a simulated hand and the resulting trajectories were compared with the experimentally captured trajectories.

关键词： humans Kinematics Trajectory Aerospace electronics Robots Electromyography Muscles

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Relating Postural Synergies to Low-D Muscular Activations: Towards Bio-inspired control of Robotic Hands

Relating Postural Synergies to Low-D Muscular Activations: T...

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12th IEEE International Conference on BioInformatics and BioEngineering (BIBE)

作者： Katsiaris, P. T. Artemiadis, P. K. Kyriakopoulos, K. J. Natl Tech Univ Athens Control Syst Lab Sch Mech Eng GR-10682 Athens Greece Arizona State Univ Schools Engn Sch Engn Matter Transport & Energy ASU Human Oriented Robot & Control Lab Tempe AZ USA

ISBN: (纸本)9781467343589;9781467343572

关键词： State space methods

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