Publications
2013
11.
Inaki Rano; Ioannis Iossifidis
Modelling human arm motion through the attractor dynamics approach Inproceedings
In: 2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013, pp. 2088–2093, 2013, ISBN: 9781479927449.
Abstract | Links | BibTeX | Tags: arm movement model, dynamical systems, movement model, Robotics
@inproceedings{Rano2013b,
title = {Modelling human arm motion through the attractor dynamics approach},
author = {Inaki Rano and Ioannis Iossifidis},
doi = {10.1109/ROBIO.2013.6739777},
isbn = {9781479927449},
year = {2013},
date = {2013-01-01},
booktitle = {2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013},
pages = {2088--2093},
abstract = {Movement generation in robotics is an old problem with many excellent solutions. Most of them, however, look for optimality according to some metrics, but have no biological inspiration or cannot be used to imitate biological motion. For a human these techniques behave in a non-naturalistic way. This poses a problem for instance in human-robot interaction and, in general, for a good acceptance of robots in society. The present work presents a new analysis of the attractor dynamics approach to movement generation used in an anthropomorphic robot arm. Our analysis points to the possibility of using this approach to generate human-like arm trajectories in robots. One key property of human trajectories in pick-and-place tasks is the planarity of the trajectory of the end effector in 3D space. We show that this feature is also displayed by the attractor dynamic approach and, therefore, is a good candidate to the generation of naturalistic arm movements. textcopyright 2013 IEEE.},
keywords = {arm movement model, dynamical systems, movement model, Robotics},
pubstate = {published},
tppubtype = {inproceedings}
}
Movement generation in robotics is an old problem with many excellent solutions. Most of them, however, look for optimality according to some metrics, but have no biological inspiration or cannot be used to imitate biological motion. For a human these techniques behave in a non-naturalistic way. This poses a problem for instance in human-robot interaction and, in general, for a good acceptance of robots in society. The present work presents a new analysis of the attractor dynamics approach to movement generation used in an anthropomorphic robot arm. Our analysis points to the possibility of using this approach to generate human-like arm trajectories in robots. One key property of human trajectories in pick-and-place tasks is the planarity of the trajectory of the end effector in 3D space. We show that this feature is also displayed by the attractor dynamic approach and, therefore, is a good candidate to the generation of naturalistic arm movements. textcopyright 2013 IEEE.
10.
Ioannis Iossifidis; Ianki Rano
Modeling Human Arm Motion by Means of Attractor Dynamics Approach Inproceedings
In: Proc. IEEE/RSJ International Conference on Robotics and Biomimetics (RoBio2013), 2013.
Abstract | BibTeX | Tags: arm movement model, dynamical systems, movement model, Robotics
@inproceedings{Iossifidis2013ac,
title = {Modeling Human Arm Motion by Means of Attractor Dynamics Approach},
author = {Ioannis Iossifidis and Ianki Rano},
year = {2013},
date = {2013-01-01},
booktitle = {Proc. IEEE/RSJ International Conference on Robotics and Biomimetics (RoBio2013)},
abstract = {Autonomous robots with limited computational capacity call for control approaches that generate meaningful, goal-directed behavior without using a large amount of resources. The attractor dynamics approach to movement generation is a framework that links sensor data to motor commands via coupled dynamical systems that have attractors at behaviorally desired states. The low computational demands leave enough system resources for higher level function like forming a sequence of local goals to reach a distant one. The comparatively high performance of local behavior generation allows the global planning to be relatively simple.
In the present paper, we apply this approach to generate walking trajectories for a small humanoid robot, the Aldebaran Nao, that are goal-directed and avoid obstacles. The sensor information is a single camera in the head of the robot. The limited field of vision is compensated by head movements. The design of the dynamical system for motion generation and the choice of state variable makes a computationally expensive scene representation or local map building unnecessary.},
keywords = {arm movement model, dynamical systems, movement model, Robotics},
pubstate = {published},
tppubtype = {inproceedings}
}
Autonomous robots with limited computational capacity call for control approaches that generate meaningful, goal-directed behavior without using a large amount of resources. The attractor dynamics approach to movement generation is a framework that links sensor data to motor commands via coupled dynamical systems that have attractors at behaviorally desired states. The low computational demands leave enough system resources for higher level function like forming a sequence of local goals to reach a distant one. The comparatively high performance of local behavior generation allows the global planning to be relatively simple.
In the present paper, we apply this approach to generate walking trajectories for a small humanoid robot, the Aldebaran Nao, that are goal-directed and avoid obstacles. The sensor information is a single camera in the head of the robot. The limited field of vision is compensated by head movements. The design of the dynamical system for motion generation and the choice of state variable makes a computationally expensive scene representation or local map building unnecessary.
In the present paper, we apply this approach to generate walking trajectories for a small humanoid robot, the Aldebaran Nao, that are goal-directed and avoid obstacles. The sensor information is a single camera in the head of the robot. The limited field of vision is compensated by head movements. The design of the dynamical system for motion generation and the choice of state variable makes a computationally expensive scene representation or local map building unnecessary.
2010
9.
Hendrik Reimann; Ioannis Iossifidis; Gregor Schöner
End-effector obstacle avoidance using multiple dynamic variables Inproceedings
In: ISR / ROBOTIK 2010, Munich, Germany, 2010.
Abstract | BibTeX | Tags: arm movement model, behavior generation, dynamical systems, movement model, obstacle avoidance, Robotics
@inproceedings{Reimanndb,
title = {End-effector obstacle avoidance using multiple dynamic variables},
author = {Hendrik Reimann and Ioannis Iossifidis and Gregor Schöner},
year = {2010},
date = {2010-01-01},
booktitle = {ISR / ROBOTIK 2010},
address = {Munich, Germany},
abstract = {The avoidance of obstacles is a crucial part of the generation of behavior for autonomos robotic agents. A standard method to produce trajectories to a given target that avoids a number of possibly mobile obstacles is the potential field approach introduced by Khatib, where an artificial potential field is constructed around target and obstacles, with the target acting as a global minimum and the obstacles as local maxima, the gradient of which is used to determine the (artificial) force acting on the robot at any moment. While the potential field approach has been used extensively for vehicle motion in a plane, applications for robotic manipulators suffer from a high level of complexity due to the formulation of constraints as forces necessitating the inclusion of dynamic properties of the manipulator into the system. We pursue a different solution to the problem of manipulator obstacle avoidance based on the dynamic approach to robotics, which states that all behavioral constraints for the generation of movement should be formulated as attractors or repellors of a dynamical systems. The problem of behavior design is thus separated from the control problem of how to realize the designed behavior, bringing the advantage of simplicity in the formulation of the former.},
keywords = {arm movement model, behavior generation, dynamical systems, movement model, obstacle avoidance, Robotics},
pubstate = {published},
tppubtype = {inproceedings}
}
The avoidance of obstacles is a crucial part of the generation of behavior for autonomos robotic agents. A standard method to produce trajectories to a given target that avoids a number of possibly mobile obstacles is the potential field approach introduced by Khatib, where an artificial potential field is constructed around target and obstacles, with the target acting as a global minimum and the obstacles as local maxima, the gradient of which is used to determine the (artificial) force acting on the robot at any moment. While the potential field approach has been used extensively for vehicle motion in a plane, applications for robotic manipulators suffer from a high level of complexity due to the formulation of constraints as forces necessitating the inclusion of dynamic properties of the manipulator into the system. We pursue a different solution to the problem of manipulator obstacle avoidance based on the dynamic approach to robotics, which states that all behavioral constraints for the generation of movement should be formulated as attractors or repellors of a dynamical systems. The problem of behavior design is thus separated from the control problem of how to realize the designed behavior, bringing the advantage of simplicity in the formulation of the former.
8.
Yulia Sandamirskaya; John Lipinski; Ioannis Iossifidis; G Schöner
Natural human-robot interaction through spatial language: a dynamic neural fields approach Inproceedings
In: Proc. 19th IEEE International Workshop on Robot and Human Interactive Communication (ROMAN 2010), pp. 600–607, IEEE, 2010, ISSN: 1944-9445.
Links | BibTeX | Tags: arm movement model, behavior generation, dynamical systems, man machine interaction, movement model, Robotics, speech recognition
@inproceedings{Sandamirskayasubmittedb,
title = {Natural human-robot interaction through spatial language: a dynamic neural fields approach},
author = {Yulia Sandamirskaya and John Lipinski and Ioannis Iossifidis and G Schöner},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5598671},
issn = {1944-9445},
year = {2010},
date = {2010-01-01},
booktitle = {Proc. 19th IEEE International Workshop on Robot and Human Interactive Communication (ROMAN 2010)},
pages = {600--607},
publisher = {IEEE},
keywords = {arm movement model, behavior generation, dynamical systems, man machine interaction, movement model, Robotics, speech recognition},
pubstate = {published},
tppubtype = {inproceedings}
}
2005
7.
Ioannis Iossifidis; A Steinhage
Behavior generation for Anthropomorphic robots by means of dynamical systems Book
2005, ISSN: 16107438.
Abstract | BibTeX | Tags: arm movement model, behavior generation, dynamical systems, movement model, Robotics
@book{Iossifidis2005cb,
title = {Behavior generation for Anthropomorphic robots by means of dynamical systems},
author = {Ioannis Iossifidis and A Steinhage},
issn = {16107438},
year = {2005},
date = {2005-01-01},
urldate = {2005-01-01},
booktitle = {Springer Tracts in Advanced Robotics},
volume = {14},
abstract = {This article describes the current state of our research on anthropomorphic robots. Our aim is to make the reader familiar with the two basic principles our work is based on: anthropomorphism and dynamics. The principle of anthropomorphism means a restriction to human-like robots which use version, audition and touch as their only sensors so that natural man-machine interaction is possible. The principle of dynamics stands for the mathematical framework based on which our robots generate their behavior. Both principles have their root in the idea that concepts of biological behavior and information processing can be exploited to control technical systems. textcopyright Springer-Verlag Berlin Heidelberg 2005.},
keywords = {arm movement model, behavior generation, dynamical systems, movement model, Robotics},
pubstate = {published},
tppubtype = {book}
}
This article describes the current state of our research on anthropomorphic robots. Our aim is to make the reader familiar with the two basic principles our work is based on: anthropomorphism and dynamics. The principle of anthropomorphism means a restriction to human-like robots which use version, audition and touch as their only sensors so that natural man-machine interaction is possible. The principle of dynamics stands for the mathematical framework based on which our robots generate their behavior. Both principles have their root in the idea that concepts of biological behavior and information processing can be exploited to control technical systems. textcopyright Springer-Verlag Berlin Heidelberg 2005.
2004
6.
Erwin Prassler; Gisbert Lawitzky; Andreas Stopp; Gerhard Grunwald; Martin Ħägele; Rüdiger Đillmann; Ioannis Iossifidis
Advances in Ħuman Robot Interaction Book
Springer Press, 2004.
Abstract | Links | BibTeX | Tags: arm movement model, behavior generation, dynamical systems, movement model, Robotics
@book{Prassler2004d,
title = {Advances in Ħuman Robot Interaction},
author = {Erwin Prassler and Gisbert Lawitzky and Andreas Stopp and Gerhard Grunwald and Martin Ħägele and Rüdiger Đillmann and Ioannis Iossifidis},
editor = {Erwin Prassler and Gisbert Lawitzky and Andreas Stopp and Gerhard Grunwald and Martin Ħägele and Rüdiger Đillmann and Ioannis Iossifidis},
url = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,5-102-22-35029562-0,00.html?changeHeader=true},
year = {2004},
date = {2004-01-01},
booktitle = {Advances in Ħuman Robot Interaction},
volume = {14/2004},
number = {ISBN: 3-540-23211-7},
pages = {414},
publisher = {Springer Press},
series = {Springer Tracts in Advanced Robotics STAR},
abstract = {Human Robot Interaction and Cooperation
Motion Coordination
Multi-Modal Robot Interfaces
Physical Interaction between Humans and Robots
Robot Learning
Visual Instruction of Robots},
keywords = {arm movement model, behavior generation, dynamical systems, movement model, Robotics},
pubstate = {published},
tppubtype = {book}
}
Human Robot Interaction and Cooperation
Motion Coordination
Multi-Modal Robot Interfaces
Physical Interaction between Humans and Robots
Robot Learning
Visual Instruction of Robots
Motion Coordination
Multi-Modal Robot Interfaces
Physical Interaction between Humans and Robots
Robot Learning
Visual Instruction of Robots
5.
Ioannis Iossifidis; Gregor Schöner
Attractor dynamics approach for autonomous collision-free path generation in 3d-space for an 7 dof robot arm Inproceedings
In: Proceedings of the ROBOTIK 2004, Leistungsstand - Anwendungen - Visionen - Trends, number 1841 in VDI-Berichte, pp. 815–822, VDI/VDE VDI Verlag, München, Germany, 2004.
BibTeX | Tags: arm movement model, collision avoidance, dynamical systems, Inverse kinematics, movement model, Robotics
@inproceedings{Iossifidis2004ab,
title = {Attractor dynamics approach for autonomous collision-free path generation in 3d-space for an 7 dof robot arm},
author = {Ioannis Iossifidis and Gregor Schöner},
year = {2004},
date = {2004-01-01},
booktitle = {Proceedings of the ROBOTIK 2004, Leistungsstand - Anwendungen - Visionen - Trends, number 1841 in VDI-Berichte},
pages = {815--822},
publisher = {VDI Verlag},
address = {München, Germany},
organization = {VDI/VDE},
keywords = {arm movement model, collision avoidance, dynamical systems, Inverse kinematics, movement model, Robotics},
pubstate = {published},
tppubtype = {inproceedings}
}
4.
Ioannis Iossifidis; Carsten Bruckhoff; Christoph Theis; Claudia Grote; Christian Faubel; Gregor Schöner
A Cooperative Robot Assistant CoRA For Human Environments Incollection
In: Prassler, Erwin; Lawitzky, Gisbert; Stopp, Andreas; Grunwald, Gerhard; Hägele, Martin; Dillmann, Rüdiger; Iossifidis, Ioannis (Ed.): Advances in Human Robot Interaction, vol. 14/2004, no. ISBN: 3-540-23211-7,, pp. 385–401, Springer Press, 2004, ISBN: 3-540-23211-7,.
Abstract | Links | BibTeX | Tags: arm movement model, behavior generation, dynamical systems, movement model, Robotics
@incollection{Iossifidis2004db,
title = {A Cooperative Robot Assistant CoRA For Human Environments},
author = {Ioannis Iossifidis and Carsten Bruckhoff and Christoph Theis and Claudia Grote and Christian Faubel and Gregor Schöner},
editor = {Erwin Prassler and Gisbert Lawitzky and Andreas Stopp and Gerhard Grunwald and Martin Hägele and Rüdiger Dillmann and Ioannis Iossifidis},
url = {http://www.springerlink.com/index/91656F7B99CD2C2C},
doi = {10.1007/b97960},
isbn = {3-540-23211-7,},
year = {2004},
date = {2004-01-01},
booktitle = {Advances in Human Robot Interaction},
volume = {14/2004},
number = {ISBN: 3-540-23211-7,},
pages = {385--401},
publisher = {Springer Press},
chapter = {7},
series = {Springer Tracts in Advanced Robotics STAR},
abstract = {CoRA is a robotic assistant whose task is to collaborate with a human operator on simple manipulation or handling tasks. Its sensory channels comprising vision, audition, haptics, and force sensing are used to extract perceptual information about speech, gestures and gaze of the operator, and object recognition. The anthropomorphic robot arm makes goal-directed movements to pick up and hand-over objects. The human operator may mechanically interact with the arm by pushing it away (haptics) or by taking an object out of the robotrsquos gripper (force sensing). The design objective has been to exploit the human operatorrsquos intuition by modeling the mechanical structure, the senses, and the behaviors of the assistant on human anatomy, human perception, and human motor behavior.},
keywords = {arm movement model, behavior generation, dynamical systems, movement model, Robotics},
pubstate = {published},
tppubtype = {incollection}
}
CoRA is a robotic assistant whose task is to collaborate with a human operator on simple manipulation or handling tasks. Its sensory channels comprising vision, audition, haptics, and force sensing are used to extract perceptual information about speech, gestures and gaze of the operator, and object recognition. The anthropomorphic robot arm makes goal-directed movements to pick up and hand-over objects. The human operator may mechanically interact with the arm by pushing it away (haptics) or by taking an object out of the robotrsquos gripper (force sensing). The design objective has been to exploit the human operatorrsquos intuition by modeling the mechanical structure, the senses, and the behaviors of the assistant on human anatomy, human perception, and human motor behavior.
3.
Ioannis Iossifidis; Axel Steinhage
Behavior Generation For Anthropomorphic Robots by Means of Dynamical Systems Incollection
In: Prassler, Erwin; Lawitzky, Gisbert; Stopp, Andreas; Grunwald, Gerhard; Hägele, Martin; Dillmann, Rüdiger; Iossifidis, Ioannis (Ed.): Advances in Human Robot Interaction, vol. 14/2004, no. ISBN: 3-540-23211-7,, pp. 269–300, Springer Press, 2004, ISBN: 3-540-23211-7,.
Abstract | Links | BibTeX | Tags: arm movement model, behavior generation, dynamical systems, movement model, Robotics
@incollection{Iossifidis2004eb,
title = {Behavior Generation For Anthropomorphic Robots by Means of Dynamical Systems},
author = {Ioannis Iossifidis and Axel Steinhage},
editor = {Erwin Prassler and Gisbert Lawitzky and Andreas Stopp and Gerhard Grunwald and Martin Hägele and Rüdiger Dillmann and Ioannis Iossifidis},
url = {http://www.springerlink.com/index/96DD6AB012CF71E7},
doi = {0.1007/b97960},
isbn = {3-540-23211-7,},
year = {2004},
date = {2004-01-01},
booktitle = {Advances in Human Robot Interaction},
volume = {14/2004},
number = {ISBN: 3-540-23211-7,},
pages = {269--300},
publisher = {Springer Press},
chapter = {6},
series = {Springer Tracts in Advanced Robotics STAR},
abstract = {This article describes the current state of our research on anthropomorphic robots. Our aim is to make the reader familiar with the two basic principles our work is based on: anthropomorphism and dynamics. The principle of anthropomorphism means a restriction to human-like robots which use version, audition and touch as their only sensors so that natural man-machine interaction is possible. The principle of dynamics stands for the mathematical framework based on which our robots generate their behavior. Both principles have their root in the idea that concepts of biological behavior and information processing can be exploited to control technical systems.},
keywords = {arm movement model, behavior generation, dynamical systems, movement model, Robotics},
pubstate = {published},
tppubtype = {incollection}
}
This article describes the current state of our research on anthropomorphic robots. Our aim is to make the reader familiar with the two basic principles our work is based on: anthropomorphism and dynamics. The principle of anthropomorphism means a restriction to human-like robots which use version, audition and touch as their only sensors so that natural man-machine interaction is possible. The principle of dynamics stands for the mathematical framework based on which our robots generate their behavior. Both principles have their root in the idea that concepts of biological behavior and information processing can be exploited to control technical systems.
2.
Erwin Prassler; Gisbert Lawitzky; Andreas Stopp; Gerhard Grunwald; Martin Hägele; Rüdiger Dillmann; Ioannis Iossifidis
Advances in Human Robot Interaction Book
Springer Press, 2004.
Abstract | Links | BibTeX | Tags: arm movement model, behavior generation, dynamical systems, Inverse kinematics, movement model, redundant robot arm, Robotics
@book{Prassler2004bb,
title = {Advances in Human Robot Interaction},
author = {Erwin Prassler and Gisbert Lawitzky and Andreas Stopp and Gerhard Grunwald and Martin Hägele and Rüdiger Dillmann and Ioannis Iossifidis},
editor = {Erwin Prassler and Gisbert Lawitzky and Andreas Stopp and Gerhard Grunwald and Martin Hägele and Rüdiger Dillmann and Ioannis Iossifidis},
url = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,5-102-22-35029562-0,00.html?changeHeader=true},
year = {2004},
date = {2004-01-01},
booktitle = {Advances in Human Robot Interaction},
volume = {14/2004},
pages = {414},
publisher = {Springer Press},
series = {Springer Tracts in Advanced Robotics STAR},
abstract = {Human Robot Interaction and Cooperation Motion Coordination Multi-Modal Robot Interfaces Physical Interaction between Humans and Robots Robot Learning Visual Instruction of Robots},
keywords = {arm movement model, behavior generation, dynamical systems, Inverse kinematics, movement model, redundant robot arm, Robotics},
pubstate = {published},
tppubtype = {book}
}
Human Robot Interaction and Cooperation Motion Coordination Multi-Modal Robot Interfaces Physical Interaction between Humans and Robots Robot Learning Visual Instruction of Robots
1.
Erwin Prassler; Gisbert Lawitzky; Andreas Stopp; Gerhard Grunwald; Martin Hägele; Rüdiger Dillmann; Ioannis Iossifidis
Advances in Human Robot Interaction (Springer Tracts in Advanced Robotics) Book
Springer, 2004, ISBN: 3540232117.
Links | BibTeX | Tags: arm movement model, behavior generation, dynamical systems, Inverse kinematics, movement model, redundant robot arm, Robotics
@book{Prassler2004cb,
title = {Advances in Human Robot Interaction (Springer Tracts in Advanced Robotics)},
author = {Erwin Prassler and Gisbert Lawitzky and Andreas Stopp and Gerhard Grunwald and Martin Hägele and Rüdiger Dillmann and Ioannis Iossifidis},
url = {http://www.amazon.co.uk/Advances-Interaction-Springer-Advanced-Robotics/dp/3540232117},
isbn = {3540232117},
year = {2004},
date = {2004-01-01},
pages = {414},
publisher = {Springer},
keywords = {arm movement model, behavior generation, dynamical systems, Inverse kinematics, movement model, redundant robot arm, Robotics},
pubstate = {published},
tppubtype = {book}
}