2021
Tim Sziburis; Susanne Blex; Tobias Glasmachers; Inaki Rano; Ioannis Iossifidis
Modelling the Generation of Human Upper-Limb Reaching Trajectories: An Extended Behavioural Attractor Dynamics Approach Proceedings Article
In: Bernstein Conference, 2021.
Links | BibTeX | Tags: attractor dynamics approach, human arm motion
@inproceedings{sziburisModellingGenerationHuman2021b,
title = {Modelling the Generation of Human Upper-Limb Reaching Trajectories: An Extended Behavioural Attractor Dynamics Approach},
author = {Tim Sziburis and Susanne Blex and Tobias Glasmachers and Inaki Rano and Ioannis Iossifidis},
doi = {10.12751/nncn.bc2021.p078},
year = {2021},
date = {2021-10-01},
urldate = {2021-10-01},
publisher = {Bernstein Conference},
keywords = {attractor dynamics approach, human arm motion},
pubstate = {published},
tppubtype = {inproceedings}
}
Sebastian Doliwa; Muhammad Ayaz Hussain; Tim Sziburis; Ioannis Iossifidis
Biologically Inspired Model for Timed Motion in Robotic Systems Journal Article
In: arXiv:2106.15864 [cs, math], 2021.
Abstract | BibTeX | Tags: attractor dynamics approach, Autonomous robotics, dynamical systems
@article{doliwaBiologicallyInspiredModel2021,
title = {Biologically Inspired Model for Timed Motion in Robotic Systems},
author = {Sebastian Doliwa and Muhammad Ayaz Hussain and Tim Sziburis and Ioannis Iossifidis},
year = {2021},
date = {2021-07-01},
urldate = {2021-07-01},
journal = {arXiv:2106.15864 [cs, math]},
abstract = {The goal of this work is the development of a motion model for sequentially timed movement actions in robotic systems under specific consideration of temporal stabilization, that is maintaining an approximately constant overall movement time (isochronous behavior). This is demonstrated both in simulation and on a physical robotic system for the task of intercepting a moving target in three-dimensional space. Motivated from humanoid motion, timing plays a vital role to generate a naturalistic behavior in interaction with the dynamic environment as well as adaptively planning and executing action sequences on-line. In biological systems, many of the physiological and anatomical functions follow a particular level of periodicity and stabilization, which exhibit a certain extent of resilience against external disturbances. A main aspect thereof is stabilizing movement timing against limited perturbations. Especially human arm movement, namely when it is tasked to reach a certain goal point, pose or configuration, shows a stabilizing behavior. This work incorporates the utilization of an extended Kalman filter (EKF) which was implemented to predict the target position while coping with non-linear system dynamics. The periodicity and temporal stabilization in biological systems was artificially generated by a Hopf oscillator, yielding a sinusoidal velocity profile for smooth and repeatable motion.},
keywords = {attractor dynamics approach, Autonomous robotics, dynamical systems},
pubstate = {published},
tppubtype = {article}
}
The goal of this work is the development of a motion model for sequentially timed movement actions in robotic systems under specific consideration of temporal stabilization, that is maintaining an approximately constant overall movement time (isochronous behavior). This is demonstrated both in simulation and on a physical robotic system for the task of intercepting a moving target in three-dimensional space. Motivated from humanoid motion, timing plays a vital role to generate a naturalistic behavior in interaction with the dynamic environment as well as adaptively planning and executing action sequences on-line. In biological systems, many of the physiological and anatomical functions follow a particular level of periodicity and stabilization, which exhibit a certain extent of resilience against external disturbances. A main aspect thereof is stabilizing movement timing against limited perturbations. Especially human arm movement, namely when it is tasked to reach a certain goal point, pose or configuration, shows a stabilizing behavior. This work incorporates the utilization of an extended Kalman filter (EKF) which was implemented to predict the target position while coping with non-linear system dynamics. The periodicity and temporal stabilization in biological systems was artificially generated by a Hopf oscillator, yielding a sinusoidal velocity profile for smooth and repeatable motion.
2011
Hendrik Reimann; Ioannis Iossifidis; Gregor Schöner
Autonomous movement generation for manipulators with multiple simultaneous constraints using the attractor dynamics approach Proceedings Article
In: 2011 IEEE International Conference on Robotics and Automation, ICRA2011, 2011.
Abstract | BibTeX | Tags: anthropomorphic robot arm, attractor dynamics approach, dynamical systems
@inproceedings{Reimann2011,
title = {Autonomous movement generation for manipulators with multiple simultaneous constraints using the attractor dynamics approach},
author = {Hendrik Reimann and Ioannis Iossifidis and Gregor Schöner},
year = {2011},
date = {2011-01-01},
urldate = {2011-01-01},
booktitle = {2011 IEEE International Conference on Robotics and Automation, ICRA2011},
abstract = {The movement of autonomous agents in natural environments is restricted by potentially large numbers of con- straints. To generate behavior that fulfills all given constraints simultaneously, the attractor dynamics approach to movement generation represents each constraint by a dynamical system with attractors or repellors at desired or undesired values of a relevant variable. These dynamical systems are transformed into vector fields over the control variables of a robotic agent that force the state of the whole system in directions beneficial to the satisfaction of the behavioral constraint. The attractor dynamics approach was recently successfully applied to the generation of manipulator motion trajectories avoiding collision with obstacles [1] and constraints on gripper orientation during reaching and grasping movements [2]. Continuing that body of work, this paper proposes a system which generates movements satisfying both obstacle avoidance and gripper orientation constraints simultaneously. As an extension, the additional constraint of avoiding hardware limits for joint angles is in- cluded. Properties of the resulting system are demonstrated by a systematic study generating movements with a large number of constraints in different scene setups. Specific characteristics are highlighted by several showcase example movements.},
keywords = {anthropomorphic robot arm, attractor dynamics approach, dynamical systems},
pubstate = {published},
tppubtype = {inproceedings}
}
The movement of autonomous agents in natural environments is restricted by potentially large numbers of con- straints. To generate behavior that fulfills all given constraints simultaneously, the attractor dynamics approach to movement generation represents each constraint by a dynamical system with attractors or repellors at desired or undesired values of a relevant variable. These dynamical systems are transformed into vector fields over the control variables of a robotic agent that force the state of the whole system in directions beneficial to the satisfaction of the behavioral constraint. The attractor dynamics approach was recently successfully applied to the generation of manipulator motion trajectories avoiding collision with obstacles [1] and constraints on gripper orientation during reaching and grasping movements [2]. Continuing that body of work, this paper proposes a system which generates movements satisfying both obstacle avoidance and gripper orientation constraints simultaneously. As an extension, the additional constraint of avoiding hardware limits for joint angles is in- cluded. Properties of the resulting system are demonstrated by a systematic study generating movements with a large number of constraints in different scene setups. Specific characteristics are highlighted by several showcase example movements.
Ioannis Iossifidis; Darius Malysiak; Hendrik Reimann
Model-free local navigation for humanoid robots Proceedings Article
In: Proc. IEEE/RSJ International Conference on Robotics and Biomimetics (RoBio2011), 2011.
Abstract | BibTeX | Tags: attractor dynamics approach, dynamical systems
@inproceedings{Iossifidis2011A,
title = {Model-free local navigation for humanoid robots},
author = {Ioannis Iossifidis and Darius Malysiak and Hendrik Reimann},
year = {2011},
date = {2011-01-01},
urldate = {2011-01-01},
booktitle = {Proc. IEEE/RSJ International Conference on Robotics and Biomimetics (RoBio2011)},
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 = {attractor dynamics approach, dynamical systems},
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.
D Malysiak; H Reiman; I Iossifidis
Human like trajectories for humanoid robots Conference
BC11 : Computational Neuroscience $backslash$& Neurotechnology Bernstein Conference $backslash$& Neurex Annual Meeting 2011, 2011.
BibTeX | Tags: attractor dynamics approach, dynamical systems
@conference{Malysiak2011,
title = {Human like trajectories for humanoid robots},
author = {D Malysiak and H Reiman and I Iossifidis},
year = {2011},
date = {2011-01-01},
urldate = {2011-01-01},
booktitle = {BC11 : Computational Neuroscience $backslash$& Neurotechnology Bernstein Conference $backslash$& Neurex Annual Meeting 2011},
keywords = {attractor dynamics approach, dynamical systems},
pubstate = {published},
tppubtype = {conference}
}
2010
Hendrik Reimann; Ioannis Iossifidis; Gregor Schoner; Gregor Schöner
Integrating orientation constraints into the attractor dynamics approach for autonomous manipulation Proceedings Article
In: 2010 10th IEEE-RAS International Conference on Humanoid Robots, pp. 294–301, IEEE, 2010, ISBN: 978-1-4244-8688-5.
Abstract | Links | BibTeX | Tags: attractor dynamics approach, Autonomous robotics, dynamical systems, Inverse kinematics
@inproceedings{Reimann2010a,
title = {Integrating orientation constraints into the attractor dynamics approach for autonomous manipulation},
author = {Hendrik Reimann and Ioannis Iossifidis and Gregor Schoner and Gregor Schöner},
url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5686349},
doi = {10.1109/ICHR.2010.5686349},
isbn = {978-1-4244-8688-5},
year = {2010},
date = {2010-12-01},
urldate = {2010-12-01},
booktitle = {2010 10th IEEE-RAS International Conference on Humanoid Robots},
pages = {294–301},
publisher = {IEEE},
abstract = {When autonomous robots generate behavior in complex environments they must satisfy multiple different constraints such as moving toward a target, avoidance of obstacles, or alignment of the gripper with a particular orientation. It is often convenient to represent each type of constraint in a specific reference frame, so that the satisfaction of all constraints requires transformation into a shared base frame. In the attractor dynamics approach, behavior is generated as an attractor solution of a dynamical system that is formulated in such a base frame to enable control. Each constraint contributes an attractive (for targets) or repulsive (for obstacles) component to the vector field. Here we show how these dynamic contributions can be formulated in different reference frames suited to each constraint and then be transformed and integrated within the base frame. Building on earlier work, we show how the orientation of the gripper can be integrated with other constraints on the movement of the manipulator. We also show, how an attractor dynamics of “neural” activation variables can be designed that activates and deactivates the different contributions to the vector field over time to generate a sequence of component movements. As a demonstration, we treat a manipulation task in which grasping oblong cylindrical objects is decomposed into an ensemble of separate constraints that are integrated and resolved using the attractor dynamics approach. The system is implemented on the small humanoid robot Nao, and illustrated in two exemplary movement tasks.},
keywords = {attractor dynamics approach, Autonomous robotics, dynamical systems, Inverse kinematics},
pubstate = {published},
tppubtype = {inproceedings}
}
When autonomous robots generate behavior in complex environments they must satisfy multiple different constraints such as moving toward a target, avoidance of obstacles, or alignment of the gripper with a particular orientation. It is often convenient to represent each type of constraint in a specific reference frame, so that the satisfaction of all constraints requires transformation into a shared base frame. In the attractor dynamics approach, behavior is generated as an attractor solution of a dynamical system that is formulated in such a base frame to enable control. Each constraint contributes an attractive (for targets) or repulsive (for obstacles) component to the vector field. Here we show how these dynamic contributions can be formulated in different reference frames suited to each constraint and then be transformed and integrated within the base frame. Building on earlier work, we show how the orientation of the gripper can be integrated with other constraints on the movement of the manipulator. We also show, how an attractor dynamics of “neural” activation variables can be designed that activates and deactivates the different contributions to the vector field over time to generate a sequence of component movements. As a demonstration, we treat a manipulation task in which grasping oblong cylindrical objects is decomposed into an ensemble of separate constraints that are integrated and resolved using the attractor dynamics approach. The system is implemented on the small humanoid robot Nao, and illustrated in two exemplary movement tasks.
H Reimann; I Iossifidis; G Schöner
Generating collision free reaching movements for redundant manipulators using dynamical systems Proceedings Article
In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 5372–5379, IEEE, 2010, ISBN: 978-1-4244-6674-0.
Abstract | Links | BibTeX | Tags: attractor dynamics approach, central nervous system, collision avoidance, dynamical systems, manipulator dynamics, obstacle avoidance, redundant robot arm
@inproceedings{Reimann2010b,
title = {Generating collision free reaching movements for redundant manipulators using dynamical systems},
author = {H Reimann and I Iossifidis and G Schöner},
url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5650603},
doi = {10.1109/IROS.2010.5650603},
isbn = {978-1-4244-6674-0},
year = {2010},
date = {2010-10-01},
booktitle = {2010 IEEE/RSJ International Conference on Intelligent Robots and Systems},
pages = {5372–5379},
publisher = {IEEE},
abstract = {For autonomous robots to manipulate objects in unknown environments, they must be able to move their arms without colliding with nearby objects, other agents or humans. The simultaneous avoidance of multiple obstacles in real time by all link segments of a manipulator is still a hard task both in practice and in theory. We present a systematic scheme for the generation of collision free movements for redundant manipulators in scenes with arbitrarily many obstacles. Based on the dynamical systems approach to robotics, constraints are formulated as contributions to a dynamical system that erect attractors for targets and repellors for obstacles. These contributions are formulated in terms of variables relevant to each constraint and then transformed into vector fields over the manipulator joint velocity vector as an embedding space in which all constraints are simultaneously observed. We demonstrate the feasibility of the approach by implementing it on a real anthropomorphic 8-degrees-of-freedom redundant manipulator. In addition, performance is characterized by detecting failures in a systematic simulation experiment in randomized scenes with varying numbers of obstacles.},
keywords = {attractor dynamics approach, central nervous system, collision avoidance, dynamical systems, manipulator dynamics, obstacle avoidance, redundant robot arm},
pubstate = {published},
tppubtype = {inproceedings}
}
For autonomous robots to manipulate objects in unknown environments, they must be able to move their arms without colliding with nearby objects, other agents or humans. The simultaneous avoidance of multiple obstacles in real time by all link segments of a manipulator is still a hard task both in practice and in theory. We present a systematic scheme for the generation of collision free movements for redundant manipulators in scenes with arbitrarily many obstacles. Based on the dynamical systems approach to robotics, constraints are formulated as contributions to a dynamical system that erect attractors for targets and repellors for obstacles. These contributions are formulated in terms of variables relevant to each constraint and then transformed into vector fields over the manipulator joint velocity vector as an embedding space in which all constraints are simultaneously observed. We demonstrate the feasibility of the approach by implementing it on a real anthropomorphic 8-degrees-of-freedom redundant manipulator. In addition, performance is characterized by detecting failures in a systematic simulation experiment in randomized scenes with varying numbers of obstacles.
2009
M Tuma; I Iossifidis; G Schöner
Temporal stabilization of discrete movement in variable environments: An attractor dynamics approach Proceedings Article
In: 2009 IEEE International Conference on Robotics and Automation, pp. 863–868, IEEE, 2009, ISBN: 978-1-4244-2788-8.
Abstract | Links | BibTeX | Tags: attractor dynamics approach, Autonomous robotics, dynamical systems, hopf oscillator
@inproceedings{Tuma2009b,
title = {Temporal stabilization of discrete movement in variable environments: An attractor dynamics approach},
author = {M Tuma and I Iossifidis and G Schöner},
url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5152562},
doi = {10.1109/ROBOT.2009.5152562},
isbn = {978-1-4244-2788-8},
year = {2009},
date = {2009-05-01},
booktitle = {2009 IEEE International Conference on Robotics and Automation},
pages = {863–868},
publisher = {IEEE},
abstract = {The ability to generate discrete movement with distinct and stable time courses is important for interaction scenarios both between different robots and with human partners, for catching and interception tasks, and for timed action sequences. In dynamic environments, where trajectories are evolving online, this is not a trivial task. The dynamical systems approach to robotics provides a framework for robust incorporation of fluctuating sensor information, but control of movement time is usually restricted to rhythmic motion and realized through stable limit cycles. The present work uses a Hopf oscillator to produce discrete motion and formulates an online adaptation rule to stabilize total movement time against a wide range of disturbances. This is integrated into a dynamical systems framework for the sequencing of movement phases and for directional navigation, using 2D-planar motion as an example. The approach is demonstrated on a Khepera mobile unit in order to show its reliability even when depending on low-level sensor information.},
keywords = {attractor dynamics approach, Autonomous robotics, dynamical systems, hopf oscillator},
pubstate = {published},
tppubtype = {inproceedings}
}
The ability to generate discrete movement with distinct and stable time courses is important for interaction scenarios both between different robots and with human partners, for catching and interception tasks, and for timed action sequences. In dynamic environments, where trajectories are evolving online, this is not a trivial task. The dynamical systems approach to robotics provides a framework for robust incorporation of fluctuating sensor information, but control of movement time is usually restricted to rhythmic motion and realized through stable limit cycles. The present work uses a Hopf oscillator to produce discrete motion and formulates an online adaptation rule to stabilize total movement time against a wide range of disturbances. This is integrated into a dynamical systems framework for the sequencing of movement phases and for directional navigation, using 2D-planar motion as an example. The approach is demonstrated on a Khepera mobile unit in order to show its reliability even when depending on low-level sensor information.
Matthias Tuma; Ioannis Iossifidis; Gregor Schöner
Temporal Stabilization of Discrete Movement in Variable Environments: An Attractor Dynamics Approach Proceedings Article
In: Proc. IEEE International Conference on Robotics and Automation ICRA '09, pp. 863–868, Kobe, Japan, 2009.
Abstract | BibTeX | Tags: attractor dynamics approach, Autonomous robotics, dynamical systems, hopf oscillator
@inproceedings{Tuma2009,
title = {Temporal Stabilization of Discrete Movement in Variable Environments: An Attractor Dynamics Approach},
author = {Matthias Tuma and Ioannis Iossifidis and Gregor Schöner},
year = {2009},
date = {2009-01-01},
booktitle = {Proc. IEEE International Conference on Robotics and Automation ICRA '09},
pages = {863–868},
address = {Kobe, Japan},
abstract = {The ability to generate discrete movement with distinct and stable time courses
is important for interaction scenarios both between different robots and with human partners,
for catching and interception tasks, and for timed action sequences.
In dynamic environments, where trajectories are evolving on-line, this is not a trivial task.
The dynamical systems approach to robotics provides a framework for robust
incorporation of fluctuating sensor information, but control of movement time is usually
restricted to rhythmic motion and realized through stable limit cycles. The present work
uses a Hopf oscillator to produce discrete motion and formulates an on-line adaptation rule
to stabilize total movement time against a wide range of disturbances. This is integrated into
a dynamical systems framework for the sequencing of movement phases and for directional navigation, using 2D-planar motion
as an example. The approach is demonstrated on a Khepera mobile unit in order to show its
reliability even when depending on low-level sensor information.},
keywords = {attractor dynamics approach, Autonomous robotics, dynamical systems, hopf oscillator},
pubstate = {published},
tppubtype = {inproceedings}
}
The ability to generate discrete movement with distinct and stable time courses
is important for interaction scenarios both between different robots and with human partners,
for catching and interception tasks, and for timed action sequences.
In dynamic environments, where trajectories are evolving on-line, this is not a trivial task.
The dynamical systems approach to robotics provides a framework for robust
incorporation of fluctuating sensor information, but control of movement time is usually
restricted to rhythmic motion and realized through stable limit cycles. The present work
uses a Hopf oscillator to produce discrete motion and formulates an on-line adaptation rule
to stabilize total movement time against a wide range of disturbances. This is integrated into
a dynamical systems framework for the sequencing of movement phases and for directional navigation, using 2D-planar motion
as an example. The approach is demonstrated on a Khepera mobile unit in order to show its
reliability even when depending on low-level sensor information.
is important for interaction scenarios both between different robots and with human partners,
for catching and interception tasks, and for timed action sequences.
In dynamic environments, where trajectories are evolving on-line, this is not a trivial task.
The dynamical systems approach to robotics provides a framework for robust
incorporation of fluctuating sensor information, but control of movement time is usually
restricted to rhythmic motion and realized through stable limit cycles. The present work
uses a Hopf oscillator to produce discrete motion and formulates an on-line adaptation rule
to stabilize total movement time against a wide range of disturbances. This is integrated into
a dynamical systems framework for the sequencing of movement phases and for directional navigation, using 2D-planar motion
as an example. The approach is demonstrated on a Khepera mobile unit in order to show its
reliability even when depending on low-level sensor information.
2008
Gregor Schöner; Ioannis Iossifidis
Auf gute Zusammenarbeit Journal Article
In: Gerhirn und Geist, Spektrum der Wissenschaft, vol. 3, 2008.
BibTeX | Tags: attractor dynamics approach, collision avoidance, manipulator dynamics, obstacle avoidance, primate central nervous system, redundant robot arm, telerobotics
@article{Schoener2008,
title = {Auf gute Zusammenarbeit},
author = {Gregor Schöner and Ioannis Iossifidis},
year = {2008},
date = {2008-01-01},
journal = {Gerhirn und Geist, Spektrum der Wissenschaft},
volume = {3},
keywords = {attractor dynamics approach, collision avoidance, manipulator dynamics, obstacle avoidance, primate central nervous system, redundant robot arm, telerobotics},
pubstate = {published},
tppubtype = {article}
}
2006
Ioannis Iossifidis; Gregor Schöner; Gregor Schoner
Dynamical Systems Approach for the Autonomous Avoidance of Obstacles and Joint-limits for an Redundant Robot Arm Proceedings Article
In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 580–585, IEEE, 2006, ISBN: 1-4244-0258-1.
Abstract | Links | BibTeX | Tags: attractor dynamics approach, collision avoidance, manipulator dynamics, obstacle avoidance, primate central nervous system, redundant robot arm, telerobotics
@inproceedings{Iossifidis2006a,
title = {Dynamical Systems Approach for the Autonomous Avoidance of Obstacles and Joint-limits for an Redundant Robot Arm},
author = {Ioannis Iossifidis and Gregor Schöner and Gregor Schoner},
doi = {10.1109/IROS.2006.282468},
isbn = {1-4244-0258-1},
year = {2006},
date = {2006-10-01},
booktitle = {2006 IEEE/RSJ International Conference on Intelligent Robots and Systems},
pages = {580–585},
publisher = {IEEE},
abstract = {We extend the attractor dynamics approach to generate goal-directed movement of a redundant, anthropomorphic arm while avoiding dynamic obstacles and respecting joint limits. To make the robot's movements human-like, we generate approximately straight-line trajectories by using two heading direction angles of the tool-point quite analogously to how movement is represented in the primate central nervous system. Two additional angles control the tool's spatial orientation so that it follows the tool-point's collision-free path. A fifth equation governs the redundancy angle, which controls the elevation of the elbow so as to avoid obstacles and respect joint limits. These variables make it possible to generate movement while sitting in an attractor (or, in the language of the potential field approach, in a minimum). We demonstrate the approach on an assistant robot, which interacts with human users in a shared workspace},
keywords = {attractor dynamics approach, collision avoidance, manipulator dynamics, obstacle avoidance, primate central nervous system, redundant robot arm, telerobotics},
pubstate = {published},
tppubtype = {inproceedings}
}
We extend the attractor dynamics approach to generate goal-directed movement of a redundant, anthropomorphic arm while avoiding dynamic obstacles and respecting joint limits. To make the robot's movements human-like, we generate approximately straight-line trajectories by using two heading direction angles of the tool-point quite analogously to how movement is represented in the primate central nervous system. Two additional angles control the tool's spatial orientation so that it follows the tool-point's collision-free path. A fifth equation governs the redundancy angle, which controls the elevation of the elbow so as to avoid obstacles and respect joint limits. These variables make it possible to generate movement while sitting in an attractor (or, in the language of the potential field approach, in a minimum). We demonstrate the approach on an assistant robot, which interacts with human users in a shared workspace