Veröffentlichungen

@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}

}

@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}

}

@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}

}

@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}

}

@inproceedings{Reimann2010b,

title = {Generating collision free reaching movements for redundant manipulators using dynamical systems},

author = {H Reimann and Ioannis 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},

urldate = {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 = {anthropomorphic arm, attractor dynamics approach, autonomous obstacle avoidance, central nervous system, collision avoidance, Dynamical systems, manipulator dynamics, redundant manipulators, redundant robot arm},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Tuma2009b,

title = {Temporal stabilization of discrete movement in variable environments: An attractor dynamics approach},

author = {M Tuma and Ioannis 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},

urldate = {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}

}

@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}

}

@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 = {anthropomorphic arm, attractor dynamics approach, autonomous obstacle avoidance, collision avoidance, dynamical systems approach, manipulator dynamics, primate central nervous system, redundant manipulators, redundant robot arm, telerobotics},

pubstate = {published},

tppubtype = {inproceedings}

}