Prof. Dr. rer. nat. Ioannis Iossifidis

AUSGEWÄHLTE PUBLIKATIONEN

• anthropomorphic robot arm anthropomorphism arm movement model artificial skin attractor dynamics approach Autonomous robotics BCI behavior generation direct physical interaction Dynamical systems haptic interface human anatomy human motor behavior human operators intuition inverse kinematics Machine Learning man machine interaction man-machine systems man-machine-interaction manipulators mechanical structure modeling movement model object recognition operators gesture pervasive design robot manipulator control robot vision robotic assistant sensory channels user modelling

  Zeige alle

  11 Einträge « ‹ 1 von 2 › »

  2021

  11.

  Sziburis, Tim; Blex, Susanne; Glasmachers, Tobias; Rano, Inaki; Iossifidis, Ioannis

  Modelling the Generation of Human Upper-Limb Reaching Trajectories: An Extended Behavioural Attractor Dynamics Approach Proceedings Article

  In: Bernstein Conference, 2021.

  Links | BibTeX | Schlagwörter: 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}
  
  }
  
  

  Schließen

  • doi:10.12751/nncn.bc2021.p078

  Schließen

  10.

  Doliwa, Sebastian; Hussain, Muhammad Ayaz; Sziburis, Tim; Iossifidis, Ioannis

  Biologically Inspired Model for Timed Motion in Robotic Systems Artikel

  In: arXiv:2106.15864 [cs, math], 2021.

  Abstract | BibTeX | Schlagwörter: 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}
  
  }
  
  

  Schließen

  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.

  Schließen

  2011

  9.

  Reimann, Hendrik; Iossifidis, Ioannis; Schöner, Gregor

  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 | Schlagwörter: 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}
  
  }
  
  

  Schließen

  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.

  Schließen

  8.

  Iossifidis, Ioannis; Malysiak, Darius; Reimann, Hendrik

  Model-free local navigation for humanoid robots Proceedings Article

  In: Proc. IEEE/RSJ International Conference on Robotics and Biomimetics (RoBio2011), 2011.

  Abstract | BibTeX | Schlagwörter: 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}
  
  }
  
  

  Schließen

  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.

  Schließen

  7.

  Malysiak, D; Reiman, H; Iossifidis, Ioannis

  Human like trajectories for humanoid robots Konferenz

  BC11 : Computational Neuroscience $backslash$& Neurotechnology Bernstein Conference $backslash$& Neurex Annual Meeting 2011, 2011.

  BibTeX | Schlagwörter: attractor dynamics approach, Dynamical systems

  @conference{Malysiak2011,
  
  title = {Human like trajectories for humanoid robots},
  
  author = {D Malysiak and H Reiman and Ioannis 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}
  
  }
  
  

  Schließen

  2010

  6.

  Reimann, Hendrik; Iossifidis, Ioannis; Schoner, Gregor; Schöner, Gregor

  Integrating orientation constraints into the attractor dynamics approach for autonomous manipulation Proceedings Article

  In: 2010 10th IEEE-RAS International Conference on Humanoid Robots, S. 294–301, IEEE, 2010, ISBN: 978-1-4244-8688-5.

  Abstract | Links | BibTeX | Schlagwörter: 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}
  
  }
  
  

  Schließen

  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.

  Schließen

  • http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5686349
  • doi:10.1109/ICHR.2010.5686349

  Schließen

  5.

  Reimann, H; Iossifidis, Ioannis; Schöner, G

  Generating collision free reaching movements for redundant manipulators using dynamical systems Proceedings Article

  In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, S. 5372–5379, IEEE, 2010, ISBN: 978-1-4244-6674-0.

  Abstract | Links | BibTeX | Schlagwörter: anthropomorphic arm, attractor dynamics approach, autonomous obstacle avoidance, central nervous system, collision avoidance, Dynamical systems, manipulator dynamics, redundant manipulators, redundant robot arm

  @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}
  
  }
  
  

  Schließen

  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.

  Schließen

  • http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5650603
  • doi:10.1109/IROS.2010.5650603

  Schließen

  2009

  4.

  Tuma, M; Iossifidis, Ioannis; Schöner, G

  Temporal stabilization of discrete movement in variable environments: An attractor dynamics approach Proceedings Article

  In: 2009 IEEE International Conference on Robotics and Automation, S. 863–868, IEEE, 2009, ISBN: 978-1-4244-2788-8.

  Abstract | Links | BibTeX | Schlagwörter: 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 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}
  
  }
  
  

  Schließen

  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.

  Schließen

  • http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5152562
  • doi:10.1109/ROBOT.2009.5152562

  Schließen

  3.

  Tuma, Matthias; Iossifidis, Ioannis; Schöner, Gregor

  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, S. 863–868, Kobe, Japan, 2009.

  Abstract | BibTeX | Schlagwörter: 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}
  
  }
  
  

  Schließen

  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.

  Schließen

  2008

  2.

  Schöner, Gregor; Iossifidis, Ioannis

  Auf gute Zusammenarbeit Artikel

  In: Gerhirn und Geist, Spektrum der Wissenschaft, Bd. 3, 2008.

  BibTeX | Schlagwörter: 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

  @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 = {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 = {article}
  
  }
  
  

  Schließen

  11 Einträge « ‹ 1 von 2 › »