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 force sensing haptic interface human motor behavior human operators intuition human perception inverse kinematics Machine Learning man machine interaction man-machine-interaction manipulators mechanical structure modeling movement model object recognition operators gaze pervasive design robot manipulator control robot vision robotic assistant sensory channels user modelling

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  44 Einträge « ‹ 2 von 5 › »

  2011

  34.

  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

  33.

  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

  32.

  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

  31.

  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

  30.

  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

  29.

  Zibner, S K U; Faubel, Christian; Iossifidis, Ioannis; Schöner, G; Spencer, J P

  Scenes and tracking with dynamic neural fields: How to update a robotic scene representation Proceedings Article

  In: 2010 IEEE 9th International Conference on Development and Learning, ICDL-2010 - Conference Program, 2010, ISBN: 9781424469024.

  Abstract | Links | BibTeX | Schlagwörter: Autonomous robotics, dynamic field theory (DFT), Dynamical systems, embodied cognition, neural processing

  @inproceedings{Zibner2010,
  
  title = {Scenes and tracking with dynamic neural fields: How to update a robotic scene representation},
  
  author = {S K U Zibner and Christian Faubel and Ioannis Iossifidis and G Schöner and J P Spencer},
  
  doi = {10.1109/DEVLRN.2010.5578837},
  
  isbn = {9781424469024},
  
  year  = {2010},
  
  date = {2010-01-01},
  
  urldate = {2010-01-01},
  
  booktitle = {2010 IEEE 9th International Conference on Development and Learning, ICDL-2010 - Conference Program},
  
  abstract = {We present an architecture based on the Dynamic Field Theory for the problem of scene representation. At the core of this architecture are three-dimensional neural fields linking feature to spatial information. These three-dimensional fields are coupled to lower-dimensional fields that provide both a close link to the sensory surface and a close link to motor behavior. We highlight the updating mechanism of this architecture, both when a single object is selected and followed by the robot's head in smooth pursuit and in multi-item tracking when several items move simultaneously. textcopyright 2010 IEEE.},
  
  keywords = {Autonomous robotics, dynamic field theory (DFT), Dynamical systems, embodied cognition, neural processing},
  
  pubstate = {published},
  
  tppubtype = {inproceedings}
  
  }
  
  

  Schließen

  We present an architecture based on the Dynamic Field Theory for the problem of scene representation. At the core of this architecture are three-dimensional neural fields linking feature to spatial information. These three-dimensional fields are coupled to lower-dimensional fields that provide both a close link to the sensory surface and a close link to motor behavior. We highlight the updating mechanism of this architecture, both when a single object is selected and followed by the robot's head in smooth pursuit and in multi-item tracking when several items move simultaneously. textcopyright 2010 IEEE.

  Schließen

  • doi:10.1109/DEVLRN.2010.5578837

  Schließen

  28.

  Zibner, S K U; Faubel, Christian; Iossifidis, Ioannis; Schöner, G

  Scene representation for anthropomorphic robots: A dynamic neural field approach Proceedings Article

  In: Joint 41st International Symposium on Robotics and 6th German Conference on Robotics 2010, ISR/ROBOTIK 2010, 2010, ISBN: 9781617387197.

  Abstract | BibTeX | Schlagwörter: Autonomous robotics, dynamic field theory (DFT), Dynamical systems, embodied cognition, neural processing

  @inproceedings{Zibner2010b,
  
  title = {Scene representation for anthropomorphic robots: A dynamic neural field approach},
  
  author = {S K U Zibner and Christian Faubel and Ioannis Iossifidis and G Schöner},
  
  isbn = {9781617387197},
  
  year  = {2010},
  
  date = {2010-01-01},
  
  urldate = {2010-01-01},
  
  booktitle = {Joint 41st International Symposium on Robotics and 6th German Conference on Robotics 2010, ISR/ROBOTIK 2010},
  
  volume = {2},
  
  abstract = {For autonomous robotic systems, the ability to represent a scene, to memorize and track objects and their associated features is a prerequisite for reasonable interactive behavior. In this paper, we present a biologically inspired architecture for scene representation that is based on Dynamic Field Theory. At the core of the architecture we make use of three-dimensional Dynamic Neural Fields for representing space-feature associations. These associations are built up autonomously in a sequential way and they are maintained and continuously updated. We demonstrate these capabilities in two experiments on an anthropomorphic robotic platform. In the first experiment we show the sequential scanning of a scene. The second experiment demonstrates the maintenance of associations for objects, which get out of view, and the correct update of the scene representation, if such objects are removed.},
  
  keywords = {Autonomous robotics, dynamic field theory (DFT), Dynamical systems, embodied cognition, neural processing},
  
  pubstate = {published},
  
  tppubtype = {inproceedings}
  
  }
  
  

  Schließen

  For autonomous robotic systems, the ability to represent a scene, to memorize and track objects and their associated features is a prerequisite for reasonable interactive behavior. In this paper, we present a biologically inspired architecture for scene representation that is based on Dynamic Field Theory. At the core of the architecture we make use of three-dimensional Dynamic Neural Fields for representing space-feature associations. These associations are built up autonomously in a sequential way and they are maintained and continuously updated. We demonstrate these capabilities in two experiments on an anthropomorphic robotic platform. In the first experiment we show the sequential scanning of a scene. The second experiment demonstrates the maintenance of associations for objects, which get out of view, and the correct update of the scene representation, if such objects are removed.

  Schließen

  27.

  Reimann, Hendrik; Iossifidis, Ioannis; Schöner, Gregor

  End-effector obstacle avoidance using multiple dynamic variables Proceedings Article

  In: ISR / ROBOTIK 2010, Munich, Germany, 2010.

  Abstract | BibTeX | Schlagwörter: arm movement model, Autonomous robotics, behavior generation, Dynamical systems, movement model, obstacle avoidance

  @inproceedings{Reimannd,
  
  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, Autonomous robotics, behavior generation, Dynamical systems, movement model, obstacle avoidance},
  
  pubstate = {published},
  
  tppubtype = {inproceedings}
  
  }
  
  

  Schließen

  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.

  Schließen

  26.

  Grimm, Matthias; Iossifidis, Ioannis

  Behavioral Organization for Mobile Robotic Systems: An Attractor Dynamics Approach Proceedings Article

  In: ISR / ROBOTIK 2010, Munich, Germany, 2010.

  Abstract | BibTeX | Schlagwörter: Autonomous robotics, behavior generation, Dynamical systems, movement model, movile robot

  @inproceedings{Grimm2010b,
  
  title = {Behavioral Organization for Mobile Robotic Systems: An Attractor Dynamics Approach},
  
  author = {Matthias Grimm and Ioannis Iossifidis},
  
  year  = {2010},
  
  date = {2010-01-01},
  
  booktitle = {ISR / ROBOTIK 2010},
  
  address = {Munich, Germany},
  
  abstract = {Autonomous systems generate different behaviors based on the perceived environmental situation. The organization of a set of behaviors plays an important role in the field of autonomous robotics. The organization architecture must be flexible, so that behavioral changes are possible if the sensory information changes. Furthermore, behavioral organization must be stable, so that small changes in sensory information do not lead to oscillations. To achieve this, all behaviors, but also the underlying organization architecture, are based on continuous dynamical systems. They are characterized by a set of dynamical variables, also referred to as state variables. These variables represent the activation or deactivation of a particular behavior. Elementary behaviors are dependent on the sensor input in a way, that changes of the sensorial information lead to qualitatively different behaviors. The so-called sensor context denotes whether a behavior is applicable in the current sensor situation or not. However, for complex systems consisting of many elementary behaviors, it is necessary to take logical conditions into account to generate a sequence of behaviors. Furthermore, some elementary behaviors can or even must run in parallel, while others exclude each other. This internal information requires knowledge about the logical interaction of the behaviors and is stored within binary matrices. This makes the overall organization structure very flexible and easy to extend. We present the architecture using the example of approaching and passing a door. The robot has to navigate from one room to another while simultaneously avoiding obstacles in its pathway.},
  
  keywords = {Autonomous robotics, behavior generation, Dynamical systems, movement model, movile robot},
  
  pubstate = {published},
  
  tppubtype = {inproceedings}
  
  }
  
  

  Schließen

  Autonomous systems generate different behaviors based on the perceived environmental situation. The organization of a set of behaviors plays an important role in the field of autonomous robotics. The organization architecture must be flexible, so that behavioral changes are possible if the sensory information changes. Furthermore, behavioral organization must be stable, so that small changes in sensory information do not lead to oscillations. To achieve this, all behaviors, but also the underlying organization architecture, are based on continuous dynamical systems. They are characterized by a set of dynamical variables, also referred to as state variables. These variables represent the activation or deactivation of a particular behavior. Elementary behaviors are dependent on the sensor input in a way, that changes of the sensorial information lead to qualitatively different behaviors. The so-called sensor context denotes whether a behavior is applicable in the current sensor situation or not. However, for complex systems consisting of many elementary behaviors, it is necessary to take logical conditions into account to generate a sequence of behaviors. Furthermore, some elementary behaviors can or even must run in parallel, while others exclude each other. This internal information requires knowledge about the logical interaction of the behaviors and is stored within binary matrices. This makes the overall organization structure very flexible and easy to extend. We present the architecture using the example of approaching and passing a door. The robot has to navigate from one room to another while simultaneously avoiding obstacles in its pathway.

  Schließen

  25.

  Sandamirskaya, Yulia; Lipinski, John; Iossifidis, Ioannis; Schöner, G

  Natural human-robot interaction through spatial language: a dynamic neural fields approach Proceedings Article

  In: Proc. 19th IEEE International Workshop on Robot and Human Interactive Communication (ROMAN 2010), S. 600–607, IEEE, 2010, ISSN: 1944-9445.

  Links | BibTeX | Schlagwörter: arm movement model, Autonomous robotics, behavior generation, Dynamical systems, man machine interaction, movement model, speech recognition

  @inproceedings{Sandamirskayasubmitted,
  
  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, Autonomous robotics, behavior generation, Dynamical systems, man machine interaction, movement model, speech recognition},
  
  pubstate = {published},
  
  tppubtype = {inproceedings}
  
  }
  
  

  Schließen

  • http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5598671

  Schließen

  44 Einträge « ‹ 2 von 5 › »