Veröffentlichungen

@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}

}

@inproceedings{Iossifidis2009,

title = {Reaching while avoiding obstacles: a neuronally inspired attractor dynamics approach},

author = {Ioannis Iossifidis and Gregor Schöner},

doi = {10.3389/conf.neuro.10.2009.14.007},

year  = {2009},

date = {2009-01-01},

booktitle = {Bernstein Conference on Computational Neuroscience (BCCN 2009)},

keywords = {anthropomorphic arm, central nervous system, collision avoidance, Dynamical systems, manipulator dynamics, obstacle avoidance, redundant manipulators, redundant robot arm},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Iossifidis2004b,

title = {Autonomous reaching and obstacle avoidance with the anthropomorphic arm of a robotic assistant using the attractor dynamics approach},

author = {Ioannis Iossifidis and Gregor Schöner and Gregor Schoner},

doi = {10.1109/ROBOT.2004.1302393},

issn = {1050-4729},

year  = {2004},

date = {2004-01-01},

booktitle = {Proc. IEEE International Conference on Robotics and Automation ICRA '04},

volume = {5},

pages = {4295----4300 Vol.5},

abstract = {To enable a robotic assistant to autonomously reach for and transport objects while avoiding obstacles we have generalized the attractor dynamics approach established for vehicles to trajectory formation in robot arms. This approach is able to deal with the time-varying environments that occur when a human operator moves in a shared workspace. Stable fixed points (attractors) for the heading direction of the end-effector shift during movement and are being tracked by the system. This enables the attractor dynamics approach to avoid the spurious states that hamper potential field methods. Separating planning and control computationally, the approach is also simpler to implement. The stability properties of the movement plan make it possible to deal with fluctuating and imprecise sensory information. We implement this approach on a seven degree of freedom anthropomorphic arm reaching for objects on a working surface. We use an exact solution of the inverse kinematics, which enables us to steer the spatial position of the elbow clear of obstacles. The straight-line trajectories of the end-effector that emerge as long as the arm is far from obstacles make the movement goals of the robotic assistant predictable for the human operator, improving man-machine interaction.},

keywords = {anthropomorphic arm, attractor dynamics, autonomous reaching, collision avoidance, end effector shift, end effectors, man machine interaction, manipulator dynamics, obstacle avoidance, robotic assistant, time varying environment, time-varying systems},

pubstate = {published},

tppubtype = {inproceedings}

}