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2013
2.
 Iossifidis, Ioannis
Motion constraint satisfaction by means of closed form solution for redundant robot arms Proceedings Article 
In: 2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013, S. 2106–2111, 2013, ISBN: 978-1-4799-2744-9.
Abstract | Links | BibTeX | Schlagwörter: Autonomous robotics, inverse kinematics, motion constraints, redundant robot
@inproceedings{Iossifidis2013b,

title = {Motion constraint satisfaction by means of closed form solution for redundant robot arms},

author = {Ioannis Iossifidis},

doi = {10.1109/ROBIO.2013.6739780},

isbn = {978-1-4799-2744-9},

year  = {2013},

date = {2013-01-01},

booktitle = {2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013},

pages = {2106--2111},

abstract = {Generation of flexible goal directed movement describes the key skill of autonomous articulated robots. Critical points are still the acknowledgement of reaching and grasping task while satisfying static and dynamically changing constraints given by the environment or caused by the human operator in a collaborative situation. This means that the motion planning dynamics has to incorporate multiple contributions of different qualities which should be formulated in constraint specific reference frames and then transformed into the frame of joint velocities. Whereby the handling of the contribution to motion planning is determined by the solution of the inverse kinematics problem. In this work a closed form solution for the inverse kinematics problem for an eight degree of freedom arm is presented. The geometrical properties of the multi redundant arm and the resulting free parameter which determine it's null space motion are utilized to satisfy constraints of the desired motion. We implement this system on an eight DoF redundant manipulator and show its feasibility in a simulation. textcopyright 2013 IEEE.},

keywords = {Autonomous robotics, inverse kinematics, motion constraints, redundant robot},

pubstate = {published},

tppubtype = {inproceedings}

}

Schließen
Generation of flexible goal directed movement describes the key skill of autonomous articulated robots. Critical points are still the acknowledgement of reaching and grasping task while satisfying static and dynamically changing constraints given by the environment or caused by the human operator in a collaborative situation. This means that the motion planning dynamics has to incorporate multiple contributions of different qualities which should be formulated in constraint specific reference frames and then transformed into the frame of joint velocities. Whereby the handling of the contribution to motion planning is determined by the solution of the inverse kinematics problem. In this work a closed form solution for the inverse kinematics problem for an eight degree of freedom arm is presented. The geometrical properties of the multi redundant arm and the resulting free parameter which determine it's null space motion are utilized to satisfy constraints of the desired motion. We implement this system on an eight DoF redundant manipulator and show its feasibility in a simulation. textcopyright 2013 IEEE.
Schließen
doi:10.1109/ROBIO.2013.6739780
Schließen
1.
 Iossifidis, Ioannis
Motion Constraint Satisfaction by Means of Closed Form Solution for Redundant Robot Arms Proceedings Article 
In: Proc. IEEE/RSJ International Conference on Robotics and Biomimetics (RoBio2013), 2013.
Abstract | BibTeX | Schlagwörter: Autonomous robotics, inverse kinematics, motion constraints, redundant robot
@inproceedings{Iossifidis2013db,

title = {Motion Constraint Satisfaction by Means of Closed Form Solution for Redundant Robot Arms},

author = {Ioannis Iossifidis},

year  = {2013},

date = {2013-01-01},

booktitle = {Proc. IEEE/RSJ International Conference on Robotics and Biomimetics (RoBio2013)},

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 = {Autonomous robotics, inverse kinematics, motion constraints, redundant robot},

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