A method for the study of position in highly redundant multibody systems in environments with obstacles

This paper looks at a method for the analysis of highly redundant multibody systems (e.g., in the case of cellular adaptive structures of variable geometry) in environments with obstacles. Our aim is to solve the inverse kinematics in successive positions of multibody systems, avoiding the obstacles...

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Bibliographic Details
Published in:IEEE transactions on robotics and automation 2002-04, Vol.18 (2), p.257-262
Main Authors: Agirrebeitia, J., Aviles, R., de Bustos, I.F., Ajuria, G.
Format: Article
Language:English
Subjects:
Actuators
Applied sciences
Cellular
Computational geometry
Computer science
control theory
systems
Control theory. Systems
Deformable models
Equations
Exact sciences and technology
Finite element method
Finite element methods
Geometry
Inverse kinematics
Kinetics
Lagrangian functions
Mathematical analysis
Mathematical models
Minimization methods
Multibody systems
Obstacles
Power system modeling
Prosthetics
Redundant
Robot kinematics
Robotics
Robots
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Summary:This paper looks at a method for the analysis of highly redundant multibody systems (e.g., in the case of cellular adaptive structures of variable geometry) in environments with obstacles. Our aim is to solve the inverse kinematics in successive positions of multibody systems, avoiding the obstacles in its work environment. The multibody systems are modeled via rod-type finite elements, both deformable and indeformable, and the coordinates of their nodes are chosen as variables. The obstacles are modeled via a mesh of points that exert repulsive forces on the nodes of the model of the multibody, in order to model the obstacle avoidance. Such forces have been chosen inversely proportional to the Nth power of the distance between the corresponding points of the obstacle and of the multibody system. The method is based on a potential function and on its minimization using the Lagrange Multiplier Method. The solution of the resulting equations is undertaken iteratively with the Newton-Raphson Method.
ISSN:1042-296X
2374-958X
DOI:10.1109/TRA.2002.999655