
Proceedings Paper
An obstacle avoidance method for a redundant manipulator controlled through a recurrent neural networkFormat | Member Price | Non-Member Price |
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Paper Abstract
In this paper we study the problem of obstacle avoidance for a redundant manipulator. The manipulator
is controlled through an already developed recurrent neural network, called MMC-model (Mean of Multiple
Computation), able to solve the kinematics of manipulators in any configuration. This approach solves both
problems of direct and inverse kinematics by simple numerical iterations. The MMC-model here proposed is
constituted by a linear part that performs the topological analysis without any constraint and by a second layer,
with nonlinear blocks used to add the constraints related to both the mechanical structure of the manipulator
and the obstacles located in the operative space. The control architecture was evaluated in simulation for a
planar manipulator with three links. The robot starting from a given initial configuration is able to reach a
target position chosen in the operative space avoiding collisions with an obstacle placed in the plane. The
obstacle is identified by simulated sensors placed on each link, they can measure the distance between link and obstacle. The reaction to the obstacle proximity can be modulated through a damping factor that improves the smoothing of the robot trajectory. The good results obtained open the way to a hardware implementation for the real-time control of a redundant manipulator.
Paper Details
Date Published: 22 May 2007
PDF: 8 pages
Proc. SPIE 6592, Bioengineered and Bioinspired Systems III, 65920N (22 May 2007); doi: 10.1117/12.724087
Published in SPIE Proceedings Vol. 6592:
Bioengineered and Bioinspired Systems III
Paolo Arena; Ángel Rodríguez-Vázquez; Gustavo Liñán-Cembrano, Editor(s)
PDF: 8 pages
Proc. SPIE 6592, Bioengineered and Bioinspired Systems III, 65920N (22 May 2007); doi: 10.1117/12.724087
Show Author Affiliations
Luigi Fortuna, Univ. degli Studi di Catania (Italy)
Luca Patané, Univ. degli Studi di Catania (Italy)
Luca Patané, Univ. degli Studi di Catania (Italy)
Published in SPIE Proceedings Vol. 6592:
Bioengineered and Bioinspired Systems III
Paolo Arena; Ángel Rodríguez-Vázquez; Gustavo Liñán-Cembrano, Editor(s)
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