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A local-based method for manipulators path planning, using sub-goals resulting from a local graph

Published online by Cambridge University Press:  07 July 2006

S. Zeghloul
Affiliation:
Laboratoire de Mécanique des Solides, UMR CNRS 6610, Université de Poitiers, SP2MI, Bd. Pierre et Marie Curie, BP 179, 86962 Futuroscope de Chasseneuil (France)
C. Helguera
Affiliation:
Instituto Tecnológico y de Estudios Superiores de Monterrey – Campus Laguna, Paseo del Tecnológico No. 751, Col. Ampliación la Rosita, Torreón, Coah. CP. 27250 (Mexico)
G. Ramirez
Affiliation:
Laboratoire de Mécanique des Solides, UMR CNRS 6610, Université de Poitiers, SP2MI, Bd. Pierre et Marie Curie, BP 179, 86962 Futuroscope de Chasseneuil (France)
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Abstract

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This paper addresses the path planning problem for manipulators. The problem of path planning in robotics can be defined as follows: To find a collision free trajectory from an initial configuration to a goal configuration. In this paper a collision-free path planner for manipulators, based on a local constraints method, is proposed. In this approach the task is described by a minimization problem under geometric constraints. The anti-collision constraints are mapped as linear constraints in the configuration space and they are not included in the function to minimize. Also, the task to achieve is defined as a combination of two displacements. The first displacement brings the robot towards to the goal configuration, while the second one allows the robot to avoid the local minima. This formulation solves many of classical problems found in local methods. However, when the robot acts in some heavy cluttered environments, a zig-zaging phenomenon could appear. To solve this situation, a graph based on the local environment of the robot is constructed. On this graph, an A* search is performed, in order to find a dead-lock free position that can be used as a sub-goal in the optimization process. This path-planner has been implemented within SMAR, a CAD-Robotics system developed at our laboratory. Tests in heavy cluttered environments were successfully performed.

Type
Article
Copyright
2006 Cambridge University Press