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Two-level structure swarm formation system with self-organized topology network.
- Source :
-
Neurocomputing . Apr2020, Vol. 384, p356-367. 12p. - Publication Year :
- 2020
-
Abstract
- In this work, a two-level mobile robot swarm system with self-organized formation network is proposed. Initially, based on the position information of the robots, a relation-invariable persistent formation (RIPF) algorithm can automatically organize the swarm network and construct an optimal persistent formation. At the upper formation planning level, the collision-free reference paths of the swarm can be planned for guiding the robots to reach and maintain a desired distance with their neighbors. Then, at the lower formation tracking control level, a neural-dynamic combined model predictive control (MPC) method is applied to drive the swarm moving on the reference paths. The MPC can reformulate the system into a convex minimization problem, which can further be transformed into a constrained quadratic programming (QP) problem such that an efficient QP solver, called primal-dual neural network (PDNN), is implemented to obtain the optimal control inputs online for the robots. In the end, simulation results show the effectiveness of the proposed formation system. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09252312
- Volume :
- 384
- Database :
- Academic Search Index
- Journal :
- Neurocomputing
- Publication Type :
- Academic Journal
- Accession number :
- 141683002
- Full Text :
- https://doi.org/10.1016/j.neucom.2019.11.053