DocumentCode
532089
Title
Notice of Retraction
Obstacle avoidance in flocking motion
Author
Dong-Mei Wang ; Ling Xiong
Author_Institution
Coll. of Inf. Sci. & Eng., Wuhan Univ. of Sci. & Technol., Wuhan, China
Volume
8
fYear
2010
fDate
22-24 Oct. 2010
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
An approach to obstacle avoidance in the flocking motion is presented in this paper. Flock navigation is addressed using virtual agents which are produced by the rolling windows method, and obstacle avoidance is achieved by the limit-cycle method. This results not only in flocking motion to the goal, but also in obstacle avoidance with each other and with static obstacles in global unknown environment. Furthermore, the swarm is extended to an intelligent swarm by giving individual agents some limited memories, and flocking with obstacle avoidance of the intelligent swarm is also achieved. Simulations verified the effectiveness of the proposed schemes,and the intelligent swarm can more efficient to achieve flocking motion in obstacle environment.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
An approach to obstacle avoidance in the flocking motion is presented in this paper. Flock navigation is addressed using virtual agents which are produced by the rolling windows method, and obstacle avoidance is achieved by the limit-cycle method. This results not only in flocking motion to the goal, but also in obstacle avoidance with each other and with static obstacles in global unknown environment. Furthermore, the swarm is extended to an intelligent swarm by giving individual agents some limited memories, and flocking with obstacle avoidance of the intelligent swarm is also achieved. Simulations verified the effectiveness of the proposed schemes,and the intelligent swarm can more efficient to achieve flocking motion in obstacle environment.
Keywords
collision avoidance; mobile agents; motion control; multi-agent systems; flock navigation; flocking motion; limit cycle method; obstacle avoidance; rolling windows method; virtual agent; Artificial neural networks; Lead; Radio navigation; Flocking motion; Limit-cycle; Rolling window method; Virtual leader;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-7235-2
Type
conf
DOI
10.1109/ICCASM.2010.5619431
Filename
5619431
Link To Document