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Composite Local Path Planning for Multi-Robot Obstacle Avoidance and Formation Navigation

Title
Composite Local Path Planning for Multi-Robot Obstacle Avoidance and Formation Navigation
Authors
Wee, Sung GilKim, Yoon GuAn, Jin UngLee, Dong HaLee, Suk-Gyu
DGIST Authors
Wee, Sung Gil; Kim, Yoon Gu; An, Jin Ung; Lee, Dong Ha; Lee, Suk-Gyu
Issue Date
2015-09
Citation
Advances in Computer Science: an International Journal, 4(17), 61-68
Type
Article
ISSN
2322-5157
Abstract
This paper proposes a composite local path planning method for multi-robot formation navigation with path deviation prevention using a repulsive function, A-star algorithm, and unscented Kalman filter (UKF). The repulsive function in the potential field method is used to avoid collisions among robots and obstacles. The A-star algorithm helps the robots to find an optimal local path. In addition, error estimation based on UKF guarantees small path deviation of each robot during navigation. The proposed method of composite local path planning is verified by the simulation results of the collective robot navigation because the system maintains a designated formation and performs a successful return to the assigned formation with effective obstacle avoidance under various experimental conditions.
URI
http://hdl.handle.net/20.500.11750/13330
https://pdfs.semanticscholar.org/b760/81395c96843b3eb2dd3870f5aea985ddb63d.pdf
Publisher
ACSIJ
Related Researcher
  • Author An, Jinung Brain Robot Augmented InteractioN(BRAIN) Laboratory
  • Research Interests
Files:
There are no files associated with this item.
Collection:
Division of Intelligent RoboticsBrain Robot Augmented InteractioN(BRAIN) Laboratory1. Journal Articles
ETC1. Journal Articles


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