scholarly journals Formation control of underactuated bio-inspired snake robots

2016 ◽  
Vol 21 (3) ◽  
pp. 282-294 ◽  
Author(s):  
Ehsan Rezapour ◽  
Kristin Y. Pettersen ◽  
Jan T. Gravdahl ◽  
Andreas Hofmann
Keyword(s):  
Formation Control ◽  
Snake Robots

Energy-based cooperative formation control for multiple flight vehicles

2017 ◽  
Author(s):  
Chao-Yang Dong ◽  
Ming-Yu Ma ◽  
Qing Wang ◽  
Chao Ren
Keyword(s):  
Formation Control ◽  
Flight Vehicles

scholarly journals Scalability Analysis of Algebraic Graph-Based Multi-UAVs Formation Control

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 129719-129733 ◽  
Author(s):  
Yu Ding ◽  
Xiangke Wang ◽  
Yirui Cong ◽  
Huiming Li
Keyword(s):  
Formation Control ◽  
Scalability Analysis

Leaderless Swarm Formation Control: From Global Specifications to Local Control Laws

2021 ◽  
Author(s):  
Solomon Gudeta ◽  
Ali Karimoddini ◽  
Mohammadreza Davoodi ◽  
Ioannis Raptis
Keyword(s):  
Local Control ◽  
Formation Control ◽  
Control Laws ◽  
Swarm Formation

scholarly journals Formation Control and Obstacle Avoidance Algorithm of a Multi-USV System Based on Virtual Structure and Artificial Potential Field

2021 ◽  
Vol 9 (2) ◽  
pp. 161
Author(s):  
Xun Yan ◽  
Dapeng Jiang ◽  
Runlong Miao ◽  
Yulong Li
Keyword(s):  
Obstacle Avoidance ◽  
Potential Field ◽  
Formation Control ◽  
Shape Change ◽  
Artificial Potential Field ◽  
Generation Algorithm ◽  
Time Performance ◽  
Movement Ability ◽  
Window Approach ◽  
Avoidance Problem

This paper proposes a formation generation algorithm and formation obstacle avoidance strategy for multiple unmanned surface vehicles (USVs). The proposed formation generation algorithm implements an approach combining a virtual structure and artificial potential field (VSAPF), which provides a high accuracy of formation shape keeping and flexibility of formation shape change. To solve the obstacle avoidance problem of the multi-USV system, an improved dynamic window approach is applied to the formation reference point, which considers the movement ability of the USV. By applying this method, the USV formation can avoid obstacles while maintaining its shape. The combination of the virtual structure and artificial potential field has the advantage of less calculations, so that it can ensure the real-time performance of the algorithm and convenience for deployment on an actual USV. Various simulation results for a group of USVs are provided to demonstrate the effectiveness of the proposed algorithms.

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