scholarly journals Convergence and Collision Avoidance in Formation Control: A Survey of the Artificial Potential Functions Approach

10.5772/14142 ◽  
2011 ◽  
Author(s):  
Eduardo G. ◽  
Eduardo Aranda-Bricaire
Keyword(s):  
Collision Avoidance ◽  
Formation Control ◽  
Potential Functions

scholarly journals Fuzzy Formation Control and Collision Avoidance for Multiagent Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-18 ◽  
Author(s):  
Yeong-Hwa Chang ◽  
Chun-Lin Chen ◽  
Wei-Shou Chan ◽  
Hung-Wei Lin ◽  
Chia-Wen Chang
Keyword(s):  
Collision Avoidance ◽  
Multiagent Systems ◽  
Formation Control ◽  
Descent Method ◽  
Minimum Problem ◽  
Gradient Descent Method ◽  
Consensus Formation ◽  
Distributed Information ◽  
Graph Theoretic ◽  
Learning Rules

This paper aims to investigate the formation control of leader-follower multiagent systems, where the problem of collision avoidance is considered. Based on the graph-theoretic concepts and locally distributed information, a neural fuzzy formation controller is designed with the capability of online learning. The learning rules of controller parameters can be derived from the gradient descent method. To avoid collisions between neighboring agents, a fuzzy separation controller is proposed such that the local minimum problem can be solved. In order to highlight the advantages of this fuzzy logic based collision-free formation control, both of the static and dynamic leaders are discussed for performance comparisons. Simulation results indicate that the proposed fuzzy formation and separation control can provide better formation responses compared to conventional consensus formation and potential-based collision-avoidance algorithms.

Control of Multiple Mobile Agents Via Artificial Potential Functions and Random Motion

2007 ◽  
Author(s):  
Manish Kumar ◽  
Devendra P. Garg ◽  
Randy Zachery
Keyword(s):  
Potential Function ◽  
Mobile Agents ◽  
Formation Control ◽  
Cluster Formation ◽  
Limited Range ◽  
Random Motion ◽  
Potential Functions ◽  
Random Behavior ◽  
Artificial Potential Function ◽  
Multiple Mobile Agents

This paper investigates the effectiveness of designed random behavior in cooperative formation control of multiple mobile agents. A method based on artificial potential functions provides a framework for decentralized control of their formation. However, it implies heavy communication costs. The communication requirement can be replaced by onboard sensors. The onboard sensors have limited range and provide only local information, and may result in the formation of isolated clusters. This paper proposes to introduce a component representing random motion in the artificial potential function formulation of the formation control problem. The introduction of the random behavior component results in a better chance of global cluster formation. The paper uses an agent model that includes both position and orientation, and formulates the dynamic equations to incorporate that model in artificial potential function approach. The effectiveness of the proposed method is verified via extensive simulations performed on a group of mobile agents and leaders.

Optimal formation control and collision avoidance in environment with multiple rectangle obstacles

2018 ◽  
Vol 355 (15) ◽  
pp. 7626-7642 ◽  
Author(s):  
Zhengqing Shi ◽  
Junda He ◽  
Tengli Wang ◽  
Chuan Zhou ◽  
Jian Guo
Keyword(s):  
Collision Avoidance ◽  
Formation Control
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