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.

A Collision Avoidance Control of Multiple Mobile Agents Based on Active Sensing

2021 ◽  
Vol 2021 (0) ◽  
pp. 1P3-F09
Author(s):  
Takeru KANNO ◽  
Taishi MIKAMI ◽  
Yasufumi YAMADA ◽  
Mayuko IWAMOTO ◽  
Daishin UEYAMA ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Mobile Agents ◽  
Active Sensing ◽  
Collision Avoidance Control ◽  
Avoidance Control ◽  
Multiple Mobile Agents

scholarly journals Probabilistic Search and Track with Multiple Mobile Agents

2019 ◽  
Author(s):  
Savvas Papaioannou ◽  
Panayiotis Kolios ◽  
Theocharis Theocharides ◽  
Christos G. Panayiotou ◽  
Marios M. Polycarpou
Keyword(s):  
Mobile Agents ◽  
Probabilistic Search ◽  
Multiple Mobile Agents

scholarly journals Balanced Parallel Exploration of Orthogonal Regions

Algorithms ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 104
Author(s):  
Wyatt Clements ◽  
Costas Busch ◽  
Limeng Pu ◽  
Daniel Smith ◽  
Hsiao-Chun Wu
Keyword(s):  
Mobile Agents ◽  
Online Algorithm ◽  
Total Work ◽  
Entire Area ◽  
Asymptotically Optimal ◽  
Face To Face ◽  
Exploration Time ◽  
Unknown Area ◽  
Agent Coordination ◽  
Multiple Mobile Agents

We consider the use of multiple mobile agents to explore an unknown area. The area is orthogonal, such that all perimeter lines run both vertically and horizontally. The area may consist of unknown rectangular holes which are non-traversable internally. For the sake of analysis, we assume that the area is discretized into N points allowing the agents to move from one point to an adjacent one. Mobile agents communicate through face-to-face communication when in adjacent points. The objective of exploration is to develop an online algorithm that will explore the entire area while reducing the total work of all k agents, where the work is measured as the number of points traversed. We propose splitting the exploration into two alternating tasks, perimeter and room exploration. The agents all begin with the perimeter scan and when a room is found they transition to room scan after which they continue with perimeter scan until the next room is found and so on. Given the total traversable points N, our algorithm completes in total O ( N ) work with each agent performing O ( N / k ) work, namely the work is balanced. If the rooms are hole-free the exploration time is also asymptotically optimal, O ( N / k ) . To our knowledge, this is the first agent coordination algorithm that considers simultaneously work balancing and small exploration time.

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