Decentralized Cohesive Motion Control of Multi-Agent Formations

Sandeep, S.R.; Fi̇dan, Barış; Yu, Changbin

doi:10.1109/med.2006.328692

Cited by 30 publications

(30 citation statements)

References 7 publications

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“…) (i For simplicity, for each agent " i ", the kinematic model [7] ) (iv using their own positions w.r.t the global coordinate system and relative distance and bearing information in ) (ii w.r.t respective cartesian coordinate system fixed on their (first follower and ordinary follower) point bodies; positions of other agents can be converted with respect to the global coordinate system It is intended to provide a control scheme for this triangular formation (starting from a non-collinear arrangement) such that during the motion of three robots for any mission, desired inter-agent distances are preserved.…”

Section: Assumptionmentioning

confidence: 99%

“…Due to these problems decentralized control is recommended when formation involves a large number of agents. In the decentralized mode of control [ 4,5,7], one agent of the group can be a leader and others are followers (or each agent of the group can be a leader and follower except a designated group leader and the two outmost agents) and as a follower each agent generates its own commands autonomously (i.e. control law for each agent is provided separately such that each agent works autonomously) based on the relative measurement only from its neighbours without need of an external supervisor and whole purpose of the formation motion is achieved.…”

Section: Introductionmentioning

confidence: 99%

“…In [7], formation control strategy of leaderfollower and three coleader structures is set up based on discrete-time motion equations considering decentralized approach. In [8], Anderson et al analyzed control of leaderfollower structure with cycles, in continuous domain assuming linearized system for small displacement and stability aspects are also discussed.…”

Section: Introductionmentioning

confidence: 99%

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A New Algorithm for Motion Control of Leader-Follower Formation of Mobile Autonomous Agents

Atta¹,

Subudhi²

2010

IJCA

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This paper presents a motion control strategy for a rigid and constraint consistent formation that can be modeled by a directed graph whose each vertex represents individual agent kinematics and each of directed edges represents distance constraints maintained by an agent, called follower, to its neighbouring agents. A rigid and constraint consistent graph is called persistent graph. A persistent graph is minimally persistent if it is persistent and no edge can be removed without losing its persistence. An acyclic (free of cycles in its sensing pattern) minimally persistent graph of Leader-Follower structure has been considered here and which can be constructed from an initial LeaderFollower seed (initial graph with two vertices, one is Leader and another one is First Follower and one edge in between them is directed towards Leader) by Henneberg sequence (a procedure of growing a graph) containing only vertex additions. A set of nonlinear optimization based decentralized control laws for mobile autonomous point agents in plane have been proposed. An infinitesimal deviation in formation shape created by continuous motion of Leader is compensated by corresponding continuous motion of other agents fulfilling the shortest path criteria.

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Section: Assumptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A New Algorithm for Motion Control of Leader-Follower Formation of Mobile Autonomous Agents

Atta¹,

Subudhi²

2010

IJCA

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show abstract

“…Splitting/rejoining can be one solution to avoid collision with the obstacles [4], as suggested by observation of fish swarms: the swarm of fish will split into two parts, each of which goes one side of the obstacle. Another approach [3], [4] is to move the entire formation to one side of the obstacle and this is the approach we use in this paper. Different methods for moving the formation as a whole around an obstacle are introduced in [3], [4]: Line-of-Sight Obstacle Avoidance, Nearest Effective Obstacle Avoidance and Sheepdog Approach.…”

Section: Introductionmentioning

confidence: 99%

“…Another approach [3], [4] is to move the entire formation to one side of the obstacle and this is the approach we use in this paper. Different methods for moving the formation as a whole around an obstacle are introduced in [3], [4]: Line-of-Sight Obstacle Avoidance, Nearest Effective Obstacle Avoidance and Sheepdog Approach. Among these, we use Line-of-Sight Obstacle Avoidance in this paper, mainly because the principles of this approach fit well in vision based formation control implementation.…”

Section: Introductionmentioning

confidence: 99%

Single view depth estimation based formation control of robotic swarms: Obstacle avoidance, simulation, and practical issues

Zhai

Fi̇dan

Öztürk³

et al. 2008

2008 16th Mediterranean Conference on Control and Automation

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Abstract-In a companion paper we have presented a practical formation motion control scheme for robotic swarms based on single view depth estimation. In this paper we adapt this control scheme to the cases where there are obstacles to be avoided in the region of interest. First, a set of distributed control laws for the agents, to be incorporated with depth (distance) estimation scheme, are introduced to move the formation from an arbitrary initial position to an arbitrary final position without deforming the formation shape or having a collision with an obstacle. Then, we present simulation results on formation control using the proposed control scheme for both obstacle free and with obstacle cases. We later discuss certain practical issues regarding the proposed scheme. The robots do not have any global positioning sensors, and they do not communicate with each other. The performance of the overall system as well as the effects of delay and quantization in estimation of distance are analyzed via simulations.

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UAV Formation Control: Theory and Application

Anderson

Fi̇dan

et al.

Lecture Notes in Control and Information Sciences

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161

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Unmanned airborne vehicles (UAVs) are finding use in military operations and starting to find use in civilian operations. UAVs often fly in formation, meaning that the distances between individual pairs of UAVs stay fixed, and the formation of UAVs in a sense moves as a rigid entity. In order to maintain the shape of a formation, it is enough to maintain the distance between a certain number of the agent pairs; this will result in the distance between all pairs being constant. We describe how to characterize the choice of agent pairs to secure this shape-preserving property for a planar formation, and we describe decentralized control laws which will stably restore the shape of a formation when the distances between nominated agent pairs become unequal to their prescribed values. A mixture of graph theory, nonlinear systems theory and linear algebra is relevant. We also consider a particular practical problem of flying a group of three UAVs in an equilateral triangle, with the centre of mass following a nominated trajectory reflecting constraints on turning radius, and with a requirement that the speeds of the UAVs are constant, and nearly (but not necessarily exactly) equal.

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Decentralized Cohesive Motion Control of Multi-Agent Formations

Cited by 30 publications

References 7 publications

A New Algorithm for Motion Control of Leader-Follower Formation of Mobile Autonomous Agents

A New Algorithm for Motion Control of Leader-Follower Formation of Mobile Autonomous Agents

Single view depth estimation based formation control of robotic swarms: Obstacle avoidance, simulation, and practical issues

UAV Formation Control: Theory and Application

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