Achieving a desired collective centroid by a formation of agents moving in a controllable force field
28 Mar 2016-pp 182-187
TL;DR: In this article, an all-to-all coupled planar motion model is proposed to solve the problem of a formation of agents trying to achieve a desired stationary or moving collective centroid.
Abstract: In this paper, we study the problem of a formation of agents trying to achieve a desired stationary or moving collective centroid. The agents are assumed to be moving in a force field which is controlled externally. The stabilization of the collective centroid to a fixed desired location results in a balanced formation of the agents about that point. Similarly, the centroid of the system of agents may be required to move along a certain given trajectory. For this, the centroid of the formation must converge to the desired trajectory. To solve this problem, we propose an all-to-all coupled planar motion model that explicitly incorporates an additional control pertaining to the external force field. Simulation results are presented to support the theoretical findings.
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TL;DR: This paper proposes a combined controller to stabilize a formation shape and synchronize the heading of each agent simultaneously and considers several different formation design approaches based on different formation specifications under different interaction graphs.
Abstract: This paper discusses the problem of controlling formation shapes for a group of nonholonomic unicycle-type agents with constant speeds. The control input is designed to steer their orientations and the aim is to achieve a desired formation configuration for all the agents subject to constant-speed constraints. The circular motion center is adopted as a virtual position for each agent to define the desired formation shape. We consider several different formation design approaches based on different formation specifications under different interaction graphs. In particular, two different formation design approaches, namely, a displacement-based approach and a distance-based approach, are discussed in detail to coordinate constant-speed agents in achieving a desired formation shape with stable circular motions via limited interactions. The communication and measurement requirements for each approach are also discussed. Furthermore, we propose a combined controller to stabilize a formation shape and synchronize the heading of each agent simultaneously. The effectiveness of the proposed formation control schemes is validated by both numerical simulations and real experiments with actual unmanned fixed-wing aircraft.
61 citations
Cites background from "Achieving a desired collective cent..."
...Furthermore, some recent papers [18]–[20] have discussed the control problem of a group of unit-speed agents to achieve different collective tasks, e....
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01 Jan 2008
TL;DR: This paper considers the problem of controlling a group of agents under the constraint that every agent must be given the same control input, relevant for the control of mobile micro-robots that all receive the same power and control signals through an underlying substrate.
Abstract: This paper considers the problem of controlling a group of agents under the constraint that every agent must be given the same control input This problem is relevant for the control of mobile micro-robots that all receive the same power and control signals through an underlying substrate Despite this restriction, several examples in simulation demonstrate that it is possible to get a group of micro-robots to perform useful tasks All of these tasks are derived by thinking about the relationships between robots, rather than about their individual states
13 citations
Proceedings Article•
08 May 2020TL;DR: This paper develops a two-phase search algorithm, called SWARM-MAPF, whose first phase is inspired by swarm-based algorithms (in open regions) and whose second phase isinspired by multi-agent path-finding (MAPF) algorithms ( in congested regions).
Abstract: In this paper, we formalize and study the Moving Agents in Formation (MAiF) problem, that combines the tasks of finding short collision-free paths for multiple agents and keeping them in close adherence to a desired formation Previous work includes controller-based algorithms, swarm-based algorithms, and potential-field-based algorithms They usually focus on only one or the other of these tasks, solve the problem greedily without systematic search, and thus generate costly solutions or even fail to find solutions in congested environment In this paper, we develop a two-phase search algorithm, called SWARM-MAPF, whose first phase is inspired by swarm-based algorithms (in open regions) and whose second phase is inspired by multi-agent path-finding (MAPF) algorithms (in congested regions) In the first phase, SWARM-MAPF selects a leader among the agents and finds a path for it that is sufficiently far away from the obstacles so that the other agents can preserve the desired formation around it It also identifies the critical segments of the leader's path where the other agents cannot preserve the desired formation and the refinement of which has thus to be delegated to the second phase In the second phase, SWARM-MAPF refines these segments Theoretically, we prove that SWARM-MAPF is complete Empirically, we show that SWARM-MAPF scales well and is able to find close-to-optimal solutions
4 citations
Additional excerpts
...Examples include behavior-based [1], leader-follower [3], virtual-structure [12], potential-field [11], graph-based [4], and other swarm-based algorithms [9, 13, 21]....
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TL;DR: This paper analyses collective motion of multi-vehicle systems in balanced or splay formation when the vehicles are equipped with heterogeneous controller gains and proposes strategies to achieve such balanced and splay formations about a desired centroid location while allowing the vehicles to move either along straight line paths or on individual circular orbits.
Abstract: This paper analyses collective motion of multi-vehicle systems in balanced or splay formation when the vehicles are equipped with heterogeneous controller gains. Balancing refers to a situation in which the positional centroid of the vehicles is stationary. The splay formation is a special case of balancing in which the vehicles are spatially distributed with equal angular separation between them. The paper proposes strategies to achieve such balanced and splay formations about a desired centroid location while allowing the vehicles to move either along straight line paths or on individual circular orbits. Feedback control laws that can tolerate heterogeneity in the controller gains, which may be caused by imperfect implementation, are derived and analyzed. It is shown that drastic failures leading to controller gains becoming zero for almost half of the vehicles in the group can be tolerated and balanced formation can still be achieved. On the other hand, splay formation can still be achieved if the controller gain is zero for at most one vehicle. Simulation examples are given to illustrate the theoretical findings.
2 citations
01 Jan 2017
TL;DR: This paper proposes a heterogeneous gains based controller design methodology to stabilize a particular type of collective motion in a multi-agent system where the heading angles of the agents are in balanced formation and derives feedback control laws that operate with heterogeneous control gains.
Abstract: This paper proposes a heterogeneous gains based controller design methodology to stabilize a particular type of collective motion in a multi-agent system where the heading angles of the agents are in balanced formation. Balancing refers to the situation in which the movement of agents causes the position of their centroid to become stationary. Our interest, in this paper, is to achieve balanced formation about a desired location of the centroid while allowing the agents to move either along straight line paths or around individual circular orbits. For this purpose, we derive feedback control laws that operate with heterogeneous control gains, and are more practical compared to the homogeneous gains based controls existing in the literature. We also show that if the heterogeneous control gains are zero for almost half of the agents of the group, it is possible to achieve balanced formation at an additional advantage of reduced computational complexity of the proposed control law. Simulations are given to illustrate the theoretical findings.
1 citations
Cites background or result from "Achieving a desired collective cent..."
...In a similar context, the authors in [9] and [10] propose a steering control which operates with homogeneous control gains, and depends on both positions and heading angles of the agents [9] or only on the heading angles of the agents with an additional external force applied to them [10]....
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...Unlike [9] and [10], in the present work, the proposed feedback control uses heterogeneous control gains that ensures the robustness of the system against variations in the homogeneous control gains caused by physical implementation (by means of some electrical circuitry)....
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...However, unlike [9] and [10], in this paper, we generalize existing results and propose a more realistic steering control law which uses heterogeneous control gains....
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References
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14 May 2012
TL;DR: This paper constructs a discrete-time model for the cell dynamics that is based on first principle, and formulate a model predictive approach for feedback control of magnetotactic T. pyriformis cells.
Abstract: The use of live microbial cells as microscale robots is an attractive premise, primarily because they are easy to produce and to fuel. In this paper, we study the motion control of magnetotactic Tetrahymena pyriformis cells. Magnetotactic T. pyriformis is produced by introducing artificial magnetic dipole into the cells. Subsequently, they can be steered by using an external magnetic field. We observe that the external magnetic field can only be used to affect the swimming direction of the cells, while the swimming velocity depends largely on the cells' own propulsion. Feedback information for control is obtained from a computer vision system that tracks the cell. The contribution of this paper is twofold. First, we construct a discrete-time model for the cell dynamics that is based on first principle. Subsequently, we identify the model parameters using the Least Squares approach. Second, we formulate a model predictive approach for feedback control of magnetotactic T. pyriformis. Both the model fitness and the performance of the feedback controller are verified using experimental data.
14 citations
"Achieving a desired collective cent..." refers methods in this paper
...[29] present a model predictive control algorithm to control the magneto-tactic Tetrahymena pyriformis....
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01 Jan 2008
TL;DR: This paper considers the problem of controlling a group of agents under the constraint that every agent must be given the same control input, relevant for the control of mobile micro-robots that all receive the same power and control signals through an underlying substrate.
Abstract: This paper considers the problem of controlling a group of agents under the constraint that every agent must be given the same control input This problem is relevant for the control of mobile micro-robots that all receive the same power and control signals through an underlying substrate Despite this restriction, several examples in simulation demonstrate that it is possible to get a group of micro-robots to perform useful tasks All of these tasks are derived by thinking about the relationships between robots, rather than about their individual states
13 citations
"Achieving a desired collective cent..." refers background in this paper
...There has been considerable interest in recent times on control of multiple agents that are under the influence of external control signals broadcast to the agent collective [20], [21]....
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18 Aug 2008
TL;DR: A planar motion model that explicitly incorporates a flow field and, for uniform and constant flows, is introduced that provides decentralized control algorithms that stabilize basic motion primitives in the model.
Abstract: Decentralized, cooperative control algorithms enable autonomous sensing platforms to conduct synoptic, adaptive surveys of dynamic spatiotemporal processes. Often these sensing platforms are advected by strong and variable flow fields—i.e., winds in the atmosphere and currents in the ocean. Existing cooperative control algorithms are based on simple models of vehicle motion that do not consider an external flow field. In this paper, we introduce a planar motion model that explicitly incorporates a flow field and, for uniform and constant flows, we provide decentralized control algorithms that stabilize basic motion primitives in the model. The motion primitives include synchronized motion, in which all of the vehicles move in the same direction with arbitrary separation; balanced motion, in which the centroid of vehicle positions is fixed; and circular motion, in with all of the particles travel around a circle with a fixed center. By introducing a virtual particle that serves as reference, we derive a circular-motion algorithm that stabilizes motion around a prescribed center point.
11 citations
Additional excerpts
...An important contribution to this literature are the works by Paley [12], [13] which addresses the problem of stabilizing the collective motion of the agents in a uniform and constant flow field....
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17 Jun 2013
TL;DR: It is shown that, by selecting suitable controller gains, these formations can be controlled significantly to obtain not only a desired direction of motion but also a desired location of the centroid.
Abstract: In this paper, we study the collective motion of individually controlled planar particles when they are coupled through heterogeneous controller gains. Two types of collective formations, synchronization and balancing, are described and analyzed under the influence of these heterogeneous controller gains. These formations are characterized by the motion of the centroid of the group of particles. In synchronized formation, the particles and their centroid move in a common direction, while in balanced formation the movement of particles possess a fixed location of the centroid. We show that, by selecting suitable controller gains, these formations can be controlled significantly to obtain not only a desired direction of motion but also a desired location of the centroid. We present the results for N-particles in synchronized formation, while in balanced formation our analysis is confined to two and three particles.
10 citations
"Achieving a desired collective cent..." refers background or methods in this paper
...Therefore, as an extension, [9] introduces heterogeneous coupling among agents to obtain a desired velocity direction (in synchronized formation) and a desired location of the centroid (in balanced formation)....
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...Previous works in this area deal with the stabilization of these formations when the agents are coupled through homogeneous [7] and heterogeneous [9] controller gains....
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...To achieve the balanced formation about a desired location of the centroid, the analysis in [9] is limited to two and three agents....
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10 Dec 2007
TL;DR: Comparisons of the simulation results show the improved performance of the new control law, and an alternative control law is proposed in the paper.
Abstract: This paper presents a study which extends previous work on collective motion control of a group of vehicles for target tracking. The approach is to drive the group centroid to follow a moving target while keeping all vehicles near the centroid. The provided analysis shows that the system is stable. However, the tracking performance is sensitive to imperfect communication and steering dynamics. Simulation results show the performance degrades significantly when delays and steering dynamics are present. An analysis is provided to identify a major cause of the performance degradation. An alternative control law is proposed in the paper. Comparisons of the simulation results show the improved performance of the new control law.
6 citations
"Achieving a desired collective cent..." refers background in this paper
...[18] propose a control algorithm to match the average vehicle velocity to a reference velocity, which is either constant or varies with time....
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