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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TL;DR: A second generation motorized nanocar was designed, synthesized, and imaged to verify structural integrity, and all signals in (1)H NMR were unambiguously assigned, and the results were consistent with the helical structure of the motor.
Abstract: A second generation motorized nanocar was designed, synthesized, and imaged. To verify structural integrity, NMR-based COSY, NOESY, DEPT, HSQC, and HMBC experiments were conducted on the intermediate motor. All signals in 1H NMR were unambiguously assigned, and the results were consistent with the helical structure of the motor. The nanocar was deposited on a Cu(111) surface, and single intact molecules were imaged by scanning tunneling microscopy (STM) at 5.7 K, thereby paving the way for future single-molecule studies of this motorized nanocar atop planar substrates.
119 citations
"Achieving a desired collective cent..." refers background in this paper
...[31] present the development of a light driven nano-car....
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14 Jun 2006
TL;DR: In this paper, the authors extend previous work on oscillator models to meet the needs of multi-agent applications in which the motion of the collective centroid of the group must be dynamic.
Abstract: This paper extends previous work on oscillator models to meet the needs of multiagent applications in which the motion of the collective centroid of the group must be dynamic. Individual agents are modeled as unit speed planar kinematic unicycles. A steering control law is derived for each individual so that the velocity of the collective centroid matches a reference velocity, provided the reference speed is less than one. A framework for steering controls is presented such that the unicycles stay near the collective centroid even though the centroid is non-static. Finally, an outer loop controller is proposed to allow tracking of a target vehicle. Simulation results are shown to support analysis.
93 citations
"Achieving a desired collective cent..." refers background or methods in this paper
...Related to the tracking problem, Klein and Morgansen [17], and Pongpunwattana et al. [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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...In order to achieve consensus between the positions of the current and the desired centroids, the concept of the reference velocity is adopted from [17]....
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...Related to the tracking problem, Klein and Morgansen [17], and Pongpunwattana et al....
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TL;DR: In this paper, a self-propelled particle model that incorporates a time-invariant flowfield is proposed to stabilize collective motion in a known flowfield, where each vehicle is represented by a Newtonian particle subject to a gyroscopic steering control.
Abstract: Cooperative steering controls enable mobile sampling platforms to conduct synoptic, adaptive surveys of dynamic spatiotemporal processes by appropriately regulating the space-time separation of their sampling trajectories. Sensing platforms in the air and maritime domains can be pushed off course by strong and variable environmental dynamics. However, most existing cooperative-control algorithms are based on simple motion models that do not include a flowfield. Existing models that include the flowfield often include speed control to compensate for the flow. In this paper, we describe a constant-speed self-propelled particle model that explicitly incorporates a time-invariant flowfield. Each vehicle is represented by a Newtonian particle subject to a gyroscopic steering control. We describe the Lyapunov-based design of decentralized control algorithms that stabilize collective motion in a known flowfield. In the case of a spatially variable flow, we provide an algorithm to stabilize synchronized motion, in which all of the particles move in the same direction, and circular motion, in which all of the particles orbit an inertially fixed point at a constant radius. For a spatially invariant flow, we provide an algorithm to stabilize balanced motion, in which the particle position centroid is inertially fixed, and symmetric circular formations, in which the particle spacing around a circle is temporally regulated. Via the latter algorithm, we provide a method of stabilizing a circular formation in which the particles are evenly spaced in time and the formation is centered on a moving target. The theoretical results are illustrated with two numerical examples based on applications in environmental monitoring and target surveillance.
80 citations
TL;DR: In this article, a decentralized multivehicle coordination algorithm for operation in a spatially or temporally varying flowfield is presented, where each vehicle is represented using a Newtonian particle traveling at constant speed relative to the flow and subject to a steering control.
Abstract: Unmanned vehicles are an effective platform for tracking, surveillance, and reconnaissance missions. Existing control algorithms promote collaboration of unmanned aerial vehicles and other autonomous vehicles. However, these algorithms often fail to account for the degradation of control performance caused by flowfields. This paper presents decentralized multivehicle coordination algorithms designed for operation in a spatially or temporally varying flowfield. Each vehicle is represented using a Newtonian particle traveling at constant speed relative to the flow and subject to a steering control. An algorithm is described that stabilizes a circular formation in a time-varying spatially nonuniform flowfield, assuming that the flowfield is known and does not exceed the particle speed relative to the flow. For a time-varying and spatially uniform flowfield, an algorithm is provided to stabilize a circular formation in which the temporal spacing between particles is regulated. These algorithms are extended by relaxing the assumption that the flow is known: each particle dynamically estimates the flow and uses that estimate in the control. It is shown that including a turning-rate bound does not alter the main results. The theoretical results are supported by numerical simulations that illustrate the coordinated encirclement of a maneuvering target.
68 citations
"Achieving a desired collective cent..." refers background in this paper
...The more general case of the time-varying and spatially nonuniform flow field is given in [15]....
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01 Jan 2007
42 citations
"Achieving a desired collective cent..." refers background in this paper
...The applications have encompassed tracking, environmental monitoring, surveillance, reconnaissance, search and data collection [1]-[6]....
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