Coordinated patterns of unit speed particles on a closed curve

Zhang, Fumin; Leonard, Naomi Ehrich

doi:10.1016/j.sysconle.2006.10.027

Cited by 121 publications

(98 citation statements)

References 22 publications

(31 reference statements)

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“…Email: jkim37@mail.gatech.edu, {fumin,magnus}@ece.gatech.edu law was used to model the interaction of a particle with an image particle representing the closest point on a closed curve bounding an obstacle. This controller design method was generalized to cooperative motion patterns on closed curves for multiple vehicles in [4], [5], [6]. The closest point is also used for path following in [7].…”

Section: Introductionmentioning

confidence: 99%

Curve Tracking Control for Autonomous Vehicles with Rigidly Mounted Range Sensors

Kim

Zhang

Egerstedt

2009

J Intell Robot Syst

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Abstract-In this paper, we present a feedback control law to make an autonomous vehicle with rigidly mounted range sensors track a desired curve. In particular, we consider a vehicle which has two range sensors that emit rays perpendicular to the velocity of the vehicle. Under such a sensor configuration, singularities are bound to occur in the feedback control law. Thus, to overcome this, we derive a hybrid strategy of switching between control laws close to the singularity.

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Section: Introductionmentioning

confidence: 99%

Curve Tracking Control for Autonomous Vehicles with Rigidly Mounted Range Sensors

Kim

Zhang

Egerstedt

2009

J Intell Robot Syst

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“…Therefore, it is piecewise uniformly continuous on [0, ∞) in the sense of the definition from [15]. We notice that discontinuous commands such as steps or square waves satisfy these conditions.…”

Section: M-mracmentioning

confidence: 97%

On the Robustness Properties of M-MRAC

Stepanyan

Krishnakumar

2012

Infotech@Aerospace 2012

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The paper presents performance and robustness analysis of the modified reference model MRAC (model reference adaptive control) or M-MRAC in short, which differs from the conventional MRAC systems by feeding back the tracking error to the reference model. The tracking error feedback gain in concert with the adaptation rate provides an additional capability to regulate not only the transient performance of the tracking error, but also the transient performance of the control signal. This differs from the conventional MRAC systems, in which we have only the adaptation rate as a tool to regulate just the transient performance of the tracking error. It is shown that the selection of the feedback gain and the adaptation rate resolves the tradeoff between the robustness and performance in the sense that the increase in the feedback gain improves the behavior of the adaptive control signal, hence improves the systems robustness to time delays (or unmodeled dynamics), while increasing the adaptation rate improves the tracking performance or systems robustness to parametric uncertainties and external disturbances.

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“…The interpretation here is that, as fish pay more attention to near-by fish, the square norm counter-acts this by penalizing far-away fish in an overly aggressive manner. If the robots are supposed to arrange themselves at a prescribed inter-robot distance δ, we obtain a formation control protocol, [16], [24], [46]- [49], as opposed to a rendezvous protocol. An example of this found in [14] is given by…”

Section: Weighted Protocolsmentioning

confidence: 99%

“…A number of algorithms that satisfy these four constraints have been proposed and they have been used successfully for achieving and maintaining formations [15]- [18], for covering areas [19]- [21], for securing and tracking boundary curves [22]- [24], or for mimicking biological social behaviors such as flocking and swarming [25]- [28]. In this overview, we illustrate some of the common features and unifying assumptions behind this body of work.…”

Section: Introductionmentioning

confidence: 99%

Coordinated Control of Multi-Robot Systems: A Survey

Cortés

Egerstedt

2017

SICE Journal of Control, Measurement, and System Integration

131

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: Recently, significant gains have been made in our understanding of multi-robot systems, and such systems have been deployed in domains as diverse as precision agriculture, flexible manufacturing, environmental monitoring, search-and-rescue operations, and even swarming robotic toys. What has enabled these developments is a combination of technological advances in performance, price, and scale of the platforms themselves, and a new understanding of how the robots should be organized algorithmically. In this paper, we focus on the latter of these advances, with particular emphasis on decentralized control and coordination strategies as they pertain to multi-robot systems. The paper discusses a class of problems related to the assembly of preferable geometric shapes in a decentralized manner through the formulation of descent-based algorithms defined with respect to team-level performance costs.

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Coordinated patterns of unit speed particles on a closed curve

Cited by 121 publications

References 22 publications

Curve Tracking Control for Autonomous Vehicles with Rigidly Mounted Range Sensors

Curve Tracking Control for Autonomous Vehicles with Rigidly Mounted Range Sensors

On the Robustness Properties of M-MRAC

Coordinated Control of Multi-Robot Systems: A Survey

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