Nonholonomic Source Seeking With Tuning of Angular Velocity

Cochran, Jennie; Krstić, Miroslav

doi:10.1109/tac.2009.2014927

Cited by 219 publications

(159 citation statements)

References 19 publications

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“…The second step corresponds to the tracking control design. In order to achieve the objective r k →r k + c, the tracking error is defined by (4). With a view to make the error converge to zero, we wish to impose the error dynamics…”

Section: Theorem 1 Consider a Twice Differentiable Function C(t)mentioning

confidence: 99%

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Cooperative translation control based on consensus with reference velocity: A source-seeking application

Briñón-Arranz

Seuret

2013

2013 European Control Conference (ECC)

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Abstract-This paper deals with the design of cooperative control laws for nonlinear multi-agent systems. On the first hand, the control objectives are to ensure that a group of agents reaches a time-varying circular formation characterized by some external references representing the position of the center of the formation and its derivatives. In order to reduce the amount of information to be shared, the second part of the paper considers the situation where only the velocity of the center of the formation is available to each agent. Then a distributed consensus algorithm is provided in order to satisfy the same control objectives. Finally, an application to the source-seeking problem is proposed to emphasize previous contribution. These results are supported through computer simulations.

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Section: Theorem 1 Consider a Twice Differentiable Function C(t)mentioning

confidence: 99%

“…The source localization of a signal distribution is a problem considered in recent literature [4], [11]. There are different approaches to deal with this topic, but the common alexandre.seuret at laas.fr objective is to calculate the position of the source using measurements of the signal propagation.…”

Section: Introductionmentioning

confidence: 99%

Cooperative translation control based on consensus with reference velocity: A source-seeking application

Briñón-Arranz

Seuret

2013

2013 European Control Conference (ECC)

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“…While others executed gradient based source seeking techniques by deploying a team of seekers to form a mobile sensor network 4,[8][9][10][11] to track the gradient of the source. Recently, there has been some work in 12,13 where the authors adopted the extremum seeking technique originally developed in. 14 This perturbation-based extremum seeking method essentially still relies on the gradient information derived from robots' movement.…”

Section: Introductionmentioning

confidence: 99%

Standard Particle Swarm Optimization on Source Seeking Using Mobile Robots

Zou

Kalivarapu

Bhattacharya

et al. 2015

56th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

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In this paper, we explore the implementation of standard particle swarm optimization (SPSO) on a swarm of physical mobile robots conducting a source seeking task. The signal source is electromagnetic, whose strength is non-differentiable at many points making most gradient based source seeking strategies ineffective in this scenario. We analyze the physical limitations of the robots and modify SPSO accordingly to make them compatible with each other. We also compare different SPSO topology models to determine the one best suited for our problem. Finally, we incorporate obstacle avoidance strategies into PSO, and compare the performance of original PSO, SPSO 2006 and SPSO 2011 in a complex environment with obstacles. Simulation results demonstrate the efficacy of implementing SPSO to robot source seeking problem. Moreover, it is shown that SPSO 2011 is not only superior as an optimization method, but also provides better performance in robotic implementation compared to SPSO 2006 and original PSO. DisciplinesAeronautical Vehicles | Electro-Mechanical Systems | Navigation, Guidance, Control and Dynamics | Robotics | Signal Processing CommentsThis is a manuscript of a proceeding published as Zou, Rui, Vijay Kalivarapu, E. Winer, J. Oliver, and S. Bhattacharya. "Standard particle swarm optimization on source seeking using mobile robots. In this paper, we explore the implementation of standard particle swarm optimization (SPSO) on a swarm of physical mobile robots conducting a source seeking task. The signal source is electromagnetic, whose strength is non-differentiable at many points making most gradient based source seeking strategies ineffective in this scenario. We analyze the physical limitations of the robots and modify SPSO accordingly to make them compatible with each other. We study the implementation of SPSO in an environment where obstacles and collisions exist and compare the results of this implementation with a basic PSO that was implemented in our prior work.

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“…Unlike the existing results, e.g., [1]- [5], we are interested in the stochastic source seeking, which involves a randomly switching field, and we want to solve it for a general class of mobile robots. This is motivated by two facts.…”

Section: Introductionmentioning

confidence: 99%

“…Next, to our best knowledge, there is no solution dealing with various types of robots in a unified way. In fact, the existing results have focused on specific robots, e.g., integrators in [3], nonholonomic unicycles in [2], [4], [5], and underwater vehicles [1].…”

Section: Introductionmentioning

confidence: 99%

Nonholonomic source seeking in switching random fields

Azuma

Sakar

Pappas

2010

49th IEEE Conference on Decision and Control (CDC)

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Abstract-We consider the problem of designing controllers for nonholonomic mobile robots converging to the source (minimum) of a field. In addition to the mobility constraints posed by the nonholonomic dynamics, we assume that the field is completely unknown to the robot and the robot has no knowledge of its own position. Furthermore, the field is randomly switching. In this paper, we combine ideas from stochastic approximations and nonholonomic control, in order to address this challenging problem. In particular, we develop a rotation-invariant and forward-sided version of the simultaneous-perturbation stochastic algorithm, which is much more suitable for sensorfree navigation. Based on this algorithm, we design source seeking controllers for nonholonomic robots and prove convergence to the unknown source with probability 1. The proposed controllers are demonstrated by numerical simulations.

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Nonholonomic Source Seeking With Tuning of Angular Velocity

Cited by 219 publications

References 19 publications

Cooperative translation control based on consensus with reference velocity: A source-seeking application

Cooperative translation control based on consensus with reference velocity: A source-seeking application

Standard Particle Swarm Optimization on Source Seeking Using Mobile Robots

Nonholonomic source seeking in switching random fields

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