Overshoot-Free Steering-Based Source Seeking

Raisch, Adrian; Krstić, Miroslav

doi:10.1109/tcst.2016.2583383

Cited by 15 publications

(9 citation statements)

References 26 publications

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“…An extension of this method was presented in [7], where a filter was added to the sensor measurement to improve the transient behavior. Furthermore, by combining the feedback laws from [4] and [27] the transient and asymptotic behavior of the source seeking algorithm is enhanced in [25]. It was conjectured in [1], that sperm chemotaxis is a biological implementation of the source seeking algorithm from [27,7].…”

Section: Related Workmentioning

confidence: 99%

“…In order to verify the performance of the PT-control feedback law (26) for the point mass vehicle (21), we simulate the point mass PT-seeker (25) and compare it to the exponential source seeking schemes proposed in [8] and [34]. These schemes were already used as a motivation for our source seeking design on I τ and are given in equation (24).…”

Section: Introduction To Pt-source Seekingmentioning

confidence: 99%

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Practical Prescribed-Time Seeking of a Repulsive Source by Unicycle Angular Velocity Tuning

Velimir¹,

Krstić²

2022

Preprint

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All the existing source seeking algorithms for unicycle models in GPS-denied settings guarantee at best an exponential rate of convergence over an infinite interval. Using the recently introduced time-varying feedback tools for prescribed-time stabilization, we achieve source seeking in prescribed time, i.e., the convergence to the source, without the measurements of the position and velocity of the unicycle, in as short a time as the user desires, starting from an arbitrary distance from the source. The convergence is established using a singularly perturbed version of the Lie bracket averaging method, combined with time dilation and time contraction operations. The algorithm is robust, provably, even to an arbitrarily strong gradient-dependent repulsive velocity drift emanating from the source.

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Section: Related Workmentioning

confidence: 99%

Section: Introduction To Pt-source Seekingmentioning

confidence: 99%

Practical Prescribed-Time Seeking of a Repulsive Source by Unicycle Angular Velocity Tuning

Velimir¹,

Krstić²

2022

Preprint

Self Cite

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“…The idea of ESC emerged in the context of gradientfree optimization [21], having since spread to applications in model-free control, adaptive control, and source seeking [22], [23], [24], [5], [6], [10], [11], [25]. The basic ESC loop is shown in Fig.…”

Section: B Sinusoidal Extremum Seeking Controlmentioning

confidence: 99%

Source Seeking in Unknown Environments with Convex Obstacles

Angélico

Chamon

Paternain

et al. 2021

2021 American Control Conference (ACC)

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Navigation tasks often cannot be defined in terms of a target, either because global position information is unavailable or unreliable or because target location is not explicitly known a priori. This task is then often defined indirectly as a source seeking problem in which the autonomous agent navigates so as to minimize the convex potential induced by a source while avoiding obstacles. This work addresses this problem when only scalar measurements of the potential are available, i.e., without gradient information. To do so, it construct an artificial potential over which an exact gradient dynamics would generate a collision-free trajectory to the target in a world with convex obstacles. Then, leveraging extremum seeking control loops, it minimizes this artificial potential to navigate smoothly to the source location. We prove that the proposed solution not only finds the source, but does so while avoiding any obstacle. Numerical results with velocityactuated particles, simulations with an omni-directional robot in ROS+Gazebo, and a robot-in-the-loop experiment are used to illustrate the performance of this approach.

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“…While sinusoidal dither signals are used in the aforementioned works, filtered white noise dither signals have been used in [37], [38], [39] that are commonly known as the stochastic source seeking methods. In [45], Raisch and Krstic combined two kinds of perturbation signals (periodic-based and constant-based) for an efficient convergence toward the source and maintaining tight hovering near the source. By bounding the update rate in the optimum seeking and stabilization control law, Scheinker and Krstic proposed a new constrained ESC scheme [46], which is advantageous to the hardware control implementation [47] and is generalized in [48].…”

Section: Introductionmentioning

confidence: 99%

Source Seeking Control of Unicycle Robots with 3D-printed Flexible Piezoresistive Sensors

Li,

Jayawardhana,

Kamat

et al. 2021

Preprint

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We present the design and experimental validation of source seeking control algorithms for a unicycle mobile robot that is equipped with novel 3D-printed flexible graphenebased piezoresistive airflow sensors. Based solely on a local gradient measurement from the airflow sensors, we propose and analyze a projected gradient ascent algorithm to solve the source seeking problem. In the case of partial sensor failure, we propose a combination of Extremum-Seeking Control with our projected gradient ascent algorithm. For both control laws, we prove the asymptotic convergence of the robot to the source. Numerical simulations were performed to validate the algorithms and experimental validations are presented to demonstrate the efficacy of the proposed methods.

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Overshoot-Free Steering-Based Source Seeking

Cited by 15 publications

References 26 publications

Practical Prescribed-Time Seeking of a Repulsive Source by Unicycle Angular Velocity Tuning

Practical Prescribed-Time Seeking of a Repulsive Source by Unicycle Angular Velocity Tuning

Source Seeking in Unknown Environments with Convex Obstacles

Source Seeking Control of Unicycle Robots with 3D-printed Flexible Piezoresistive Sensors

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