An Efficient, Time-of-Flight-Based Underwater Acoustic Ranging System for Small Robotic Fish

Shatara, Stephan; Tan, Xiaobo

doi:10.1109/joe.2010.2060810

Cited by 23 publications

(13 citation statements)

References 35 publications

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“…Consequently, the signal processing approach is not amenable to online implementation. To address this problem, we will use a sliding discrete Fourier transform (SDFT) [46,47] to update the signal amplitude as new data samples come in. This will not only allow us to perform source localization in real time, but will also enable the tracking of a moving dipole source, where the received signal amplitude is time-varying.…”

Section: Discussionmentioning

confidence: 99%

An artificial lateral line system using IPMC sensor arrays

Abdulsadda

Tan

2012

International Journal of Smart and Nano Materials

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Most fish and aquatic amphibians use the lateral line system, consisting of arrays of hair-like neuromasts, as an important sensory organ for prey/predator detection, communication, and navigation. In this paper a novel bio-inspired artificial lateral line system is proposed for underwater robots and vehicles by exploiting the inherent sensing capability of ionic polymer-metal composites (IPMCs). Analogous to its biological counterpart, the IPMC-based lateral line processes the sensor signals through a neural network. The effectiveness of the proposed lateral line is validated experimentally in the localization of a dipole source (vibrating sphere) underwater. In particular, as a proof of concept, a prototype with body length (BL) of 10 cm, comprising six millimeter-scale IPMC sensors, is constructed and tested. Experimental results have shown that the IPMC-based lateral line can localize the source from 1-2 BLs away, with a maximum localization error of 0.3 cm, when the data for training the neural network are collected from a grid of 2 cm by 2 cm lattices. The effect of the number of sensors on the localization accuracy has also been examined.

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Section: Discussionmentioning

confidence: 99%

An artificial lateral line system using IPMC sensor arrays

Abdulsadda

Tan

2012

International Journal of Smart and Nano Materials

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“…The proof that Q A 1 (Y,Ĝ) + μ sin(ζ) cos(θ) > M 1 when (ρ 1 , ζ) ∈ DE for large enough K 1 is analogous, because for all such points, we have h 1 (ρ 1 ) ≥ h 1 (ρ * 1 +ζ/μ + K 1 ) > 0 when K 1 is large enough, ζ ≤ 0, and nonpositivity of the term in curly braces in (33), and because lim s→+∞ h 1 (s) = +∞. This proves (C1).…”

Section: Adaptive Controlmentioning

confidence: 93%

“…when ρ * 1 > 0 is small enough and μ > 0 is large enough, using the nonnegativity of the term in curly braces in (33) along AB, the fact that 0 < cos(ζ) ≤ cos(ζ) ≤ 1 on H 1 (ρ * 1 ,ζ, K 1 )× H 2 (ρ * 2 ,θ, K 2 ), and the fact that lim s→0 + h 1 (s) = −∞ to use h 1 (ρ * 1 + ζ/μ ) to cancel the effects of the other terms in (33). The proof that Q A 1 (Y,Ĝ) + μ sin(ζ) cos(θ) > M 1 when (ρ 1 , ζ) ∈ DE for large enough K 1 is analogous, because for all such points, we have h 1 (ρ 1 ) ≥ h 1 (ρ * 1 +ζ/μ + K 1 ) > 0 when K 1 is large enough, ζ ≤ 0, and nonpositivity of the term in curly braces in (33), and because lim s→+∞ h 1 (s) = +∞.…”

Section: Adaptive Controlmentioning

confidence: 99%

Robustness of Adaptive Control under Time Delays for Three-Dimensional Curve Tracking

Malisoff¹,

Zhang²

2015

SIAM J. Control Optim.

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We analyze the robustness of a class of controllers that enable three-dimensional curve tracking by a free moving particle. The free particle tracks the closest point on the curve. By building a strict Lyapunov function and robustly forward invariant sets, we show input-to-state stability under predictable tolerance and safety bounds that guarantee robustness under control uncertainty, input delays, and a class of polygonal state constraints, including adaptive tracking and parameter identification under unknown control gains. Such an understanding may provide certified performance when the control laws are applied to real-life systems. Introduction.Curve tracking is a central problem in control and path planning for mobile robots [1,8,27,36,37]. The work presented in [39] used a nonstrict Lyapunov function to find feedback controllers that ensure that a robot moves parallel to a two-dimensional (2D) curve. See also [32] for chained form systems that capture the nonholonomic dynamics of a large variety of mobile robots, such as a kinematic car with trailers, which led to extended curve tracking control laws, and [12] for a reformulation of 2D curve tracking in the three-dimensional (3D) case. Curve tracking is also important for cooperative controllers that track motion for multiple mobile robots; see [38] for applications to ocean sensing. The controls in the works cited above have been found to give reliable performance, even under severe perturbations, in farming [18], obstacle avoidance in corridors [41], and ocean sampling [38].Given a curve tracking control, we are interested in deriving predictable safety and tolerance bounds under several types of uncertainty and input delays, and in identifying unknown control gains. To this end, this paper presents novel 3D analogs of the robustness results that we derived for 2D in [20,21]. For 2D tracking, [20] proved robustness using input-to-state stability (ISS) with respect to actuator errors and robust forward invariance, which gave predictable tolerance and safety bounds under time delays and a class of polygonal state constraints. Briefly described, robust forward invariance means forward invariance in the usual sense of differential equations, but that is also preserved under perturbations; see section 3 for the precise definition. Actuator errors can be modeled as additive perturbations on controls, and communication delays are also common [6, 16], e.g., in marine robotics where there may only be intermittent communications under unfriendly sea conditions. In

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“…Following [19] a SDFT is applied to the digitally sampled data in real time. The SDFT presents the advantage of being computationally efficient when interested in a specific bin and not the full frequency spectrum of the Discrete Fourier Transform (DFT).…”

Section: Signal Detection and Delay Estimationmentioning

confidence: 99%

Low cost underwater acoustic localization

Ruland

Johnson-Roberson

2017

The Journal of the Acoustical Society of America

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Abstract. Over the course of the last decade, the cost of marine robotic platforms has significantly decreased. In part this has lowered the barriers to entry of exploring and monitoring larger areas of the earth's oceans. However, these advances have been mostly focused on autonomous surface vessels (ASVs) or shallow water autonomous underwater vehicles (AUVs). One of the main drivers for high cost in the deep water domain is the challenge of localizing such vehicles using acoustics. A low cost one-way travel time (OWTT) underwater ranging system is proposed to assist in localizing deep water submersibles. The system consists of location aware anchor buoys at the surface and underwater nodes. This paper presents a comparison of methods together with details on the physical implementation to allow its integration into a deep sea micro AUV currently in development. Additional simulation results show error reductions by a factor of three.

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An Efficient, Time-of-Flight-Based Underwater Acoustic Ranging System for Small Robotic Fish

Cited by 23 publications

References 35 publications

An artificial lateral line system using IPMC sensor arrays

An artificial lateral line system using IPMC sensor arrays

Robustness of Adaptive Control under Time Delays for Three-Dimensional Curve Tracking

Low cost underwater acoustic localization

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