Gert Toming

Hydrodynamic pressure sensing with an artificial lateral line in steady and unsteady flows

With the overall goal being a better understanding of the sensing environment from the local perspective of a situated agent, we studied uniform flows and Kármán vortex streets in a frame of reference relevant to a fish or swimming robot. We visualized each flow regime with digital particle image velocimetry and then took local measurements using a rigid body with laterally distributed parallel pressure sensor arrays. Time and frequency domain methods were used to characterize hydrodynamically relevant scenarios in steady and unsteady flows for control applications. Here we report that a distributed pressure sensing mechanism has the capability to discriminate Kármán vortex streets from uniform flows, and determine the orientation and position of the platform with respect to the incoming flow and the centre axis of the Kármán vortex street. It also enables the computation of hydrodynamic features which may be relevant for a robot while interacting with the flow, such as vortex shedding frequency, vortex travelling speed and downstream distance between vortices. A Kármán vortex street was distinguished in this study from uniform flows by analysing the magnitude of fluctuations present in the sensor measurements and the number of sensors detecting the same dominant frequency. In the Kármán vortex street the turbulence intensity was 30% higher than that in the uniform flow and the sensors collectively sensed the vortex shedding frequency as the dominant frequency. The position and orientation of the sensor platform were determined via a comparative analysis between laterally distributed sensor arrays; the vortex travelling speed was estimated via a cross-correlation analysis among the sensors.

FILOSE for Svenning: A Flow Sensing Bioinspired Robot

The trend of biomimetic underwater robots has emerged as a search for an alternative to traditional propeller-driven underwater vehicles. The drive of this trend, as in any other areas of bioinspired and biomimetic robotics, is the belief that exploiting solutions that evolution has already optimized leads to more advanced technologies and devices. In underwater robotics, bioinspired design is expected to offer more energy-efficient, highly maneuverable, agile, robust, and stable underwater robots. The 30,000 fish species have inspired roboticists to mimic tuna [1], rays [2], boxfish [3], eels [4], and others. The development of the first commercialized fish robot Ghostswimmer by Boston Engineering and the development of fish robots for field trials with specific applications in mind (http://www.roboshoal. com) mark a new degree of maturity of this engineering discipline after decades of laboratory trials.

A bio-mimetic design and control of a fish-like robot using compliant structures

This paper presents a bio-mimetic approach to the design and control of a fish-like robot with compliant parts. One of the key contributions of this work is the use of continuous structures instead of discrete assemblies. In this framework, the motion of the robot is accomplished by copying the kinematics of a biological fish swimming in a sub-carangiform mode. The flexible part referred to as the tail is modeled as a cantilever beam with non-uniform cross-section actuated by a time varying moment. The geometrical and inertial properties of the tail are known. The method of assumed mode is used to derive the equations of motion of the tail; a relationship between the applied torque and the lateral line deflections is calculated. The expression of the torque mimicking the midline kinematics of a biological fish is then computed. A prototype implementing the proposed approach is built. Experiments are performed on a given tail in air and in water. The calculated and experimental midline deflections are then compared.

A bio-inspired compliant robotic fish: Design and experiments

This paper studies the modelling, design and fabrication of a bio-inspired fish-like robot propelled by a compliant body. The key to the design is the use of a single motor to actuate the compliant body and to generate thrust. The robot has the same geometrical properties of a subcarangiform swimmer with the same length. The design is based on rigid head and fin linked together with a compliant body. The flexible part is modelled as a non-uniform cantilever beam actuated by a concentrated moment. The dynamics of the compliant body are studied and a relationship between the applied moment and the resulting motion is derived. A prototype that implements the proposed approach is built. Experiments on the prototype are done to identify the model parameters and to validate the theoretical modelling.

Design principle of a biomimetic underwater robot U-CAT

This paper presents a design rationale and describes the design of a biomimetic underwater robot U-CAT. U-CAT is an autonomous, small-size and low cost vehicle, currently under development, for shipwreck penetration. The robot will assist archaeologists during possibly dangerous and expensive shipwreck exploration missions. It reduces the need of using divers, while being able to go to places that remain unreachable for ROVs. U-CAT uses a novel 4-fin actuation that gives the vehicle high maneuverability for operating in complex environments with walls, ropes, nets and other obstacles. The use of fins also allows more quiet motion with respect to the traditional propellers. Fins beat up less sediment from the bottom and the walls, and thus maintain higher visibility for recording a video. The U-CAT will be also equipped with sensors specifically customized for shipwreck exploration tasks.

Myometry-driven compliant-body design for underwater propulsion

Within the broader scope of underwater biomimetics, in this paper we address the relevance of factors such as shape and elasticity distribution in the ability of a compliant device to imitate the kinematic behaviour of a fish. We assess the viability of myometry as a tool to determine candidate mechanical parameters without relying solely on analytical models; we show that we can obtain elasticity distributions that are both consistent with previous theoretical investigations and experimentally better adherent to the passive kinematics of a biological embodiment (rainbow trout).

Flow feature extraction for underwater robot localization: Preliminary results

Underwater robots conventionally use vision and sonar sensors for perception purposes, but recently bio-inspired sensors that can sense flow have been developed. In literature, flow sensing has been shown to provide useful information about an underwater object and its surroundings. In the light of this, we develop an underwater landmark recognition technique which is based on the extraction and comparison of compact flow features. The proposed features are based on frequency spectrum of a pressure signal acquired by a piezo-resistive sensor. We report experiments in semi-natural (human-made flume with obstacles) and natural (river) underwater conditions where the proposed technique successfully recognizes previously visited locations.

Design and application of a fish-shaped lateral line probe for flow measurement

We introduce the lateral line probe (LLP) as a measurement device for natural flows. Hydraulic surveys in rivers and hydraulic structures are currently based on time-averaged velocity measurements using propellers or acoustic Doppler devices. The long-term goal is thus to develop a sensor system, which includes spatial gradients of the flow field along a fish-shaped sensor body. Interpreting the biological relevance of a collection of point velocity measurements is complicated by the fact that fish and other aquatic vertebrates experience the flow field through highly dynamic fluid-body interactions. To collect body-centric flow data, a bioinspired fish-shaped probe is equipped with a lateral line pressure sensing array, which can be applied both in the laboratory and in the field. Our objective is to introduce a new type of measurement device for body-centric data and compare its output to estimates of conventional point-based technologies. We first provide the calibration workflow for laboratory investigations. We then provide a review of two velocity estimation workflows, independent of calibration. Such workflows are required as existing field investigations consist of measurements in environments where calibration is not feasible. The mean difference for uncalibrated LLP velocity estimates from 0 to 50 cm/s under in a closed flow tunnel and open channel flume was within 4 cm/s when compared to conventional measurement techniques. Finally, spatial flow maps in a scale vertical slot fishway are compared for the LLP, direct measurements, and 3D numerical models where it was found that the LLP provided a slight overestimation of the current velocity in the jet and underestimated the velocity in the recirculation zone.

Estimation of Flow Turbulence Metrics With a Lateral Line Probe and Regression

The time-averaged velocity of water flow is the most commonly measured metric for both laboratory and field applications. Its employment in scientific and engineering studies often leads to an oversimplification of the underlying flow physics. In reality, complex flows are ubiquitous, and commonly arise from fluid-body interactions with man-made structures, such as bridges as well as from natural flows along rocky river beds. Studying flows outside of laboratory conditions requires more detailed information in addition to time-averaged flow properties. The choice of in situ measuring device capable of delivering turbulence metrics is determined based on site accessibility, the required measuring period, and overall flow complexity. Current devices are suitable for measuring turbulence under controlled laboratory conditions, and thus there remains a technology gap for turbulence measurement in the field. In this paper, we show how a bioinspired fish-shaped probe outfitted with an artificial lateral line can be utilized to measure turbulence metrics under challenging conditions. The device and proposed signal processing methods are experimentally validated in a scale vertical slot fishway, which represents an extreme turbulent environment, such as those commonly encountered in the field. Optimal performance is achieved after 10 s of sampling using a standard deviation feature.

RAPTOR-UAV: Real-time particle tracking in rivers using an unmanned aerial vehicle

River system measurement and mapping using UAVs is both lean and agile, with the added advantage of increased safety for the surveying crew. A common parameter of fluvial geomorphological studies is the flow velocity, which is a major driver of sediment behavior. Advances in fluid mechanics now include metrics describing the presence and interaction of coherent structures within a flow field and along its boundaries. These metrics have proven to be useful in studying the complex turbulent flows but require time-resolved flow field data, which is normally unavailable in geomorphological studies. Contactless UAV-based velocity measurement provides a new source of velocity field data for measurements of extreme hydrological events at a safe distance, and could allow for measurements of inaccessible areas. Recent works have successfully applied large-scale particle image velocimetry (LSPIV) using UAVs in rivers, focusing predominantly on surficial flow estimation by tracking intensity differences between georeferenced images. The objective of this work is to introduce a methodology for UAV based real-time particle tracking in rivers (RAPTOR) in a case study along a short test reach of the Brigach River in the German Black Forest. This methodology allows for large scale particle tracking velocimetry (LSPTV) using a combination of floating, infrared light-emitting particles and a programmable embedded color vision sensor in order to simultaneously detect and track the positions of objects. The main advantage of this approach is its ability to rapidly collect and process the position data, which can be done in real-time. The disadvantages are that the method requires the use of specialized light-emitting particles, which in some cases cannot be retrieved from the investigation area, and that the method returns velocity data in unscaled units of px/s. This work introduces the RAPTOR system with its hardware, data processing workflow, and provides an example of unscaled velocity field estimation using the proposed method. First experiences with the method show that the tracking rate of 50 Hz allows for position estimation with sub-pixel accuracy, even considering UAV self-motion. A comparison of the unscaled tracks after Savitzky-Golay filtering shows that although the time-averaged velocities remain virtually the same, the filter reduces the standard deviation by more than 40% and the maxima by 20%.