Underwater Robotics - Science topic

Thanks. Let me go throught it.

Dear Akshat Shirish Zalte

You can go to Elsevier or Science-direct Journals and follow the steps after sign up to submit to your technical paper.

Kind Regards

Qamar Ul Islam

Dear Ammar Amory

You can use fuzzy logic based online tuning of PID controller

Regards

Thor Fossen's book is quite comprehensive on modeling dynamics of marine systems (at least for automatic control purposes):

Handbook of Marine Craft Hydrodynamics and Motion Control

Hi,

I would suggest also to have a look at the following References:

1) (A. Bemborad et al, 2004) Model Predictive Control: New Tools for Evaluation and Design

where it is described the MPC Tbx. in Matlab and a MIMO example.

2) L. Wang, 2009. Model Predictive Control System Design and Implementation Using MATLAB (Springer)

- there are step by step implementations of SISO/MIMO continuous and discrete time MPC (using Laguerre basis functions) and a design example on an industrial MIMO (2x2) process (extruder)

Good luck!

Also refer this chapter

Filippo's first comment is quite interesting. The question is about a velocity of 10 m/s. And if the body is immersed in water, there is a difference between the situation in deep water or close to the surface. For shallow open water, there is an analogy to compressible flow. So, close to the water surface, the dolphin nose may actually provide less drag than the blunt body. But hey, there should be specialists round here, right?

Conventionally, there are three methods to measure hydrodynamic coefficients in small AUV:

1. Through experimental method (using towing tank test, turning circle test or PMM Test).

2. Through CFD analysis.

3. Through empirical estimation (some basic formulas of drag lift and moment coefficients based on standard size and shapes of AUV i.e. cylinder, sphere).

You can choose any one of them based on requirement, application, time and money.

There are several publications from MIT where people have suggested semi empirical methods towards determining hydrodynamic coefficients.

You can also read a paper from Dr. Ralf Bachmayer where they have determined hydrodynamic coefficient from the in situ operational data of small AUV.

Hope this small explanation helps !!

@ Vinh Quang Trinh

Hello,

Thank you very much for this answer. I have got what you mean in the answer, but it is not available when applied to underwater vehicle because of the serious implementation. 

Camera image is the data I get collect from vehicle. when fuse image with imu and depth sensor datas,  the method that  can estimate or percept environment is what I am looking for .

Regards.

Let's say for example that you have a simple line follower robot with a light sensor in the front and a motor on each side. The robot must follow a line on the floor from point A to point B. Instead of using a single black line on white floor let's use a gradient line, i.e. a line composed of several gray-scale lines (from white to black).

This system has a single analog input (0 - black to 1 - white) and two outputs (motor left, motor right). Let's use a PWM output that goes from 0 (no speed) to 1 (full motor speed). A simple controller could have 4 parameters:

Out_right = k1*(input - i0_1)

Out_left = k2*(input - i0_2)

where k1, k2 are linear gains and i0_1, i0_2 are desired input values. Then you can encode a simple genome g = [k1, i0_1, k2, i0_2]. You can make a more complex controller if you look at the difference between the current reading and the one before (like PD controller), then you get 6 genes: g=[k1, i0_1, k2, i0_2, k3, k4].

The encoding in this case is quite easy. Each gene is a floating point number with a given range, e.g. -100 to 100 or 0 to 1.

The choice of fitness function depends on what you want to achieve with the controller. You could integrate the distance of the robot to the line over a certain period of time (or until it reaches point B). You could use the time it took to reach B as another fitness, or how much control effort it used.

When you have several fitness functions you can use a weighted sum of all the functions to sort your population or you can use a pareto front approach, like I used in my latest publication. This method gives you a range of optimized solutions rather than a single one, .e.g some will be very fast, some very efficient.

Good luck!

Best,

Jonathan

By defining the constraints on various parameters you could find the violations/faults.

~Sri

@Naresh Kumar....thanks for your response....can we configure all these channel characteristics in qualnet?

Hi Victor,

There are some solutions with directive lasers. High communication bandwidth van be achieved, but the positionnement precision , and stability of the station keeping requirements are important.

I think first of all, you should read the paper carefully. then you can start implementing the proposed method of the paper, if you need any help you can contact to the authors of paper.

So, if you want to learn something, you should understand it first.

You can use following simulators based on your specifications for conducting experiment.

NS-2, QualNet and Aqua-Sim but I can go with qua-Sim that is easy to use with enough features supported by NS2.

With the relatively inexpensive Broglio Drag Balance, you can directly measure the force acting on your unmanned underwater vehicle. This balance was developed by Broglio to measure the drag of operating satellites.

Hi Tyuen, I guess that by your question you mean that what are the applications of Underwater imaging. Underwater imaging has a wide variety of applications. Like you said to study about fishes, coral reefs, to study about seafloor hydrothermal vents, to capture 3D bathymetry of seafloor terrain etc. For example in one of my present project we are using 3D vision based mapping technique combined with an acoustic sensor to measure the volumetric distribution of manganese crusts. You can check details about this project here http://ocean.iis.u-tokyo.ac.jp/research.html .