The NXT step

Greetings

For a long time, I wanted to use my programming abilities in robotics. I wanted to create a robot and program it myself to respond to stimuli, unlike the pre-programmed ones that were available in the market. This meant that I had to buy motors, PC boards, micro-controllers, switches and sensors independently, assemble them and then program them.  While I searched the net to buy these parts (A lot of companies did not ship to the Middle East, where I used to live), I started getting disheartened because of the nonavailability of the most basic micro-controllers and motors.
                Fortunately for me, Lego and MIT released the Lego Mindstorms Kit. While the NXT-G programming language was sufficient, Visual Programming lacked a certain something that had drawn me to textual programming languages. When the good guys at LeJOS released LeJOS v0.85, I immediately flashed my NXT to that version(The latest version at the time of writing is 0.90, refer to this page to see how to flash your NXT and get the LeJOS environment running on your computer) and began coding in sweet, sweet Java. I had always been fascinated by remote controlled cars, so the first thing I set out to do was to create a program to control my NXT vehicle via input from the keyboard. To do this, I created a small GUI based Java program(send.java) which acted as the control center. The program had a command log, connect, disconnect, shutdown and options(The options button has no functionality currently) buttons, and a text area to receive the input form the keyboard. The program sent commands from the keyboard to the NXT(running rec.java) via Bluetooth. The NXT acts as a slave(The main thread is pretty much stopped from executing, until a Bluetooth connection opens) and waits for input from the computer and acts accordingly. My program works in a simple manner. When I press the top arrow key, the key-code of that key specified by Java is sent to the NXT and the NXT knows to move forward, and so on. The idea is simple in concept, but it does have a few problems. One of the problems is that in this model, the sending of two commands simultaneously is a bit of a hassle. Right now, the robot can turn or move, but not at the same time. One possible solution would be to multiply the key-codes of the two arrows and  return the product as input for the NXT because for the key-codes 37, 38, 39, 40, the product of any two numbers is different from the product of any two other numbers in the set(note that the same cannot be said for addition.) In any case, the program does the work of successfully sending commands to the NXT, albeit not with a lot of options. This is just a test program, and I am working on another one with greater functionality(one that has a working options button!)
                 In any case I will put the files that run on the NXT and on the computer up for download. Please note that to run these files, you should have LeJOS installed on both the NXT and the Computer. The files to be run on the NXT will be called rec.java and the file to run on the computer will be called send.java.Here is what you have to do. Open up command prompt and and navigate to the folder where you have placed the two files. Then type in the following commands:

nxjc rec.java              (compile the rec.java file)
nxj rec                    (upload the rec.class file to the NXT)
Now go the NXT and execute the rec.nxj file. Go back to command prompt.
nxjpcc send.java           (compile send.java)
nxjpc send                 (run send.class, AFTER starting rec.nxj on the NXT)

I have once again annotated the code, explaining how and why it works. Please edit the code, add your own functionality and experiment with it. I am once again releasing the code under the MIT license.  You can use any NXT car creation you want to test out the program, but the model has to turn via a difference in the speeds of the different sets of wheels, like in a tank. I used the 30 minute model from Lego Mindstorms for testing purposes, here is a link to the instructions to build a similar model. You can replace the tracks with wheels if you want. Also, here is a video of the program and the NXT in action.

Here are the links for the two.java files. I have not created any JARs as they are really not needed.

rec.java (On the NXT)
send.java (On the computer)

This is not the end.......

What more can you ASCII for?

Greetings

I am not the artistic type, but that does not mean that I do not appreciate art. While I do like art created by others, I sometimes wish that I too was gifted with artistic abilities. Once again, using the awesome powers of Java, I was able to realize this dream. Using simple Java code, I created an image to ASCII converter program which takes an image and outputs a text file with ASCII characters, which looks like the input image when viewed all at once. In this post I will explain the basic principle behind computer generated ASCII art, and how to implement it using Java. I will release my own code for the program that I built, the program itself and a short video of the program in action. From now on, I will release all my code under the Open Source Initiative (OSI) MIT License (MIT), because the license is clean, short and easy to understand. Before I explain the principle behind ASCII art, here are some of the ASCII art created by the program: 

That's me!!

The Simpsons are ASCIIfied!

p-51 Mustang- A classic

The principle behind ASCII art is easy to understand. An image can be thought of as an 2 dimension array with rows and columns that correspond to the width and height of the image (In reality, it is more complex than that but this is a good enough understanding for the time being). Each cell in this array holds a pixel. When all these pixels are viewed together at once, you get an image. So a 400x400 image has 400 rows and 400 columns, and has 160000 pixels. Now to convert an image to text, the program has to iterate through all the pixels, get its RGB value, convert it to its gray scale value, and append a suitable ASCII character. Java has a class called the BufferedImage class, which has the methods necessary to obtain the RGB values of a pixel. Now once the RGB values(ranging from 0 to 255) of the pixel is obtained, there is a simple formula to convert it to a gray scale value. Simply take ~30% of the Red Value,  ~59% of the Green value and ~11% of the blue value and add them up together to a value ranging from 0 to 255, 0 being the darkest and 255 being the brightest. Don't worry, the BufferedImage class has the necessary methods to obtain these values,which you can see in my annotated code posted below.This value is your gray scale value. Generally gray scale value range from 0 to 1 with decimals in between, but there is no reason for them to be between 0 and 255. You could divide it by 255 to range it from 0 to 1, but why the extra hassle? After obtaining the gray scale values, the creative part begins. As you know, some ASCII characters appear darker than the others. For example, # appears darker than 0.So what the program does is obtain the gray scale value of each pixel, and according to the value, append an ASCII character to the text file. For example, if the gray scale value is in between 180 and 200(very bright), it appends a ".", and if it is 50 and 70(very dark), it appends  a "#". Currently there are nine different ASCII characters that the program chooses from to append. However, I urge you to edit the code and experiment by adding more characters, changing the existing characters, etc. For a detailed explanation, read the comments in my code which explain the function and workings of each method. The results are stored in a file called result.txt, and when viewing the results in a text editor, choose a small bold mono-spaced font, with word wrapping DISABLED. I recommend choosing images not bigger than 600x600 as the task will become more and more resource intensive with bigger images. While the current program does have an area where the results are appended, for spectacular results, open up the result.txt file and choose the best font and size to view the art. I find that Prestige Std Elite and OCR A work really well, almost giving the illusion of colors. This program is only a test, and soon I will be releasing code to a program with better GUI, more options and ultimately more robust. But until then, here is a small video below which runs you through the code of the program and explains how the program works. 

And finally here are the links to the code of the program and the actual program and the Netbeans Project. Please go through the code, experiment with it and hope you learn something out of this.

Link to code (only .java file)

Link to the Netbeans Project

Link to the program (only .jar file)

This is not the end

Aravind Rao

                  

Prim's Algorithm

Greetings

Sometime back, I wanted to dive into a programming topic called graph theory. Graph theory is an extremely interesting topic in the sense one needs to use their brains to solve graph problems. Also many problems, such as the traveling salesman problem have only been partially solved at yet, making it a NP hard problem. I decided to start my dive with a lesson in Prim's Algorithm. However after countless hours of scourging the web, I could not find the code, nor an explanation simple enough for me to understand the algorithm. Thanks an awesome video I found on YouTube(I don't have the link, but I find it, I will post it here) on the Prim's Algorithm I was able to write my own interpretation of the Algorithm. This code makes use of arrays and simple vectors and is extremely easy to understand. I though of posting this code because I wanted anybody else in my position to be able to understand Prim's algorithm without having to resort to complex, unnecessary code. So what is the Prim' algorithm? Ever heard of problems such as the length of road required to connect all cities? or the cabling needed to form a network of computers, but some computers acting as proxies for the others? Well for all these problems, the MST or the minimum spanning tree has to be found. Imagine a group of cities (A to E) to be the nodes in a graph. Now imagine the distance between them to be the edges in a graph. Here is a pic.

An Example Graph

So the DIRECT distance from A to B is 10, A to E is 34, etc. However what is the least length of road to be constructed so that all the cities are connected? It is certainly not 106, the sum of all the distances. It happens to be 22 or the MST of the graph of cities. Try it out. cross out the distances of 33, 34 and 17 and you should still be able to travel from any city to any other city! Solving such problems require MST which can be found using the Prim's algorithm.The code I release for Prim's algorithm will have a detailed explanation on how it works. Here is a gist: start from any node, mark it visited. Choose the shortest path from all paths available and the add the path length to your MST counter. Get the node at the other end of the chosen path and mark that visited as well. Now considering the paths from all visited nodes, choose the shortest path and mark the node on the other end as visited. Continue to do this until all nodes are visited and once done you have the MST! The Prim's algorithm is great for finding the MST, although a little bit slower than other algorithms. However it is a simple algorithm to learn and is fun to work with. Links for the code and explanation down below. Once again you are free to modify and distribute the code with proper credit given.

Link to .exe file.
Link to code.

This is not the end...

Aravind Rao

Java to the rescue!

Greetings

Some time back, I decided to run for the position of secretary in the student council of my school. Being a secretary appealed to me; I did not want a position that was constantly in the limelight and I enjoyed tasks such as data handling and processing (student data and volunteer info). I was subsequently elected and while reviewing the duties of  a secretary, I realized that there was no real system in place to store, view and edit member data. I found out that previous secretaries had left this responsibility to the members themselves; that is the reporting of the hours volunteered and so on. It did not seem right to me to allow volunteers to self report theirs hours. However it was seemingly the only option considering there was no concrete system in place. One of my fellow student council members had the "bright" idea to use an excel document; At 300+ members and over 100 activities per year, the excel cells to be edited would exceed 30000. There had to be another method. Finally, it was Java that came to my rescue! I decided to create a Java GUI Swing App combined with a self written text file parser. Every time a new member is added, the app creates a new text file with name, grade, etc as well as a volunteer hours summary, edited to look like a table. Adding hours to members files involves using the text file parser. which searches for special indexes and edits the file accordingly. Since the data is stored as text files, it can be printed out and handed back to members to increase transparency. I set out to code the app and in about a week finished it. It was a mad rush of coding ~ 440 lines of Java. All the codes are in a single file, though looking back in retrospect, I should have used interfaces and abstract classes for more readable code. However, it was the best I could do in a week! In any case, it helped me tremendously in processing members and their hours. I also built upon this code to build a simple payroll program for a local dentist's office. Although I cannot release that code until they allow me, here is a screen shot below:

My more complex payroll app screenshot.

As you can see, it is a pretty complex app with over 1250 lines of code. I shall be however posting links for the source code and entire project of my Student Council Secretary App as well as the .jar file. I have annotated key parts of code, but if you have any questions, please post a comment question on this post. When using the app, he member files are created in the same directory as that of the app. Like always, you can use, modify and redistribute it without any license. If you do redistribute it, It would be nice if you could add my name somewhere in the file, but if you cannot, it is not really a problem. Here are the links:

Link to download zipped Netbeans project (source code in the Hours-src-hours folder.)

Link to download .jar executable file. (Not tested on Mac, but should work. Works in Ubuntu and Windows)

This is not the end...

Aravind Rao

Intelligent Code

Greetings

Every problem in Computer Science can be solved by accounting for every possible permutation that the program might encounter. Naturally this is not an efficient practice, especially when  the number of possibilities can grow exponentially, reaching billions in no time. To effectively solve such problems, we need to implement  a kind of logic, based on our own thinking while problem solving. This inherent 'common sense' of humans can help create powerful algorithms to solve computer problems, without the aid of brute force. An example of such a problem is a computer game (Source .cpp, and .exe), where a computer tries to guess a users' choice within a given range. If the users' choice is >= the computers' guess, the user inputs 0. If the user's choice is < than the computer;s guess, the user inputs 1. Naturally, the computer can iterate through all numbers in the range from lowest to highest and check whether the computers' guess matches the users' choice and arrive upon the answer when the user inputs one(the users' choice will be the current computers' guess - 1). However what if the range extended from 1 to 2^10? Does it make sense to loop through all those numbers, check for user input and output the answer? This method is not time or user friendly. However, if we implement an algorithm that imitates the way we think when solving such a problem, we can arrive upon an extremely efficient solution for this problem. Consider the range 0 to 16. The user's choice is 11. Now lets add 1 to 0 and 1 to 16, to make the range 1-17. This is done because we will than have 2 nice halves of the range: 1-8 and 9-17. This idea of dividing the range into half will be central to out algorithm. You will get why I do this later. Now the computer has 1\16 or 6.25 % chance of guessing the right user's choice. If it iterated through all the values of the range and checked it against the user input, the probability of the program guessing the right choice will be increased to 6.67% -> 7.14 %...etc.(Not really, but for the time being, let us consider the case to be true). What should the program do to arrive upon the answer faster and in fewer tries? It should try to increase the probability of getting the right answer in each successful turn by a greater rate. For example in the range 1-17, the computer programs' first guess has to be (1+17)/2 = 9 or the average of the range extremes. Why? Because if the user inputs 1, the users' guess is less than 9, so it is in the range 1-8. Alternatively, if the user inputs 0, the users' guess will be greater than or equal to 9, and thus in the range 9-16. What have we achieved here? We have increased them probability of the computer guessing the right answer in the next turn to a whooping (1/8)% = 12.5%, which is the double the probability of guessing the right answer of the programs' first turn. Compare this with the 6.67% probability while iterating through all values!Now since the user's choice is 11, he will input 0, and now the computer program will carry out the same operation, although this time on a different range, that is 9-16. After this turn, the probability of guessing the answer right will increase to 25%, then to 50% and finally to 100% When it reaches 1000%, the program will have the answer! his method only works on ranges whose higher extreme can be expressed as:
Log2(Higher Extreme) = some Natural Number.
Therefore 16 works(log2(16) = 4), so does 8. 32 and 4096. The number of guesses the program will make is log2(higher Extreme). In the case of the higher Extreme being 16, the program will make 4 guesses, in the case of 32, it will make 5 guesses and so on.
I have provided the links to the source code and .exe file of this 'game'. Feel free to edit it, distribute it and use it, although with proper credit!

Link to .cpp source file.
Link to .exe playable game file.


This is not the end

Aravind Rao

Onto the NXT project

Greetings

Until the NXT time it is! If you picked up from the last post, you would have guessed that the NeXT post is going to something about Mindstorms NXT. And it is. In this post I am briefly going to talk about a technology which has united my two greatest passions: Programming and Robotics! Mindstorms, by Lego, is a Robotics Kit which one use to build and program fully or partially autonomous programmable robots (Robots including, but  not limited to bipedal humanoids). Lego Mindstorms was released following a collaboration between Lego and MIT's Media Lab. The Lego Mindstorms started out as Mindstorms v1.0 and the latest version now is the Mindstorms NXT v2.0, a huge leap from its predecessors in terms of processing power by the Mindstorms Brick and availability of different kinds of sensors. Lego Mindstorms NXT is programmable through the NXT-G programming software(simple programs can be built on the Brick itself), which supports Visual Programming. I, however owning to my hacker nature, decided to go one step forward and installed the LeJOS firmware on my NXT. LeJOS allows the NXT to execute special byte-code from LeJOS specific java programs! This means that you can code all you NXT programs in leJOS Java(similar to Java ME), convert it to special byte-code with the help of LeJOS NXJ on your computer(similar to the java  JDK) and transfer the byte-code to the NXT and execute it using the LeJOS Virtual Machine. As one can see, the ability to use such a powerful language greatly increases the possibilities of the Mindstorms NXT. Also LeJOS can be used to communicate(2 way data streams) with other Java programs, whether they reside in a computer, a smart phone or even another NXT! Using you cellphone to control your NXT or developing a Client-Server relationship between the NXT and the computer can be achieved through LeJOS. The methods of communication are BlueTooth and the USB specifications. LeJOS is the not the only custom firmware for the NXT; ROBOTC and BrickOS can be used to run c/c++ programs on the NXT. For now however,  I will be sticking to LeJOS. I will soon be posting a page on how exactly to get LeJOS on your NXT, as well as many clever, innovate programs for LeJOS NXT.  Until then, take a look at a list of useful sites that I have posted down below!

Never The End.

******************
**Some Useful Sites**
******************

The LeJOS API
The LeJOS PC API
Great NXT tutorials
A NXT LeJOS forum

Day of the Knight

Recursion n. See recursion
Search v. Definition hidden at the end

Greetings
I am came across an interesting problem sometime back on the net. The problem in a nutshell was to calculate the least of amount of steps that it would take a knight to get from square(a,b) to square(x,y). The real task at hand was to map out the whole chessboard, with values denoting the depth or breadth level from the starting square. This question could be solved two ways, using either the Depth First Search Method, or the Breadth First Search Method. I am going to speak about them in this post.
DEPTH FIRST SEARCH:

The Depth First Search or DFS is a recursive searching method, where by, on goes down as long as they can until they hit a dead end. When they do, they go one up, and starting going down again, although this time in a different path. Consider it like this. Imagine a house full of rooms. Inside these rooms there are more rooms, inside which there are even more. Your task is to find how many rooms one has to go through to get to room 8. Diagram given below.

The room location map.

In a typical DFS search, the longest search order would be something like this:
Start->1->4(Dead End!)->1->5->9->5->1->Start->2->6->10->6->11->6->2->Start->3->7->12->7->3->8

In a typical DFS search, the shortest search order would be something like this:
Start->3->8
      ...............and many possible permutations in between.

As you can see, something that is just two levels away from the start takes a maximum of 23 node visits, where as the shortest one takes just 3 node visits. There is no way to ensure the DFS method to make the shortest node visits, as the DFS wont know the location of the node in absolute terms, only in relationship to other nodes. In part, the DFS has such a high, unacceptable worst case scenario result is because many of the nodes are re-visited many times over.(Start, 1, 5, etc). The difference between the best and worst cases is way too big for the search to be efficient.

BREADTH FIRST SEARCH

The search technique in BFS involves grouping nodes with the same absolute distance nodal distance from Start Point in the same breadth. Imagine that after the BFS technique identifies the nodes with nodal distance 1 from the start point. All these nodes are in Breadth Level 1. These nodes will then be pushed into a stack, where EACH on of these nodes will become the Start Point. Now the nodes with a nodal distance of 1 from these Start points will be grouped in Breadth Level 1 more than than the breadth level of their starting points, something like (Node Level = Start Point Level + 1). In this manner all the nodes will be mapped and assigned a value denoting their absolute nodal distance from the first Start Point. Here is a diagram.

The room Location Map, now with Breadth levels.

In a typical BFS search the search order would be something like this:
Start->1,2,3 stack.push(1,2,3)-1st Level
loop through stack as long as there are nodes.
1->4,5 stack.pop(1) stack.push(4,5)-2nd Level
2->6 stack.pop(2) stack.push(6)-2nd Level
3->7,8 stack.pop(3) stack.push(7,8)-2nd Level //Stop here, 8 is found
4->Dead End! stack.pop(4)-3rd Level
5->9 stack.pop(5) stack.push(9)-3rd Level
6->10,11 stack.pop(6) stack.push(10,11)-3rd Level
7->12 stack.pop(7) stack.push(12)-3rd Level
8->Dead End! stack.pop(8) -3rd Level
9->Dead End! stack.pop(9) -4th Level
10->Dead End! stack.pop(10) -4th Level
11->Dead End! stack.pop(11) -4th Level
12->Dead End! stack.pop(12) -4th Level

Another, faster case
Start->3,2,1 stack.push(3,2,1)-1st Level
loop through stack.
3->7,8 stack.pop(3) stack.push(7,8)-2nd Level //Stop here, 8 is found

As you can see, each node is not visited more than once, only its location is pushed into the stack. After its immediate nodes are visited, it should be popped out or removed, otherwise you will have an infinite loop.
The difference between the best and worst case scenarios is not much, and is generally more efficient than DFS, as it takes less time, resources and searched intuitively.

The C++ program that I built also uses the same technique of BFS to solve the problem. Have a look at it, annotations are included and post your feedback or questions regarding the program.
Link for the .cpp File
Link for the .exe File

 Until the NXT post

Aravind Rao, chief Hacker(claimed)