Tissue Engineering- A technology of tomorrow

Is there a limit to our dreams?... NO!!!.. We are human beings and we strive on inventions. 20 years back, noone had thought that mobile phones would become a day-to-day accesory. Today, almost everyone has it.

Can you imagine building an artificial heart from the cells of a living human?... Would you prefer to have a brand new bone instead of a metal rod, in case you meet with an accident?... Can you think of getting organ replacements that would help you live longer and healthier?...

Yes guys yes!! Here comes Tissue Engineering. And here come Bio-Engineers. We are here to change the world, we are here to let people live longer and happier. We are going to give you something, which, 10 years back, would have been considered as a miracle. Its a reality today... This miracle is called Tissue Engineering.

Sounds interesting?!?.. Read on.

What is Tissue Engineering?... Its a science ( or an art) of generating natural tissues and creating new tissues using biological cells, biomaterials, and some novel methods. Let me explain this to you in simple terms:

Tissue engineering is an innovative approach for repairing and replacing of damaged or diseased body parts. Cells, derived from same human source, or from other animal, which are often seeded into or shaped around a biomaterial matrix (called as a scaffold), are used to replace the tissue. As our understanding grows of the characteristics of various types of cells, and their interactions with materials, and how culture conditions can influence their development, we can see the potential for regeneration of damaged or diseased body parts with more authority.

Tissue engineering will have a significant impact in several areas of science and medicine in the future. Tissue engineering products (e.g., skin, cartilage) based on cell transplantation approaches are already available for clinical use. It is based upon a relatively simple concept: Start with some building material (e.g., extracellular matrix or biodegradable polymer... also known as a scaffold), shape it as needed, seed it with living cells and bathe it with growth factors (which helps the body to recognize the implant). When the cells multiply, they fill up the scaffold and grow into three-dimensional tissue, and once implanted in the body, the cells recreate their intended tissue functions. Blood vessels attach themselves to the new tissue, the scaffold dissolves, and the newly grown tissue eventually blends in with its surroundings. Regeneration of skin, bone, and blood vessels will likely be routine in the near (5-10 years) future.

The ultimate goal of we Tissue Engineers is to develop complete internal organs (e.g., heart, liver, brain). Researchers have taken the first steps towards that goal and have successfully created bio-artificial systems to treat patients with diabetic ulcers and soon will have the ability to repair and replace damaged cartilage.

However, we are still at the very beginning of what seems to be a field with potentially limitless growth. Success will largely depend on the ability of scientists to figure out complex cellular interactions, then intervening with the right scaffold material and exact growth factors and cells. But Tissue Engineering promises to be one of the most exciting and promising fields to look for.

http://wtec.org/loyola/te/final/te_final.pdf

RF-Based surveillance Vehicle :

Robot Construction:

This robot has two computers communicating with each other via RF Frequency modulated signals. One was a 89C51 micro controller on board and the other was a central control which was a P-IV 1GHz PC.

At the PC end: It consists of a Visual Basic based program and serial interface. It has a built in map of the effective controllable region restricted by the RF signal strength achievable on board to have fault free communication between the PC and the MuC. This map contains the static obstacles contained in the room like a wall in the region. There is a Yagi-Uda antenna to transmit modulated data to the micro-controller on board. Also there is a audio/video receiver connected to a Television which can display the color images as seen by the CCD camera on- board.

The Robot consists of the following sub-systems: It has a RF transceiver-filter-demodulator-amplifier module, a Micro controller, a CCD camera and a TV RF modulator and transmitter module, a gripper attached to a vertical extension (as in a SCARA robot) and a basic obstacle detection system of IR led and a TSop. It also had a Battery level indicator connected to the micro controller's interrupt line. There are Stepper motors to move the robot.


Working: The main aim of our project was to study different Path planning algorithms on a mobile system. The one we implemented was a Visibility Graph technique to reach a goal. Following are the typical steps to be followed to execute a task of reaching a goal position and performing a gripper task:


We developed a protocol for communication between the PC and the vehicular robot.
Commands to the Robot: Start/Stop Code, Vehicle Move, Camera ON/ OFF, Send Sensory Data, Send Battery Level Data (alive/ dead), for forward/reverse/right/left motions, Gripper OPEN/CLOSE, Gripper UP/ DOWN.


Data from the Robot: It basically executes the commands written by the PC to achieve a certain task. But in case of an obstacle it detects unknown to the PC map(stray moving/temporary objects ), or if its battery level goes LOW, it interrupts the PC. It also sends the current X and Y co-ordinates of the robot which it calculates internally by measuring the steps each stepper motor moves.

Future Enhancements possible: Here we implemented the Visibility graph because of its simplicity. The path planning can be done using Voronoi diagrams, Potential Field method, etc.
The protocols we developed for intercommunication between PC and Robot can be easily extended to multiple robots. For example, one robot could provide instructions to the rest. This Robot would take the place of the PC in our implementation. This robot will have greater processing power than the other robots.


Also the processing can be split amongst robots. As in some have better image processing, some better on-board obstacle avoidance and some others with other sensory devices attached. This will mean specialized robots performing a group activity.

The Micro-Mouse

The Micro-Mouse :
We had to build a automated mobile robot which could travel to the center of a random Maze.

The Arena: It consisted of 16x16 square cells with vertical walls (as shown by the white walls). The walls had reflective coating on them to ensure sensing.

Robot Construction:
We used an 89C51 micro controller and 4 KB external RAM. It had an array of 8 IR leds and TSOPS to detect the WALLS. Two led-sensor pairs for West/South/East/North sensing (We did not front/side/back information to take care of orientation). There was a 555 astable multivibrator and a SL100 power transistor stage to drive all the LEDs at desired current and frequency(33-38 kHz). The Ext RAM and sensors were connected to the Same PORT by using a bi-dir buffer IC. There was a Regulated power supply on board for the digital circuits. The 2 uni-polar Stepper motors are controlled by a Driver Circuit(LM 293D).

Obstacle( Wall ) Detection and Error Correction: The 8 leds are driven by a astable multivibrator at 33-38kHz. This is the active operational frequency band of the TSop. When ever any of the sensors get triggered, an interrupt is generated and the micro-controller handles the interrupts as follows:
The front and back sensors are used to correct the forward-backward errors caused due to slipping of the stepper motors and due to fractional errors introduced because of the incapability of the MuC to handle fractions. We adjusted the wheel radius and the turning radius to avoid fractional distance covered per step. An interrupt is serviced only if the steps needed to complete the ongoing task (rotate/move one cell ahead) is not reached.
The left-right sensors are used to correct skew errors. If diagonally opposite sensors detect walls then the robot is rotated in such a way that the robot is aligned parallel to the side walls by continuously reading the sensors and adjusting the orientation.
Path Planning Algorithm: The robot used differential wheel movement to spin about its center. Thus within the arena, its configuration space was defined conveniently able to occupy all ROWS,COLS and tetha:
Configuration Space = {0<= ROWS <= 16 ; 0 <= COLS <= 16 ; 0 <= tetha <= 360 }.
We came up with an algorithm which resembled closely “The Flood-Fill” algorithm. This is a variant of the Dijkstra's shortest path algorithm:
The robot continuously builds the map as it encounters new obstacles. Given the constraints of the arena, from each cell the robot has two possible shortest paths to reach the center. We analyze the following situation to explain the Flood-Fill algorithm.


Summary : The fast flood fill method ensures that the robot will reach the goal in the minimum iterations. Back-tracking is taken care of by the way we number the cells while seeing a wall. But once a loop or a dead-end is visited the map and the algorithm ensures that we don’t remain in the loop or revisit the dead-end.
The Flood fill algorithm used by us has its equivalent in robot/vehicle path planning too. It is in fact a restricted version of Potential field method of reaching to a goal and to avoid obstacles on the way. Putting FF behind walls is raising its field level and numbering decreasingly from current position towards the center ensures that if we follow a cell with a lower number then we will finally avoid dead ends and reach the Minima(Goal).