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  1. 1. International Journal of Electronics and JOURNALEngineering & Technology (IJECET), ISSN 0976 – INTERNATIONAL Communication OF ELECTRONICS AND 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 6, November - December (2013), © IAEME COMMUNICATION ENGINEERING & TECHNOLOGY (IJECET) ISSN 0976 – 6464(Print) ISSN 0976 – 6472(Online) Volume 4, Issue 6, November - December, 2013, pp. 134-139 © IAEME: www.iaeme.com/ijecet.asp Journal Impact Factor (2013): 5.8896 (Calculated by GISI) www.jifactor.com IJECET ©IAEME HOME BUTLER- A VOICE CONTROLLED ROBOT TO ASSIST THE HANDICAP GauravJha1, Addala Sai SubhaCharan2, Chalasani Rama Krishna Prasad3, AkashMantry4 1, 2, 3 4 ECE, SRM University, India ICE, SRM University, India ABSTRACT Our system works under voice control. The robot takes in the voice input from the user and decodes it using LabView. The robot first tells the user whether it can locate the object or not. If it can, it locates the object and then using another database it gets the image of the object. This is the reference image and is processed using MATLAB. The histogram of the image is processed. After finding the specified location of the object and image processing, it uses SLAM (Simultaneous Localization and Mapping) and goes to the searched location of the object. Using camera vision and image processing by MATLAB, it tries to find a match with reference image. After getting the perfect match, it then grips the object by the help of limit switches and photoelectric sensors. Then it brings the object back to the user by tracing the same path it took to locate it. Keywords: Voice Control and Decoding, Image Processing, SLAM. OBJECTIVES The following are the objectives of our study, which include: • To get the voice command by the user and decode it effectively. • To search for the object in our own created database and then locate it and get the information (histogram) related to it. • Using Simultaneous Localistaion and Mapping and Light Detection and Ranging sensors, get to the location of the VR • Using video camera vision, image processing and comparison by Matlab, find the closest match of the object. • Get the distance of the object by using Area Threshold method. • Move to the object and then grab it using limit switch and photoelectric sensors. • Bring the object back to the user. 134
  2. 2. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 6, November - December (2013), © IAEME The user gives the voice input to the robot. The robot uses microphone or Easy VR module to get the voice input. LabView is used to decode the voice to text and also get the location of the decode object from our own created database. One method of voice decoding is using the module, which directly converts voice to text, and the other is using LabView, matching the input with a preloaded voice signal. Both the input and the preloaded signal are converted to their numerical equivalent and gnal. then matched. The robot now has the name of the object. Using the database, it finds the location of the object and also the particular object’s histogram data in different positions. Using SLAM technique and LIDAR sensors it finds its path to its destination. The position of the object is obtained using Localization and then accordingly Mapping builds its map to the destination. LIDAR sensors consist of a LASER transmitter and a receiver. These sensors help the robot to detect is surroundings ansmitter by emitting laser beam through the transmitter and then checking the time it takes for the receiver to receive the transmitted light, hence, giving it the idea of its surrounding environment and hence, surrounding resulting in mapping. Once it reaches its destination, it starts taking in the images of the objects and processing them. It then finds the closest match by comparing the reference image data and the data of the image it is viewing. Next step is to find the distance of the object from the robot’s current ng. position. It uses Area Threshold method to do it. This method gives us the distance of the object. The robot then moves to the object and using its grabber grabs it. The grabber consists of limit switch and consists photoelectric sensors to assist in grabbing. After grabbing, it brings the object back to the user by tracing the same path it took to reach its destination This path or map that the robot traced was destination. stored in its memory, so that when retracing, it can follow the same path backwards. at STRUCTURE The bot is built on a hard box base with two tyres controlled by maxon motors, the speciality of these motors is that it has a built in shaft encoder. The shaft encoder gives it a sense of distance covered and to be covered. These motors are high torque motors so that they can easily mobilize the bot above. It has a third small tyre at the back to prevent it from toppling. The lower box like base structure houses the LIDAR structure. It consisits of four pairs of transmitter-receiver LIDAR c receiverof sensors on all the four sides of the box base. Above the box lies most of the interfacing unit like the camera, microphone and speakers.The design is simple, it houses a shelf like structure erected on three rods from the base. Out of the three rods one protrude out of the shelf like structur to a height above it.This rod has a camera on the top height along with a microphone.The camera is used for taking in images for processing and comparison while the microphone takes in the user voice commands. 135
  3. 3. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 6, November - December (2013), © IAEME The shelf like structure houses a pair of speakers for voice output of the robot. It also consists of flashlights which are swithed on automatically as soon as the light of the environment reduces below a threshold. Another important part of the self structure is the grabber. It has been designed anthropologically consisting of a shoulder elbow and wrist. The hand consists of three fingure like structures.The shoulder is mounted on a servo motor and can move both clockwise and anticlockwise. The shoulder consisits of another motor combined to cables.These cables being attached to the elbow. So, when the motor rotates, it coils the cables pulling the arm up, while if the motor rotates in an anticlockwise direction it releases the cable to put down the arm again.The wrist is mounted again on a servo motor for clockwise and anticlockwise rotation.The motion of the fingers is done by using motor cable combination.Three motors are used for the three fingers. When the motor winds, the cables are pulled and the fingers are moved up, while if the motor is rotated anticlockwise the cables are released and the fingers go back down. GRABBER After the system finds the image at the specefied location, the robotic handmoves towards the object. When the hand touches the object, the limit switch is triggered which sends the signal to the microcontroller and then the microcontroller sends the signal to the limit switch. In the robotic arm we have installed photoelectric sensors which are a type of proximity sensor. The photoelectric sensors are calibrated for a particular distance according to our requirement. When the robotic arm moves backward the limit switch opens and now the photoelectric sensors start sensing the object. The robotic arm moves backward in a linear direction and it stops at a particular distance where it is calibrated. The linear motion stops and the grabber grabs the object. DATABASE After the voice signal has been decoded, the decoded text goes into the database we created in LabVIEW. The location of the object which has been given as a voice input is found. For eg: If the user asks for the coffee mug, then the location of the coffee mug which is kitchen is found. We have created an array of five elements as of now which includes coffee mug, pen, charger, bottle and brush. And if the user prompts any of these objects then the location of that particular object will be found. If the user prompts an object which is not in the array, then automatically my LabVIEW program will give me the voice output as ‘Not found’. IMAGE PROCESSING In order to compare the two images we use the technique of histogram.Histogram is basically a process in which pixels of a particularimage are divided into classes.The main idea is to compare the small boxes of two images and create an array of values.These valuesare then compared with the array of values of the reference image.Now there are various possibilities for error to occur in this. For example suppose 75% of the values in an array are comparable in two images, and then it will give a result as two images are matched.but remaining 25% may be different.So final result may not be correct. To avoid thatwe divide the pixels of an image into classes which are further divided into sub classes and these sub classes are then compared.This gives us a more accurate result as it gives us more number of values in an array and all the values are compared and the closest result is given.If the screen resolution of an image is less (say 16*16 pixels) we will get limited values.So comparison may not be correct.In order to give better result in that case we go for grey scaling of an image.Also the size of image is reduced to much smaller dimensions.The advantage is that it gives a better and faster result. 136
  4. 4. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 6, November - December (2013), © IAEME LAB-VIEW Simulated Result Fig.01 MATLAB Program Fig.02 THRESHOLD In some cases when two images have comparable background and the differences are not visible then values given will be different.To solve this anomaly we go for threshold which is the minimum value that had to be exceeded in order to be counted.Here you can see the differences between a 200 pixels wide version of an image and a 100 pixels wide version of the same image. 137
  5. 5. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 6, November - December (2013), © IAEME As we can see that after giving a threshold,the values in an array are getting changed.The values below '4' are now treated as no difference.This technique is helpful in such cases.Based on the difference.This approximation,threshold value of '3' or '4' works in most of the cases.And depending on the task given you can approximate the value n value. Area Threshold This method uses a formula that relates the area of pixels and the distance between the object. This formula is derived before hand for various objects. Depending on the object, we use the respective formula to determine the distance of it from the robot once it has been detected. once 138
  6. 6. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 6, November - December (2013), © IAEME Raspberry Pi Raspberry Pi is basically a operating system. It includes a 700 MHz ARM microprocessor. We are going to develop software using this OS that contains the database for image location and image data, and the integration of LabView and Matlab. CONCLUSION The purpose of making a Home Butler Robot was to help the disabled person in his day to day activities. It can fetch things and bring it to the user. There are no such robots made especially for this application. Our robot is compact and the feasibility is high. However, further advancements can be made. 3D sensors can be used; better algorithms can be implemented for path finding. We have just mentioned one technique for the object detection but various techniques can be used. For SLAM we have used LIDAR but various other sensors can be used along with GPS to make it better. REFERENCES 1. Image comparison from the abstract submitted by CORNELL UNIVERSITY. 2. www.cmu.edu/herb-robot/‘HERB’ developed in CMU. 3. Kabeer Mohammed and Dr.Bhaskara Reddy, “Optimized Solution for Image Processing Through Mobile Robots Working as a Team with Designated Team Members and Team Leader”, International Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 3, 2013, pp. 140 - 148, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375. 139