DTMF and Gesture Controlled Robotic Wheelchair

In this world a number of people are handicapped. Their life revolves around wheels. This project presents an approach for controlling wheelchair movement using hand gesture recognition and DTMF of a smartphone.

Introduction

DTMF Control :- Conventionally, Wireless-controlled robots use RF circuits, which have the drawbacks of limited working range, limited frequency range and the limited control. Use of a mobile phone for robotic control can overcome these limitations. It provides the advantage of robust control, working range as large as the coverage area of the service provider, no interference with other controllers and up to twelve controllers.

Although the appearance and the capabilities of robots vary vastly, all robots share the feature of a mechanical, movable structure under some form of control. The Control of robot involves three distinct phases: perception, processing and action.

Generally, the preceptors are sensors mounted on the robot, processing is done by the on-board microcontroller or processor, and the task is performed using motors or with some other actuators.

Man has come long way In terms of development over a period of time we would use the RF modules for the purpose wireless after that we overcome with the techniques of GSM modems and we use the DTMF in wireless system.

The DTMF technology has overcome the problem of limitation which we can work only in limited range or limited area was in RF technology by using cell phone (DTMF).

We can access our device or the robot as large as the working space of the service provider, no interference with other controllers and up to 5 controls.

Gesture control :- It is simple and has some features to recognize and it offers robust recognizing gestures of one’s hand. The curvature based hand gesture recognition algorithms recognizes hand gestures using a combination of hand shape contour geometry and calculating the distance from the center of hand to the convex hull on the fingertips.

In this project, this method is able to recognize 5 different hand gestures in same backgrounds for five status movement of wheelchair like as: forward, reverse, left, right and stop.