Symbian based robot control using Bluetooth and MEMS

Abstract

In this application we discuss about the utilization of gesture recognition technique on a mobile phone. We also discuss about the possible applications using readily available hardware like mobile gaming or wheelchair control etc.

The proliferation of accelerometers on consumer electronics has brought an opportunity for interaction based on gestures or physical manipulation of the devices. This provides flexibility for the users to employ personalized gestures and make some physical manipulations.

Introduction

Mobile phones are the most pervasive wearable computers currently available and have the capabilities to alter and manipulate our perceptions. They contain various sensors, such as accelerometers and microphones, as well as actuators in the form of vibro-tactile feedback. Visual feedback may be provided through mobile screens or video eye wear. Dynamic input systems in the form of gesture recognition are proving popular with users, with Nintendo’s Wii being the most prominent example of this new form of interaction,

that allows users to become more engaged in video games

[1]. The video game experience is now affected not only by

timing and pressing buttons, but also by body movement.

To ensure a fast adoption rate of gesture recognition as an

ubiquitous input mechanism, technologies already available

in mobile phones should be utilized. Features like accelerometer sensing and vibro-tactile feedback are readily available in high-end mobile phones, and this should filter through to most mobile phones in the future.

Gesture recognition allows users to perceive their mobile phone as an input mechanism.

This application helps in controlling the wheel chair or the robot or a toy car with less physical efforts thus improving overall well being and quality of life.

Implementation

In the cases where a gesture recognition has been implemented on a resource-constrained device, only the simplest algorithms were considered and implemented to recognize only a small set of gestures; only three different gestures were recognized. We have developed an accelerometer-based gesture recognition technique that can be implemented on a mobile phone. The gesture recognition algorithm was optimized such that it only requires a small amount of the phone’s resources, in order to be used as a user interface to a larger piece of software, or a video game, that will require the majority of the system resources.