Wheeled Robot Design with Brain Wave Headset Control System

This project discusses about a brain controlled robot based on Brain Computer Interfaces (BCI). BCIs are systems that can bypass conventional channels of communication (i.e., muscles and thoughts) to provide direct communication and control between the human brain and physical devices by translating different patterns of brain activity into commands in real time. With these commands a mobile robot can be controlled. The intention of the project work is to develop a robot that can assist the disabled people in their daily life to do some work independent of others. Here, we analyze the brain wave signals. Human brain consists of millions of interconnected neurons. The pattern of interaction between these neurons is represented as thoughts and emotional states. According to the human thoughts, this pattern will be changing which in turn produce different electrical waves. Muscle contraction also generates unique electrical signals. All these electrical waves will be sensed by the brain wave sensor and converts the data into packets and transmits through Bluetooth medium. The brain wave raw data is sent to the computer and it will extract and process the signal using MATLAB platform. Then the control commands will be transmitted to the robot module to process. With this entire system, we can move a robot based on the human thoughts and it can be turned by blink muscle contraction.

Currently border security that incorporates social, cultural, activity and structure aspects of interactions among border security forces, smugglers and therefore the population and represent integrated technology architectures created of mounted and mobile detector and police work networks. These tools give important capabilities that influence border security operations, planning, analysis and coaching. Sensors are being deployed to enhance border security generating monumental collections of knowledge and databases. Sadly, these sensors will reply to a range of stimuli, typically reacting to important events and typically triggered by random events that are thought of false alarms. The intent of this project is to supplement human intelligence in a very detector network framework which will assist in filtering and period of time higher cognitive process from the massive volume of knowledge generated. In our project, the projected system that has secured to the motherland by victimization ideas of Wireless Integrated Network Sensors, GPS pursuit and object and metal detection and tracking of vehicles with within the country. By Object identification system we will be ready to get the images of that exact space wherever the strangers has returned in addition, because the details of objects or folks that are gift there. And later the metal police work sensors and bomb noticed signals can detect the existence of explosives and weapons(metals) with them. Presently the Indian government is coming up with to-implement a similar technology for pursuit the vehicles with within the country that carry illegitimate commodities (like government issued sugar , rice to be distributed among lots however send to alternative states without legal permission). The vehicles that carry explosive materials for industrial functions are often half-tracked.

IRJET, 2022

Robot control systems have been a topic of greater research. The control systems have different implemented in near present yet the topic of the control of the robotic vehicle remains of greater research. This project deals with the development of voice controlled robotic vehicle. The Robotic vehicle is designed which can move forward, backward, left and right using the voice commands given by the user using android application. The android application developed uses speech to text to determine the voice commands and then Bluetooth socket to send it to the robotic vehicle. The robotic vehicle structure then parses the incoming Bluetooth data to move or navigate the robotic vehicle in different directions. The robotic vehicle can move in different directions as well as turn at degree as we have included the precision turning system using servo motors.

Improving the quality of life for the elderly and disabled people and giving them the proper care at the right time is one the most important roles that are to be performed by us being a responsible member of the society. It’s not easy for the disabled and elderly people to mobile a mechanical wheelchair, which many of them normally use for locomotion or movements. Hence there is a need for designing a wheelchair that is intelligent and provides easy mobility. In this thesis, an attempt has been made to propose a brain controlled wheelchair, which uses the captured signals from the brain and processes it to control the wheelchair. Electro-encephalography (EEG) technique deploys an electrode cap that is placed on the user’s scalp for the acquisition of the EEG signals which are captured and translated into movement commands by the arduino microcontroller which in turn move the wheelchair. After measuring brain waves it delivers to brain to computer interface unit which analyzed and amplified and classify waves into alpha, beta, gamma, theta waves and attention and meditation parameter .Direction of wheelchair is controlled by any of these parameter values. Sensor circuit is used to detect object in the way of wheelchair and provide protection from collision.

2017

Paralysis is one amongst the major neural disorder that causes loss of motion of one or more muscles of the body, where in depending on the cause, it may affect a specific muscle group or region of the body or a larger area may be involved. In pursuit of rehabilitation, the eye can be regarded as one of the organs that can help a paralyzed person to communicate suitably. The Brain Signals of such patients can be used to help them communicate to others and also to perform various tasks by providing necessary infrastructure and training. This project describes the acquisition and analysis of Brain signals for operating a robot having a robotic arm mounted on top of it. The proposed method here uses a minimum number of electrodes for obtaining the brain signals using EEG Headsets available in the market and then control a robot based on the levels of these brain signals which can be varied by varying the states of mind. The EEG Headset detects the signals and generates a discrete value. This value is then sent over Bluetooth to a PC/ Laptop for further processing and plotting using MATLAB. After processing the actions to be performed are sent over ZIGBee to the ARM Microcontroller that controls the robot as well as the robotic arm mounted on the robot.

2013

It"s quite obvious that it"s near to impossible to develop fully functional human brain in laboratory, which we can use for our robots for taking intelligent decisions by its own. When it is not beneficial to manufacture something by our own then we should go for a something which is already developed and which easily available with us. And that is our brain! A human brain! There are lots of research are going on in development of Brain Interactive Robotics System in these days. As a part of this research/development in BIR, here I present the architecture of future system called "Shree Yantra", which shows how we can use the human brain thoughts as commands for robot to perform various tasks. This paper shows how different part of the one fully functional system could work. This also shows prototype of the algorithm which can be use for decoding of biotic/neurons signal and to generate appropriate command for robot.

Arxiv, 2022

This paper presents Open-source software and a developed shield board for the Raspberry Pi family of single-board computers that can be used to read EEG signals. We have described the mechanism for reading EEG signals and decomposing them into a Fourier series and provided examples of controlling LEDs and a toy robot by blinking. Finally, we discussed the prospects of the brain-computer interface for the near future and considered various methods for controlling external mechanical objects using real-time EEG signals.

EEG based Brain Computer Interface (BCI) can be classified as one of the new communication channel that exists between the Human & Computers only through the biological signals by avoiding the use of muscular activity in association for executing different applications involved in it. There are many available technologies & interfaces that are facilitating in reading the bio-electrical signals from human brain associated with explicit commands in controlling various devices. In this work, a technological based application is developed in bringing an engineering solution in development of a conceptual framework, as a part of enhancement in remote controlled communication of a robot through Brain (EEG) signals interacted by the end-users.

This brain controlled robot is based on Brain-computer interfaces (BCI). BCIs are systems that can bypass conventional channels of communication (i.e., muscles and thoughts) to provide direct communication and control between the human brain and physical devices by translating different patterns of brain activity into commands in real time. With these commands a mobile robot can be controlled. The intention of the project work is to develop a robot that can assist the disabled people in their daily life to do some work independent on others.

Embedded system is an emerging field with immense applications in Science and Engineering. The designed ROBOT is a portable machine. Communication between ROBOT and the Control Unit is performed through Radio Frequency (RF) Commu nication. The system basically has two modes. The automatic mode is the first mode and the user control mode is the second mode. ROBOT is controlled with the help of Microcontroller in the control unit and is programmed my means of microcontroller in it. The primary aim of the project is to design, develop and implement Automatic Wall Painting Robot which helps to achieve low cost painting equipment along with object recognition. The robotic system is remote controlled. Thus the aim is to provide a robotic system that can be used in industrial applications. In this paper the robot is controlled from the system using MATLAB so ftware

Brain-computer interface (BCI) system provides communication channel between human brain and external devices. The system processes and translates thought into control signals and thus enabling a user to navigate a robot from one place to another. In this context, we developed a system that enables a user to guide a robot by brain waves. The system consists of an Emotiv Epoc headset, a personal computer, and a mobile robot. The Emotiv Epoc headset attached to the head of the user and used to collect Electroencephalogram (EEG) signals. The headset picks up brain activities from 14 locations on the scalp and sends them to the computer for processing. Those brain activities can tell the system what a person is going to do in his virtual reality. Then, by using a novel application designed for this purpose, the cognitive suite supplied by Emotiv is responsible for generating the control actions needed to make the robot execute three different commands: turn right, turn left, and move forward. In this paper, hardware and software architectures were designed and implemented. Experimental results indicate that the robot can be successfully controlled in real-time based on the subject's physiological changes. Keywords: brain computer interface (BCI), electroencephalogram (EEG), emotiv epoc neuroheadset.

Kalpa Publications in Engineering

This research paper presents to develop a bio-signal acquisition system and rehabilitation technique based on “Cognitive Science application of robot controlled by brain signal”. We are trying to Developing a data acquisition system for acquiring EEG signals from Brain sense head band and also designing new algorithm for detecting attention and meditation wave and implementing on Robotics platform By using Embedded core.

Sciendo eBooks, 2020

The brain-computer interface (BCI) is a scientific field recognized by its outstanding significance covering especially biomedical engineering issues to offer thought-controlled assistive devices for people suffering from neurological diseases causing them neuromotor disabilities. However, the major achievements of functional assistive mechatronic systems were obtained in laboratories aimed for experimentation and research studies by using highperformance equipment at the expense of higher costs, cumbersome working principle and solid experience across multidisciplinary areas. This paper proposes an original prototype of a simple brain-computer interface application based on the integration between NeuroSkyMindwave Mobile headset, the Matlab software environment and the Arduino Nano 33 IoT development board along with the necessary electronic components. The aim of the BCI application is the achievement of the control of anexperimental motorcycle by using multiple voluntary eye-blinks detected across the electroencephalographic signal. According to the current scientific literature, there is no evidence of a similar approach to develop a braincomputer interface assistive system providing both cognitive training and enjoyable feedback that can help the user to regain independence and self-esteem. The main contribution of this paper is consisting of the Matlab software implementation of an algorithm for counting multiple voluntary eye-blinks and its integration with the library of functions necessary for the acquisition of the EEG signal from NeuroSky headset and the functions required to send commands aimed to control the motorcycle based on the Arduino Nano 33 IoT development board.

2019

There are several environmental conditions under which human beings do not find conducive to work. In such circumstances, without a considerable amount of safety precautions like in the disposal of hazardous wastes, radioactive substances, remote handling of explosive devices and righting and hostage situations among others, work is impossible. So, there is a need for a machine that will not be affected by these during the course of carrying out the human-like tasks. A prototype of a robotic vehicle for pick and place have been designed and implemented in this study. Our proposed system works by using a Bluetooth module for receiving the Bluetooth command being sent by the operator. The method adopted in this study uses DC motor to move the robotic vehicle to the appropriate direction using commands. The robotic car will move in the appropriate direction sent to him by the operator through the Bluetooth for execution. Our evaluation of the system shows that the robotic car for picking and placing small objects within a limited distance performed according to specification. It thereby proves that it will be useful in an environment that is hazardous to human being.

International Journal of System and Software Engineering, 2019

In order to improve the quality of life of the elderly and the disabled, the system fully considers the lifestyles of the elderly and the disabled and realizes the intelligent control of the wheelchair by using the Internet of Things and the intelligent control technology. By designing wearable equipment, the system can obtain the original EEG signals from the brain, and after filtering the noise and power signals, the brain waves are converted into output signals to realize the control of the wheelchair. Wearable devices are called brain wave collection caps. In addition, the system also has infrared obstacle-avoidance function, speech recognition and other functions, and ultimately to help the elderly and disabled people to achieve the "body with the brain moving" goal. Long-term testing of the system shows that the equipment is easy to operate, suitable for the elderly and disabled people with limited mobility, and it is of great social significance to improve the quality of life and happiness index.