ROBOTIC HAND CONTROLLING USING FLEX SENSORS AND ARDUINO UNO

Abstract - This paper envisions a robotic arm that can perform such tasks where human intervention is not possible. Robots can perform certain tasks in environments where human interaction is not possible. Here we design a robotic hand with the help of the Arduino Uno flexible sensor 1. Introduction Unfortunately most people lose limbs in accidents while working with large machinery. Other parts may be missing from birth. However with the development of technology limb prostheses such as grasping objects and running have become possible. These devices are called prostheses. A robotic hand is a mechanical device that can perform activities in parallel with a human hand. Robotic hands are an integral part of almost every manufacturing company. The companys robotic arms perform a variety of tasks including cutting and insertion welding. The biggest advantage of this hand is that it can work in dangerous areas as well as in places that are difficult for people to access. The main objective of this research work is to design and fabricate prosthetic components strong enough to perform the given task. Hands are one of the most complex and load-bearing parts of the human body that serve as human input and output devices. This goal aims to use flexible sensors. A sensor is a device that detects or measures a physical quantity and then records and responds to it. Robotic hand manipulators can have different arrangements. Some of these constraints can be accurately replicated from the realm of the human hand in the limited joint space of the robot. This paper proves a general method for representing human motion in the domain of a robot hand. At that moment the hand responds almost exactly to the robotic hand. 2. Related work: In a more challenging way inertial sensors and their research applications are discussed in [1]. [2] analyzes the impact of different sensors on navigation system performance. [5] presents a proposed control strategy for remote operation of an anthropomorphic robot arm controlled via LAN or Internet. [6] Mobile robot positioning related technologies such as GPS pattern magnetic compass inertial navigation odometry etc. 8] But the important contribution of this work is that any movement of a human hand can be compared with a robot hand with good accuracy. Also microcontroller coding makes the task much easier. Modeling: The goal is to develop processes that help users control and program a robot using a special robot language with high intelligence. An approach to robot performance in terms of high-level features such as gestural communication manual navigation visual observation of human performance etc. Defines the users method of operation. Developing and controlling an industrial robot with a machine application is a critical task that takes time and requires technical expertise. This requires new and more user-friendly programming and management methods. This paper presents many details of human gesture recognition related to finger motion and hand motion detection systems. Accelerometer-based gesture recognition has grown its own graph over the past decade. The affordable price and small size of accelerometers make them an excellent tool for detecting and detecting human body signals. Many studies have been conducted on signal detection from data acceleration using Artificial Neural Networks (ANN).

4. Methodology: Figure-2: Human Hand Using Flex Sensor In this project we use a flex sensor for each finger to detect the movement of one finger. 5 sensors are placed in the glove which makes the sensors easy to use. The second part of the manipulator consists of 5 fingers which are controlled by five servo motors for each finger. On top of this the hand is equipped with 5 flex sensors for each finger. Movements such as finger flexing are detected using the ATMega16 microcontroller and the data is then sent to one of the ports via serial communication. The microcontroller will generate a suitable PWM signal to control the servo motor. The complexity of the project can be reduced throughout the project in properly aggregated subdesigns. This enables them to make better plans and work more efficiently. The reading of each finger is measured by means of tension while the movement of each finger will be given in the form of an angle. So that you can relate the voltage to the angle of each digit on the resulting graph line. By calculating the equation for each row we can easily refer to them.

Robotic arm: The robotic arm contains the circuits that control the robotic arm. The Arduino Mega 2560 is programmed to send the required data with the help of the APC-220 module and receive the data transmitted from the robotic arm. The mounting gyroscope and the accelerometer respectively obtain the angle (alpha beta and gamma) and the acceleration of the hand in all three directions sending a signal through the cable to the Arduino Mega where the values ​​are combined together and processed. Meanwhile the flex sensor does its job by measuring the finger movement to the Arduino Mega.

Robotic hand: This is the main tool for operating the robotic glove. The sum of 6 n. The servo is connected in such a way as to provide a 3 DOF (degrees of freedom) system. An Arduino UNO microcontroller that inputs values ​​from the module and sends the data to the appropriate servers.

Robotic arm process of action: • Read sensor values. • Microcontroller processes sensor values. • Send the value from the microcontroller to the servo motor. • Manipulator based on finger movements.

. flow chart

Data communication flow chart The performance of the manipulator is tested by different finger movements. The design of the manipulator is kept modest without the use of various gears and mechanisms. Robotic hands can reproduce finger movements. We investigated a method that combines the hardware and software of a robotic hand controller with five servo motors using a microcontroller. The microcontroller-based program can be flexibly modified to suit the required servo motor steering control. Researchers can solve the problem of wireless control of robotic hands by adopting wireless application protocols. This way I can use the robotic hand more efficiently. Thank you

codee

#include <Servo.h> Servo servo_1; Servo servo_2; Servo servo_3; Servo servo_4; Servo servo_5; int flex_1 = A0; int flex_2 = A1; int flex_3 = A2; int flex_4 = A3; int flex_5 = A4; ; void setup() { servo_1.attach(0); servo_2.attach(1); servo_3.attach(2); servo_5.attach(3); servo_4.attach(4); } void loop() { int flex_1_pos; int servo_1_pos; flex_1_pos = analogRead(flex_1); servo_1_pos = map(flex_1_pos, 800, 900, 0, 180); servo_1_pos = constrain(servo_1_pos, 0, 180); servo_1.write(servo_1_pos); int flex_2_pos; int servo_2_pos; flex_2_pos = analogRead(flex_2); servo_2_pos = map(flex_2_pos, 800, 900, 0, 180); servo_2_pos = constrain(servo_2_pos, 0, 180); servo_2.write(servo_2_pos); int flex_3_pos; int servo_3_pos; flex_3_pos = analogRead(flex_3); servo_3_pos = map(flex_3_pos, 800, 900, 0, 180); servo_3_pos = constrain(servo_3_pos, 0, 180); servo_3.write(servo_3_pos); int flex_5_pos; int servo_5_pos; flex_5_pos = analogRead(flex_5); servo_5_pos = map(flex_5_pos, 800, 900, 0, 180); servo_5_pos = constrain(servo_5_pos, 0, 180); servo_5.write(servo_5_pos); int flex_4_pos; int servo_4_pos;

flex_4_pos = analogRead(flex_4); servo_4_pos = map(flex_4_pos, 800, 900, 0, 180); servo_4_pos = constrain(servo_4_pos, 0, 180); servo_4.write(servo_4_pos); delay(100); }

Component Arduino Uno, Flex Sensor5,10 kΩ ResistorSERVO1, SERVO2, SERVO3, SERVO4, SERVO5 5Positional Micro Servo

the link to the simulation is given below

simulation link click here