SushankSharma / Wireless-dexterous-anthropomorphic-Gesture-controlled-Robotic-Arm

This project creates a wireless robotic arm that mimics human hand gestures using a glove, flex sensors, and an NRF24L01 transceiver module. The robotic arm is controlled by an Arduino Nano microcontroller and has added movement capabilities with the help of MG996 servo motors. Explore the interaction between human gestures and the digital world.

🤖 The Future of Robotic Arms is Here!

🎥 Check it out in Action!

Want to see the Wireless-dexterous-anthropomorphic-Gesture-controlled-Robotic-Arm in action? 🤖 We've got you covered! 🎉 Check out our Wireless Dexterous Anthropomorphic, Gesture Controlled Robotic Arm, and see the magic unfold! 🔮 Get ready to be wowed by the power of human gestures controlling a robotic arm! 💪

🚨 Warning: Watching this video may result in a sudden urge to build your own robotic arm! 🚨

Introduction 🤖

This project is all about redefining the interaction between human gestures and the digital world. 🤝 Our goal is to create a wireless-dexterous-anthropomorphic-gesture-controlled-robotic-arm that mimics human hand gestures and performs various tasks in real-time. 🤖

How it works 🤔

1. The Tx and Rx circuit attempt to connect via the NRF24L01 transceiver module.
2. After a successful connection, the user can transmit hand gestures using a glove.
3. The transmitted gestures control the movement of the robotic arm.
4. The hardware interacts with the system and external environment using an Arduino Nano microcontroller.

Requirements 💻

• Arduino Nano
• NRF24L01 Transceiver Module
• 3D Printer
• STL Files
• Glove
• Flex Sensors (*10)
• MG996 Servo Motors

Let's get started 🚀

1. Clone the repository

git clone https://github.com/[username]/[repository].git

2. Assemble the hardware components as per the circuit diagram provided in the repository.
3. Upload the code to the Arduino Nano Microcontroller.
4. Put on the glove and control the movement of the robotic arm using hand gestures.

Design Credits 🎨

Inmoov

Conclusion 🤩

This project shows that nearly "96%" of the transmitted signals are successfully configured and demonstrates the interaction between simple human gestures and the digital world. 🤝 This study opens up avenues for further research in the area of gesture control and human-robot interaction. 🤖 Say goodbye to boring button controls and hello to a fun, interactive, and intuitive way to control robots! 🚀