Gesture Control of a Self-Balancing Robot Using TensorFlow

Gesture control of a self-balancing robot using deep learning with TensorFlow Lite.

Dec 1, 2019

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3 respects

Components and supplies

1

HC-05 Bluetooth Module

1

Nano 33 BLE Sense

Project description

Code

IMU Classifier

c_cpp

This example uses the on-board IMU to start reading acceleration and gyroscope data from on-board IMU, once enough samples are read, it then uses a TensorFlow Lite (Micro) model to try to classify the movement as a known gesture. Created by Don Coleman, Sandeep Mistry modified by Rolf Kurth

Bluetooth Receiver from self balancing robot

c_cpp

IMU Classifier

c_cpp

This example uses the on-board IMU to start reading acceleration and gyroscope data from on-board IMU, once enough samples are read, it then uses a TensorFlow Lite (Micro) model to try to classify the movement as a known gesture. Created by Don Coleman, Sandeep Mistry modified by Rolf Kurth

IMU_Capture

c_cpp

This example uses the on-board IMU to start reading acceleration and gyroscope data from on-board IMU and prints it to the Serial Monitor for one second when the button is pressed. Created by Don Coleman, Sandeep Mistry modified by Rolf Kurth

Bluetooth Receiver from self balancing robot

c_cpp

Downloadable files

sbrobotv03export_CNOGijFIPd.fzz

sbrobotv03export_CNOGijFIPd.fzz

sbrobotv03export_CNOGijFIPd.fzz

sbrobotv03export_CNOGijFIPd.fzz

Comments

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Anonymous user

3 years ago

I'm in the process of building a self-balancing robot similar to yours for a class I'm teaching. I'm not great at coding. I was wondering if I could use machine learning to train the bot how to balance instead of writing all the PID controller code myself?