Track ME is a "small" GPS, SD Card, and GSM Shield controlled by an Arduino Mega.
Call me and get my location.
How to make an Arduino 4WD RC Car with Joystick Controller (Arduino Uno | Joystick Shield | nRF24L01+PA+LNA).
Version 2 of my lane detection system!
Using Arduino and Android
Build a Semi-autonomous, 4WD Raspberry Pi Car with a camera stream!
This project shows how you can build a car which can be controlled by your smartphone using an android application via Bluetooth.
This the Bluetooth controlled car that used HC-05 Bluetooth module to communicate with mobile.
MKR WiFi 1000 talks to a car through OBD-II interface, and uploads the data to IoT cloud for real-time monitoring and post-processing.
A simple lane detection system I had developed a while back.
Simplest wifi car controlled by your smartphone using NodeMcu esp8266 and Blynk.
Track local aircraft traffic in real-time.
Ever want to say thanks to the nice person who just let you in line? I have thought a lot about that, and here is my solution.
An Arduino car project based on the RoboRoverM1 chassis.
Assembly and programming - an overview how easy it can be.
Use three HC-SR04 ultrasound sensors and two battery displays to show you how close the obstacles are and from which side.
If you have this car, you will be able to avoid obstacles and follow the necessary lines to reach your destination and protect the distances
CAN bus hack for reading the battery diagnostics form an electric car.
I want to make a small car with the stepping motor. Now, control the stepping motor first!
Using OpenCV on Raspberry Pi, Check if somebody's in my parking spot! Use the power of the cloud to notify me.
This four wheeled car can be controlled through a node web server where a custom camera view can be displayed.
Visualize car data with a free Blynk account, particle electron and Carloop.
Make an assistant which tells you about how much to drive backwards without any collision through your smartphone by Arduino and 1Sheeld.
The control of a robot may be painful as you have to develop specific clients for each mobile device. I propose a Web based control
Real-time hazard classification and tracking with TensorFlow. Sensor fusion with radar to filter for false positives.