SmartHome

C/C++ ESP32 iot

This project is a fork of my thesis project. I leveraged the versatility of this project to make my home smart. Using two levels of professional Finder relays to manage various 220V peripherals and another pair of relays to handle cascading impulses, I automated a total of four rooms with different devices. With a focus on energy efficiency, the system operates with less than 200 mW, thanks to the low-power consumption of the ESP and low-voltage logic. This allows me to control multiple rooms remotely or locally with multiple devices simultaneously, implementing a comprehensive home automation system. The entire setup has been tested on various devices, including smartwatches, old iOS and Android phones. Every device with an embedded browser is fully compatible and functional. It is also possible to set up keyboard macros to automatically control the home automation system, allowing for quick and easy access to frequently used functions. Future plans include the addition of a camera to monitor the home remotely, enhancing security and convenience.

Vision-based target Pursuit and Engagement

Python LUA ROS CoppeliaSim Matplotlib

This project represents a complex challenge where I had the opportunity to apply all the skills acquired during my university years. For instance, I utilized PID controllers and matrix algebra for transformations and spatial position calculations.

A key focus of this project was to demonstrate in real-time the difference between the calculated position of the robot and the actual positions of both the target and the chaser. Additionally, as shown in various demos, the developed targeting system proves to be highly effective and precise.

The project revolves around creating an automatic targeting system for a chaser robot, while a target robot moves intelligently to avoid being intercepted. Both robots operate in unknown environments, requiring them to avoid obstacles with a limited number of sensors while performing their tasks as efficiently as possible.

One particularly challenging aspect was enabling the chaser to recognize the target and define its behavior when the target moves out of its radar (e.g., behind an obstacle). We addressed this scenario by programming the chaser to move to the last known position of the target and perform a 360-degree scan. If the target remains undetected, the chaser returns to a state of random exploration.