At Vilros, one of the most rewarding parts of our work is hearing about the incredible things our customers create. In this post, we’re highlighting three standout Raspberry Pi projects from the Vilros community. Whether you’re just getting started or looking for your next challenge, we hope these builds spark your imagination and inspire you to Make Something Amazing.

Project #1 - Boat Chartplotter

Albert Yao, a Vilros customer, used Raspberry Pi to create a marine navigation solution for his boat.

Project #2 - Garage Door Opener

Scott Friend developed a garage door opener using Raspberry Pi.

Q: What inspired you to use the RPi for this use case?

This project was inspired by my initial setup of Home Assistant for home automation. I chose to run Home Assistant on a Raspberry Pi because of its low power consumption and cost-effectiveness. My goal was to manage home automation tasks such as controlling lights, cameras, and video doorbells efficiently and remotely.

Q: What are your goals with this use case?

My main goals were to enable garage door access from my phone. Our current garage door opener is quite older it only supports two RF remotes and lacks Bluetooth or Wi-Fi connectivity. With more than 2 people living in the house, I wanted a solution that would allow everyone to open the garage door easily and provide remote access for package deliveries. Since my camera sends motion alerts, I can see when a delivery arrives and open the garage door for them from anywhere.

Q: What were some of the major technical challenges you overcame?

There weren’t any major technical challenges during the project. The only initial uncertainty was whether I could connect the relay to the existing switch contacts on the garage door opener while still using the manual wall push button on the same circuit. I assumed it wouldn’t be an issue since a switch and a relay operate similarly—and after testing, it worked perfectly. The only other minor challenge was modifying a 3D-printed case to house the ESP32 and relay and power jack, as there wasn’t an off-the-shelf solution available. However, this was a straightforward task.

Project #3 - Voice-Activated Robot

Vasu Renganathan has developed a voice-activated robot that works in multiple different languages. He's shared a lot of information about the project on his website - http://multilingualrobot.com/

Q: What inspired you to use the RPi for this use case?

Google’s extensive research in speech recognition and text-to-speech technologies, combined with the Raspberry Pi Foundation’s work in accessible single-board computing, inspired me to bring these two ecosystems together. My goal was to create a low-cost, flexible robot capable of interacting with users naturally, much like a human, in the language of their choice.

Through this work, I have developed a voice-enabled robot that can perform a wide range of tasks using natural language interaction. These include moving around the house, delivering information, conducting quizzes and question-and-answer sessions, translating between languages, storytelling for language learners, and retrieving information from online sources such as Wikipedia and the BBC.

The robot supports multiple languages through Google’s APIs, including English, French, Spanish, Japanese, Tamil, Hindi, and many others. By leveraging modern AI platforms such as Gemini and OpenAI, the Raspberry Pi becomes a powerful gateway that allows users to interact with AI through a physical, conversational robot rather than a screen.

Q: What are your goals with this use case?

One of the primary goals of this project is to enable meaningful human–robot interaction in the user’s native language. The robot is designed not only to communicate, but to assist—by teaching new languages, carrying messages within a home environment, conducting interactive learning activities, and responding to users’ emotions through simple sentiment analysis and heuristic rules. With an attached camera, we should be able to capture routine moves from one place to another and combine them with appropriate voice commands.

Longer-term goals include enabling the robot to remember and manage user to-do tasks, provide reminders, and adapt its behavior based on past interactions. Ultimately, this project aims to make AI-driven assistance more personal, approachable, and accessible through a physical, voice-enabled platform.

Q: What were some of the major technical challenges you overcame?

One of the major challenges was integrating multiple technologies seamlessly on a Raspberry Pi platform. This included combining Google’s speech recognition and text-to-speech APIs with Python-based control logic, motor control, powering with batteries, sensors, and real-time audio processing.

Achieving human-like interaction required coordinating three core capabilities: listening to natural language speech, processing it intelligently, and responding both verbally and physically through movement. Ensuring these functions worked reliably together on a resource-constrained device was a significant technical challenge.

Additionally, I developed a web-based dashboard using Apache and a MySQL database, allowing users to configure and control the robot’s behavior through a browser interface. This made the system more flexible and user-friendly while maintaining the performance required for real-time interaction.

This is a multilingual, voice-enabled Raspberry Pi robot that brings AI, language learning, and human-like interaction into the real world.  This project is constantly being improved upon and the current stage of the work is featured in the website http://multilingualrobot.com/ with sample videos, a forty five page detailed description and snapshots of images of the robot and portal.