HIPPIE – Autonomous Robots Using Machine Learning and Swarm Intelligence
This project builds low-cost autonomous robots in Nepal that integrate machine learning, computer vision, and swarm intelligence for collaborative navigation and task execution.
Inspired by MIT's Duckietown project, this initiative explores the application of Artificial Intelligence, Machine Learning, and Deep Learning in Robotics within a low-cost framework suitable for Nepal. The underlying challenge is to evaluate and demonstrate the possibilities of modern robotics, particularly self-driving and swarm robotics, using accessible and affordable technologies.
Our goal is to develop and assess low-cost autonomous robots in Nepal, combining AI and machine learning with computer vision and swarm intelligence. This includes building base robots, implementing semi-intelligent navigation, and enabling collaborative swarm behaviors.
This project successfully developed a low-cost autonomous robotics platform in Nepal, combining machine learning, deep learning, and swarm intelligence. Multiple robot prototypes were built and tested, from base Hippiebots equipped with AVR Atmega32 microcontrollers to AI-enabled bots with computer vision capabilities. The robots demonstrated obstacle detection, path planning, and collaborative navigation, showcasing the potential of accessible robotics technology and intelligent systems for real-world applications.