Cyberworks Robotics

AI Vision Autonomous Navigation in Dense Crowds

Autonomous navigation needs to consider various factors. This project develops an AI-driven navigation system for autonomous wheelchairs operating in heavily crowded environments. Using a machine learning pipeline, the system detects nearby pedestrians and classifies situations as “avoid” or “don’t avoid” based on crowd density. A Gazebo simulation with configurable crowds is used for development and testing. The classifier is integrated into the motion planner to enable real-time decisions such as yielding, stopping, or rerouting. The system is validated through simulation and targeted for real-world deployment in environments like hospitals and airports to improve mobility and safety.