A robotics project that integrates a robotic arm mounted on a mobile platform to autonomously detect, navigate towards, and manipulate(lift) objects based on natural-language commands using 6D pose estimation of the object. The project will utilise ROS, Gazebo, ArUco Markers, 6D pose estimator and LLMs.
The project is designed to enhance road safety and traffic management by accurately detecting and tracking objects on roads and highways. Uses YOLOv7 and DeepSORT for object detection on BDD100K dataset.
The Final Year Design Project aims to improve object grasping and manipulation in warehouses. It features an autonomous robotic arm that efficiently retrieves items from any defined place using dual monocular cameras for 6D object pose estimation and techniques involving robotics and machine learning for grasping strategies that includes kinematic modeling and inverse kinematic modeling of the robotic arm.
This project demonstrates the use of YOLOv8 for detecting American Sign Language (ASL) gestures.