Vision-based Robotic Manipulation

This project focuses on developing intelligent robot control systems that can perceive their environment through computer vision and make decisions based on visual inputs. Using deep reinforcement learning techniques, the robot is trained to recognize objects, grasp them correctly, and manipulate them to perform specific tasks.

The system integrates ROS (Robot Operating System) with computer vision algorithms and deep learning models, creating a robust framework for real-time object detection, pose estimation, and motion planning. This research has applications in industrial automation, healthcare assistance, and service robotics.