This intelligent touch screen enables individuals with limited hand mobility or weak upper limb function to operate their wheelchair. 

This automatic brushing device is designed to assist elderly individuals with limited motor skills in maintaining proper oral hygiene. It provides an effortless brushing experience, ensuring thorough cleaning while addressing the challenges faced by those with reduced hand strength or dexterity. 

This project involves the simulation of a 4-wheeled mobile robot in the Gazebo environment, designed for autonomous navigation from one location to another within a simulated space. The robot is equipped with LiDAR sensors and controlled through a navigation stack NAV2 that utilizes algorithms for path planning, obstacle avoidance, and localization. The purpose of this simulation is to test and validate the robot's ability to move efficiently and autonomously within the given environment, ensuring smooth transitions between different waypoints while avoiding obstacles. 

This project focuses on real-time depth estimation by integrating an Intel RealSense depth camera with the Jetson Nano platform and utilizing the YOLOv7 algorithm for object detection. The depth camera captures 3D spatial data, while YOLOv7 processes the images to detect objects efficiently. The Jetson Nano, a powerful yet compact AI computing device, ensures smooth processing and computation, achieving a frame rate of 30 FPS. This system provides accurate depth estimation and object localization, enabling advanced applications such as autonomous navigation, robotics, and scene understanding in real-time environments.