Robots can make our lives better by helping at home, in hospitals, and on farms. But most robots today can only do tasks that are pre-programmed ahead of time. They cannot handle new situations or learn from people. This project supports research to create robot helpers that learn new skills like humans do. These robots will learn by watching people, trying tasks, and improving from feedback. This work should make robots more helpful and flexible, so they can solve harder problems in the real world. It also intends to help us understand how robots can learn and adapt. The project looks to improve robots for homes, healthcare, and agriculture. It will also get stimulate students in science through hands-on robotic activities. This project seeks to develop a new framework for teaching robots to learn tasks in real time. It uses three key approaches. (1) Learning from Demonstration helps robots gain skills by watching human actions. It addresses differences between what humans show and what robots can do. This allows robots to apply knowledge across different tasks and places. (2) Learning through Interaction helps robots take in feedback from people and their surroundings. It handles situations where information may be unclear or incomplete. (3) Learning through Collaboration helps robots understand human intentions and goals. It makes effective teamwork on shared tasks possible. Researchers will test these approaches in real-world settings such as homes and greenhouses. App