Project 24: Learning-based Multi-robot Cooperation Design and Analysis

Contact Information:

Assoc. Prof. Jianping He

Project Description and Objectives:

This project aims to develop a collaborative system for underwater robots that leverages machine learning to enhance their performance in coordinated tasks. The goal is to create a fleet of autonomous underwater vehicles (AUVs) capable of working together to achieve complex missions such as underwater exploration, environmental monitoring, and maintenance of submerged infrastructure. By employing advanced learning algorithms, these robots will be able to adapt to dynamic ocean conditions, communicate effectively, and make intelligent decisions to optimize their collective efforts. The project's success will pave the way for more efficient and safer underwater operations, reducing human risk and expanding our capabilities in marine research and industry.

Eligibility Requirements:

Interested students should be proficient in Python/C++ programming, basic knowledge of artificial intelligence and have basic knowledge of robot control. In addition, proficiency in English writing and speaking is mandatory.

Main Tasks:

Collaborative Scenarios: Develop algorithms for multi-robot coordination in various underwater mission scenarios.

Task Operations: Program and optimize the robots' task execution to ensure efficiency and accuracy in mission-critical operations.

Simulation and Physical Experiments: Conduct both simulated and real-world experiments to validate the robots' performance and robustness.

Website:

Lab: http://iwin-fins.com

School: http://www.seiee.sjtu.edu.cn/