Embodied AI is a field that studies how intelligent agents interact with the real world. It involves multiple aspects such as perception, decision-making, and action, aiming to build intelligent systems that can operate autonomously in complex environments.
“Artificial intelligence makes us think what is artificial and what is intelligence.”
Embodied AI and robotics
VLA model pretraining with human-hand keypoints
Actual deployment on edge robotics platforms
Locomotion of humanoid robots
Focus on how to apply Learning-based methods to the motion control problem of underwater robots, including simulation platform construction, real machine deployment and inference verification. Including single robot and multi-robot. The robot is the carrier of research, and the underwater is a special scene for robot applications. Through the research of underwater robots, accumulate basic engineering experience and general principles of robot system development, and explore cutting-edge neural network methods in combination with reinforcement learning.
“Chase the sea, and become the sea.”
Reinforcement learning for underwater robots
Control Theory for Underwater Systems
Simulation-to-Hardware Framework
Multiagent Systems
