Whole-body Humanoid Robot Locomotion with Human Reference.
arxiv: arxiv.org/abs/2402.18294
Qiang Zhang1,∗, Peter Cui2,∗, David Yan2, Jingkai Sun1, Yiqun Duan3, Arthur Zhang2, Renjing Xu1,†.
1. Hong Kong University of Science and Technology (GZ)
2. PNDbotics
3. Human Centric AI Centre, Australia Artificial Intelligence Institute, University of Technology Sydney 2007 Ultimo
Recently, humanoid robots have made significant advances in their ability to perform complex tasks due to the deployment of Reinforcement Learning (RL), however, the inherent complexity of humanoid robots, including the difficulty of planning complex reward functions and training entire complex systems, still poses a notable challenge.
To conquer these challenges, after many iterations and in-depth investigations, we have meticulously developed a full-size humanoid robot, 'Adam', whose innovative structural design greatly improves the efficiency and effectiveness of the imitation learning process.
In addition, we have developed a novel imitation learning framework based on an adversarial motion prior, which applies not only to Adam but also to humanoid robots in general.
Using the framework, Adam can exhibit unprecedented human-like characteristics in locomotion tasks.
Our experimental results demonstrate that the proposed framework enables Adam to achieve human-comparable performance in complex locomotion tasks, marking the first time that human locomotion data has been used for imitation learning in a full-size humanoid robot.
If you are interested in this humanoid robot, feel free to contact me (peter.htcui@gmail.com, peter.cui@pndbotics.com). :-)
#robot #robotics #humanoidrobot #ai
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