Summary of Skillmimic: Learning Reusable Basketball Skills From Demonstrations, by Yinhuai Wang et al.
SkillMimic: Learning Reusable Basketball Skills from Demonstrations
by Yinhuai Wang, Qihan Zhao, Runyi Yu, Ailing Zeng, Jing Lin, Zhengyi Luo, Hok Wai Tsui, Jiwen Yu, Xiu Li, Qifeng Chen, Jian Zhang, Lei Zhang, Ping Tan
First submitted to arxiv on: 12 Aug 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Graphics (cs.GR); Machine Learning (cs.LG); Robotics (cs.RO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes SkillMimic, a data-driven approach that learns various basketball skills by mimicking both human and ball motions. The method employs a unified configuration to learn diverse skills from datasets containing about 35 minutes of diverse basketball skills, including layups, dribbling, and shooting. The approach allows training a single policy to learn multiple skills, enabling smooth skill switching even if these switches are not present in the reference dataset. To evaluate SkillMimic, two basketball datasets were introduced: one estimated through monocular RGB videos and another using advanced motion capture equipment. Experimental results show that the method can effectively learn various basketball skills with a unified configuration. Additionally, by training a high-level controller to reuse the acquired skills, complex basketball tasks like layup scoring can be achieved. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about creating a new way to teach robots or computers how to do different things, like play basketball. It’s inspired by how humans learn from demonstrations and wants to make it easier for machines to learn too. The new method, called SkillMimic, uses data and motion tracking to teach robots various basketball skills, such as dribbling and shooting. The goal is to make the robot able to switch between different skills easily and even do complex tasks like scoring a basket. |
Keywords
» Artificial intelligence » Tracking
