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AdaManip: Adaptive Articulated Object Manipulation Environments and Policy Learning
AEO Score: 4/10
About AdaManip: Adaptive Articulated Object Manipulation Environments and Policy Learning
Articulated Object Manipulation Environments and Policy Learning ICLR 2025 Yuanfei Wang*, Xiaojie Zhang*, Ruihai Wu*, Yu Li, Yan Shen, Mingdong Wu, Zhaofeng He, Yizhou Wang, Hao Dong * denotes equal contribution Paper Code AdaManip investigates under-explored realistic adaptive mechanisms for articulated object manipulation and correspondinly provides a novel simulation environment and dataset.
Key Topics
Details
Category: Technology
adamanip.github.ioAI Visibility Breakdown
1
Structured Data
6
Content Structure
4
Entity Clarity
3
E-E-A-T Signals
5
Technical AEO
2
AI Discoverability
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Source & Attribution
Scored by Engagemii on May 22, 2026. Methodology: engagemii.com/aeo/methodology
Source URL: https://engagemii.com/aeo/brands/adamanip-github-io
Cite this score: Engagemii (2026). "AEO Score for AdaManip: Adaptive Articulated Object Manipulation Environments and Policy Learning." Retrieved from https://engagemii.com/aeo/brands/adamanip-github-io
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