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HCPLab-SYSU/Embodied_AI_Paper_List
[Embodied-AI-Survey-2025] Paper List and Resource Repository for Embodied AI
A paper-list companion to the HCPLab-SYSU embodied AI survey (IEEE/ASME T-Mech 2025), organizing hundreds of papers across simulators, perception, interaction, agents, sim-to-real, and datasets. It's for researchers or grad students who want a literature map of the embodied AI space rather than a tool to run.
The taxonomy mirrors the survey's own structure, so you can jump from a section heading straight to the matching chapter in the linked PDF for context instead of just a bare list. It's kept current into 2026 with recent arXiv entries rather than frozen at publication time. Coverage genuinely spans the full stack, from low-level SLAM and point-cloud backbones up through VLA models and 3D scene affordance work, which is useful for getting oriented across subfields quickly.
Every entry is a title plus author list plus link with no abstract or one-line takeaway, so you still have to open dozens of PDFs to figure out which ones are relevant to you. Formatting is inconsistent (author order flips between 'First Last' and 'Last, First' depending on the section, some entries have working project/code links, most don't). There's no versioned export (BibTeX file, JSON index) for pulling entries into a reference manager, just raw markdown you'd have to scrape yourself. The list only grows and nothing appears to get pruned or ranked by significance, so the highest-signal papers aren't distinguished from routine incremental ones.