Ngseo/rss-papers

RSS Papers — Robotics: Science and Systems (PDF archive)

A full-text PDF archive of accepted papers from the Robotics: Science and Systems (RSS) conference, organized by year, with per-paper metadata. Assembled as a convenience mirror of the publicly available official proceedings for personal research and archival use.

Coverage

Year	Edition	Papers
2026	RSS XXII	210
2025	RSS XXI	163
2024	RSS XX	134
2023	RSS XIX	112
2022	RSS XVIII	74
2021	RSS XVII	92
2020	RSS XVI	103
Total		888

Years 2024–2026 additionally ship per-paper topic tags (<year>/tags.json) and an aggregate topic breakdown (<year>/analysis.json) — see the analysis section below.

Repository structure

README.md
<year>/
  papers.csv          # metadata for that year's papers
  p001_<title-slug>.pdf
  p002_<title-slug>.pdf
  ...

• One folder per year (2024/, 2025/, 2026/).
• PDF filename = zero-padded paper id + a slug of the title (e.g. p007_a-systematic-study-of-data-modalities.pdf).
• <year>/papers.csv columns:

column	description
id / num	paper number within the year
session	official RSS session (2026) / —
title	paper title
authors	author list
filename	PDF file name in this folder
pdf_url	original source URL the PDF was fetched from
status	crawl status (downloaded)

How to use

Download the whole dataset (or a single year) with huggingface_hub:

from huggingface_hub import snapshot_download

# everything
path = snapshot_download("Ngseo/rss-papers", repo_type="dataset")

# just one year's PDFs + metadata
path = snapshot_download(
    "Ngseo/rss-papers", repo_type="dataset",
    allow_patterns=["2026/*"],
)

Read the metadata:

import pandas as pd
df = pd.read_csv(f"{path}/2026/papers.csv")
print(df[["id", "session", "title"]].head())

Topic landscape — RSS 2026 (content analysis)

Each 2026 paper was multi-label tagged into a fixed robotics taxonomy from its title + abstract (LLM tagging, cross-checked against the official session labels and unsupervised embedding clusters). Highlights:

Application areas (primary area of each paper)

Rank	Area	Papers (primary)	Papers (tagged)
1	Manipulation (incl. dexterous / grasping / mobile)	92	125
2	Mapping & Localization (SLAM)	16	18
3	Navigation	15	39
4	Humanoids	14	23
5	Multi-Robot & Swarm	9	15
…	Locomotion, HRI	7 each	22 / 17
tail	Aerial, Soft, Tactile, Robot Design	~5 each	—
minor	Autonomous Driving, Medical/Surgical, Field/Marine/Space	3–4 each	—

Methods (multi-label, most common first)

Imitation Learning (70) · Reinforcement Learning (56) · Perception/3D (53) · Foundation Models / LLM-VLM (50) · Self-Supervised Representation (48) · Motion & Task Planning (43) · Sim-to-Real (37) · Diffusion Policy (36) · Safety & Robustness (36) · MPC / Optimal Control (35) · Datasets & Benchmarks (33) · Vision-Language-Action (31) · Trajectory Optimization (27) · World Models (16).

Input modalities: Vision/RGB (116) · Proprioception (76) · Language (56) · Depth/Point-cloud (49) · Tactile/Force (27).

Takeaways

• Manipulation is the dominant theme — ~44% of papers have it as their primary area and ~60% touch it. The official session grouping understates this because manipulation work is spread across the Imitation learning, VLA Models, World Models, and Datasets sessions (RSS session slots are size-balanced for scheduling, so raw session counts flatten true topic prevalence).
• The generative + foundation-model wave is large in aggregate: Foundation Models (50) + Diffusion (36) + VLA (31) + World Models (16) together touch a big share of the program.
• Under-represented at RSS 2026: autonomous driving, medical/surgical robotics, soft robotics, and field/marine/space robotics (each only a handful of papers).

(Analysis method: 3-lens triangulation — official sessions, LLM multi-label tagging of title+abstract, and MiniLM embedding clustering.)

Source & provenance

• 2026: paper list from https://roboticsconference.org/program/papers/, PDFs from https://www.roboticsproceedings.org/rss22/.
• 2024–2025: https://www.roboticsproceedings.org/ (rss20, rss21).

PDFs were fetched directly from the official proceedings; every file was validated (PDF magic bytes + size) and cross-checked against the published paper index.

License & usage

PDFs are © their respective authors and RSS. This is a convenience mirror of publicly available proceedings for personal research and archival use; all rights remain with the original authors/publisher. For the authoritative versions and citation details, refer to the official RSS proceedings at https://www.roboticsproceedings.org/.

If you use RSS papers in your work, cite the individual papers (and RSS) as listed in the official proceedings.