Recent interesting robotics papers
Empirical Analysis of Sim-and-Real Cotraining Of Diffusion Policies For Planar Pushing from Pixels

- detailed analysis of co-training on DP sim-and-real

#arxiv #manipulation

X Overview, Arxiv Link
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Adam Wei (@adamwei_)
Adam Wei (@adamwei_)
Learning from both sim+real data could scale robot imitation learning. But what are the scaling laws & principles of sim+real cotraining?

We study this in the first focused analysis of sim+real cotraining spanning 250+ policies & 40k+ evals https://arxi…
arxiv manipulation
NavRL: Learning Safe Flight in Dynamic Environments

- good reward design
- randomized collision environment in IsaacSim and combination of perception in actor-critic network

#RAL2025 #navigation #RL

GitHub Link, Paper Link
GitHub
GitHub - Zhefan-Xu/NavRL: [IEEE RA-L'25] NavRL: Learning Safe Flight in Dynamic Environments (NVIDIA Isaac/Python/ROS1/ROS2)
GitHub - Zhefan-Xu/NavRL: [IEEE RA-L'25] NavRL: Learning Safe Flight in Dynamic Environments (NVIDIA Isaac/Python/ROS1/ROS2)
[IEEE RA-L'25] NavRL: Learning Safe Flight in Dynamic Environments (NVIDIA Isaac/Python/ROS1/ROS2) - Zhefan-Xu/NavRL
RAL2025 navigation RL
Rapidly Adapting Policies to the Real-World via Simulation-Guided Fine-Tuning

- efficient RL algorithm to improve rollout performance

#ICLR2025 #RL #sim2real #refinement

X Overview, Project Website
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Patrick Yin (@patrickhyin)
Current RL finetuning methods are too inefficient to make autonomous real world robot learning tractable. We propose Simulation-Guided Fine-Tuning (SGFT) - a simple, general sim2real framework that extracts structured exploration priors from sim to accelerate…
ICLR2025 RL sim2real refinement
BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics

- insightful idea of using neural dynamics to assist planning

#ICLR2025 #manipulation

X Overview, Project Website
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Keyi (@Keyi_Shen_)
🎯Can robots do better on planning involving neural dynamics?

Introducing our recent work, BaB-ND: https://robopil.github.io/bab-nd/.

Existing sampling- and gradient-based methods may fail short on complex planning problems over non-convex neural dynamics…
ICLR2025 manipulation
DROID: A Large-Scale In-the-Wild Robot Manipulation Dataset

- benchmark with precise calibration
- it is mind-blowing to see how modern vision model could help to calibrate automatically

#arxiv #dataset

X Overview, Project Website
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Zubair Irshad (@mzubairirshad)
Introducing ✨Posed DROID✨, results of our efforts at automatic post-hoc calibration of a large-scale robotics manipulation dataset.

We provide:
🤖 ~36k calibrated episodes with good quality extrinsic calibration
🦾 ~24k calibrated multi-view episodes with…
arxiv dataset
π0.5: a VLA with Open-World Generalization

- following work of pi-0
- utilize co-train and use VLM to identify low-level tasks from high-level command

#arxiv #manipulation

X Overview, Project Website, pi-0
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Chelsea Finn (@chelseabfinn)
Introducing π-0.5!

The model works out of the box in completely new environments.

Here the robot cleans new kitchens & bedrooms. 🤖

Detailed paper + videos in more than 10 unseen rooms:
http://physicalintelligence.company/blog/pi05

A short thread 🧵
arxiv manipulation
Policy Decorator: Model-Agnostic Online Refinement for Large Policy Model

- using RL with residual policy to fine-tune online policy
- similar to TRANSIC

#ICLR2025 #RL #refinement

X Overview, Project Website, TRANSIC
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Tongzhou Mu 🤖 @ ICLR 2025 (@tongzhou_mu)
🤔 How to fine-tune an Imitation Learning policy (e.g., Diffusion Policy, ACT) with RL? As an RL practitioner, I’ve been struggling with this problem for a while. Here’s why it’s tough:

1️⃣ Special designs (usually for multimodal action distributions) in…
ICLR2025 RL refinement
SRSA: Skill Retrieval and Adaptation for Robotic Assembly Tasks

- following work of IndustReal, AutoMate
- NVIDIA assembly

#ICLR2025 #assembly

X Overview, Project Website, IndustReal, AutoMate
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NVIDIA Robotics (@NVIDIARobotics)
Dive into this #ICLR2025 robotics research paper from #NVIDIAResearch, which focuses on skill retrieval and adaptation for #robotic assembly tasks.

The framework teaches robots new tasks using preexisting skill libraries, boosting zero-shot success rates…
ICLR2025 assembly
HOVER: Versatile Neural Whole-Body Controller for Humanoid Robots

- universal controller for humanoids utilizing co-train with mask
- detailed benchmark

#RSS2025 #humanoid

X Overview, Project Website
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Tairan He (@TairanHe99)
🤖 Humanoids are expected to be the ultimate embodiment for general-purpose robots, but reaching that potential means adapting to diverse tasks—navigation, tabletop manipulation, loco-manipulation—each needing unique control modes.

🤔 Can one controller handle…
RSS2025 humanoid
Reactive Diffusion Policy: Slow-Fast Visual-Tactile Policy Learning for Contact-Rich Manipulation

- good engineering using AR
- slow+fast diffusion procedure

#RSS2025 #contact_rich #tactile

X Overview, Project Website
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Han Xue (@HanXue012)
Humans can easily perform complex contact-rich tasks with vision and touch, but these tasks remain challenging for robots. How can we resolve this from both the algorithm side and the data side?

Introducing Reactive Diffusion Policy (RDP),a slow-fast imitation…
RSS2025 contact_rich tactile
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