🛠️ Steven Gong

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Oct 03, 2025, 2 min read

Everyday Robots

So sad that this group worked on so many great ideas, and just shut down. That mobile manipulator did some really awesome things.

  • Source: https://www.irvinebrown.com/?p=1748

I think actually many of things Google Deepmind thinks about is scaling up robotics, which is quite important.

Papers that came out of it:

  • Thinking While Moving Deep Reinforcement Learning with Concurrent Control (2020)
    • ?
  • AWOpt Learning Robotic Skills with Imitation and Reinforcement at Scale
    • ?
  • QTOpt Scalable Deep Reinforcement Learning for VisionBased Robotic Manipulation
    • how they did RL for multi-task policy learning
  • BCZ ZeroShot Task Generalization with Robotic Imitation Learning (2022)
    • how they did imitation learning for multi-task policy learning
  • Do As I Can Not As I Say Grounding Language in Robotic Affordances (2022)
  • Deep RL at Scale Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators (2023)
  • Everyday robots shuts down here :(
  • Inner Monologue Embodied Reasoning through Planning with Language Models (2023)
  • AutoRT Embodied Foundation Models for Large Scale Orchestration of Robotic Agents

Robot foundation models

  • RT1 Robotics Transformer for RealWorld Control at Scale
  • RT2 VisionLanguageAction Models Transfer Web Knowledge to Robotic Control

Other

  • ALOHA Unleashed A Simple Recipe for Robot Dexterity
  • RoboCat A SelfImproving Generalist Agent for Robotic Manipulation

Graph View

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