RoboAgentLab/pi-embodied-policy-interactions
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AI & ML interests
Agentic robotics: agents that act, build, and evolve. Robot task execution, robotics software engineering, reusable services and skills, policy distillation, and Robotics R&D.
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Organization Card
RoboAgentLab
Agents that Act, Build, and Evolve.
An open research platform for agentic robotics.
Robotics as software engineering
RoboAgentLab brings robot task execution and experimental development into a shared coding-agent workspace. Built on pi, the platform combines an agent loop and persistent sessions with robotics extensions. Downstream servers provide simulation, robot control, perception, planning, and policy inference; upstream skills explain how to compose these capabilities. The same interfaces are available to agent tool calls and generated Python programs.
Three complementary roles
| Role | Research focus |
|---|---|
| Act — Agent as Policy | Select behaviors, orchestrate tools, and write programs that execute robot tasks. |
| Build — Agent as Infrastructure | Develop and debug robotics systems, reproduce experiments, and connect data collection, training, and evaluation. |
| Evolve — Agent as Self-Evolver | Use feedback to revise and retain reusable components, workflows, and research capabilities. |
Two streams of research data
- Robot policy interactions — Agent interactions with robot environments, including observations, decisions, tool calls, and feedback. Our research goal is to distill large-model teachers into compact policy agents that combine task accuracy with fast inference.
- Robotics R&D interactions — Coding-agent interactions from robotics development, integration, debugging, and testing. Our research goal is to use these traces for domain-specific post-training of open-weight models that can drive the RoboAgentLab harness.
The dataset cards describe the contents and structure of the current releases.
Research and open resources
Our forthcoming paper, Agents that Act, Build, and Evolve: A Unified Framework and Platform for Agentic Robotics, connects these roles within a common framework. We are preparing a coordinated release of the paper, a curated literature list, and RoboAgentLab 1.0.
Explore the platform repository and the datasets above to follow the project.
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