Project
ALOHA
Low-cost bimanual hardware and teleop stack paired with ACT-style algorithms.
ProjectFeaturedIntermediate
GELLO
Low-cost leader-follower teleop arms for collecting high-quality manipulation demos.
Why: Affordable bimanual teleop hardware+software path
Overview
GELLO provides low-cost leader-follower teleoperation arms for collecting manipulation demonstrations. It is a practical hardware companion when you want kinesthetic teaching without full ALOHA complexity.
Focus on mechanical rigidity, encoder reliability, and recording pipelines into LeRobot or robomimic formats.
Learning Path: alternative real teleop path beside ALOHA / SO-ARM.
Who it is for
Researchers, students, and builders comparing open embodied stacks.
Key highlights
- Low-cost leader-follower teleop arms for collecting high-quality manipulation demos.
- Type: project; categories: tool
- Marked recommended on the hub
When to use
- You are mapping the open embodied AI landscape
- You need a starting URL and judgment note before deep-diving
When not to use
- You need production SLAs or certified industrial support only
- License or hardware constraints are incompatible with your deployment
Getting started
- 1Open the official URL and read README install pins.
- 2Skim license and citation requirements.
- 3Run the smallest official example before scaling experiments.
- 4Cross-link related hub resources (sim / data / policy) for a full stack.
Papers & reading
Caveats & pitfalls
- Hub cards are curated summaries — always verify upstream docs.
- Stars and dates drift; treat extra.stars as approximate.
Content reviewed 2026-07-28