BinceQu/RoboHarness
A robotic harness that gives LLM agents a visual-geometric control panel so that they can directly understand and invoke embodied tasks.
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README & documentation
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Project Page · Quick Start · Documentation · Citation · 中文 [](LICENSE) [](#reproduction-contract) [](docs/assets/overview.pdf) RoboHarness overview: visual keypoints are tracked persistently, converted into geometric constraints, executed, and verified in a closed loop. View original PDF Without training models, RoboHarness combines visual clicks, keypoint tracking, and geometric constraints to provide an embodied control panel for an LLM agent. The LLM marks points of interest on a 2D image and continuously receives their positions via optical-flow tracking and depth back-projection; with this information, it composes accurate primitive actions to perform complex manipulation. The reported BEHAVIOR results use Claude Code 2.1.259 with Qwen3.8-Flash-Next-FP8 and the R1 Pro robot. A Codex harness is also available. RoboHarness V2 replaces the tool plugin with a robot workspace that the agent works inside: robot model, joint manuals, readable Python tools and skills. It runs on the same tasks and evaluator with --harness v2; see harness/v2. The commands…
Read the full README ↗ · Preview checked 2026-10-28T11:27:57.196Z
Inside the original README — Document outline
- A Simple Harness Outperforms VLA and World Action Models
- News
- Overview
- Repository structure
- Installation
- Run a task
- Reproduction contract
- Citation
- Development and license
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What this repository does
A robotic harness that gives LLM agents a visual-geometric control panel so that they can directly understand and invoke embodied tasks.
Repository facts
- Owner
- BinceQu
- Primary language
- Python
- Stars
- 241
- Forks
- 16
- Open issues + pull requests
- 0
- License
- MIT
- Archived
- No
- Default branch
- main
- Created
- 2026-10-07T04:39:45.000Z
- Last push
- 2026-10-13T06:31:07.000Z
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