Explore / Case study / KnowNo — Robots That Ask for Help

KnowNo — Robots That Ask for Help

Demo only

Calibrate candidate actions and ask a person when the next step is ambiguous.

by admin · listed 5 days ago

⚡ What System1 does here

The language model proposes and scores candidate actions. Conformal calibration turns scores into a prediction set; ambiguity triggers human assistance before robot execution. No Jev integration is established.

About

A research framework that helps a robot ask for clarification when a request has multiple plausible interpretations, such as which bowl to put in a microwave. KnowNo evaluates uncertainty-aware planning in simulation and on physical robots. Evidence and limits: The paper’s guarantees assume correctly grounded scene descriptions, successful low-level execution and faithful human help. They are not overall safety guarantees covering perception errors, action failures or incorrect human answers. We did not run the project. Original project images and demonstrations (with attribution):

KnowNo research overview
KnowNo research overview ↗

Candidate actions and clarification in a microwave task ↗

UR5 multi-step tabletop rearrangement experiments ↗

Sources: https://robot-help.github.io/ https://arxiv.org/abs/2307.01928 https://arxiv.org/html/2307.01928v2 https://github.com/google-research/google-research/tree/master/language_model_uncertainty https://youtu.be/xCXx09gfhx4

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