US 2026/0097508 A1 · UNCERTAINTY-AWARE FAILURE DETECTION FOR IMITATION LEARNING ROBOT POLICIES

Abstract

Systems and methods described herein relate to generating a discrimination scores set based on observation data and action data obtained from a robot trained to perform a task, determining a threshold value based on the discrimination score set, and comparing a discrimination score obtained while the task is being performed with the threshold value to determine if a failure condition is present. This may be performed by utilizing random network distillation or other out-of-distribution detectors and conformal band prediction computed on a set of successful rollouts by the robot.

Claims20

Dependent claims

A system, comprising:

a processor;
and
a memory communicably coupled to the processor and storing machine-readable instructions that, when executed by the processor, cause the processor to:
generate a discrimination scores set based on observation data and action data obtained from a robot trained to perform a task;
determine a threshold value based on the discrimination score set;
and
compare a discrimination score obtained while the task is being performed with the threshold value to determine if a failure condition is present.

4 more elements

Dependencies are inferred from the claim text.

Facts

Application

19/189,531Filed 25 Apr 2025

Priority

8 Oct 2024

Published

9 Apr 2026

Term ends

Not estimatedThe source records don’t support an estimate.

Classification3 codes

B25J 9/1674
Program controls: characterised by safety, monitoring, diagnostic
B25J 9/1653
Characterised by the control loop: parameters identification, estimation, stiffness, accuracy, error analysis
B25J
Manipulators

Uncertainty-aware failure detection for imitation learning robot policies

Life of this patent

Uncertainty-aware failure detection for imitation learning robot policies

Life of this patent

Abstract

Claims20