Towards automatic visual fault detection in highly expressive human-like animatronic faces with soft skin
| Autor: | James P. Diprose, Amit Kumar Pandey, Ralf Mayet |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Social robot business.industry Computer science 05 social sciences 02 engineering and technology Expression (mathematics) Field (computer science) Fault detection and isolation 020901 industrial engineering & automation Face (geometry) Robot 0501 psychology and cognitive sciences Computer vision Artificial intelligence Actuator business 050107 human factors |
| Zdroj: | RO-MAN |
| DOI: | 10.1109/ro-man46459.2019.8956418 |
| Popis: | Designing reliable, humanoid social robots with highly expressive human-like faces is a challenging problem. Their construction requires complex mechanical assemblies, large numbers of actuators and involves soft material. When deploying these robots in the field they face problems of wear and tear and mechanical abuse. Mechanical defects of such faces can be hard to analyze automatically or by manual visual inspection. We propose a method of automatic visual calibration and actuator fault detection for complex animatronic faces. We use our approach to scan three expressive animatronic faces, and analyze the data. Our findings indicate that our approach is able to detect faulty actuators even when they contribute to the overall expression of the face only marginally, and are hard to spot visually. |
| Databáze: | OpenAIRE |
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