Work

Learning Contact-Rich Tasks for the Industry 5.0

Year: 2024

Type: conference-paper

Abstract: With industry 4.0, manufacturing transitioned from mass production to mass customization, thus requiring robotic systems to constantly adapt to new requirements. In this context, traditional programming techniques might not be sufficient to cope with contact-rich tasks, especially when the surface to be treated is complex. With this work, we review advancements in Learning from Demonstration techniques that tackle these issues by injecting human knowledge in the robotic systems.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14731042

Authors: Dalle Vedove, Matteo, Lamon, Edoardo, Palopoli, Luigi, Daniele Fontanelli, Saveriano, Matteo

Language: English

Topic: Robot Manipulation and Learning

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6949671560

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