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Related Experiment Video

Updated: Jul 28, 2025

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

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Published on: February 12, 2017

The morphological paradigm in robotics.

Sascha Freyberg¹, Helmut Hauser²

¹Max Planck Institute for the History of Science, Berlin, MPIWG, Dept. 1, Boltzmannstr. 22, 14195, Berlin, Germany.

Studies in History and Philosophy of Science

|June 4, 2023

Summary

This summary is machine-generated.

Robotics is shifting towards a bionic, morphological paradigm, emphasizing body and environment over pure artificial intelligence. This paradigm change signifies a broader epistemological shift in control principles for future robotic systems.

Keywords:

Bionics Embodied cognition Morphological computation Morphology Principles of orientation and control Soft robotics

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Area of Science:

Robotics and Artificial Intelligence
Philosophy of Science
Bionics

Background:

Robotics historically focused on artificial intelligence (AI) and computational efficiency, leading to isolated and specialized systems.
This approach often overlooked the significance of the physical body, material properties, and environmental interactions in robotic control.

Purpose of the Study:

To introduce and define the 'morphological paradigm' in robotics.
To contrast the principles of this new paradigm with those of previous AI-centric models.
To explore the epistemological implications of this paradigm shift.

Main Methods:

Conceptual analysis of robotics paradigms.
Historical epistemology framework to trace changes in principles.
Comparative study of AI-driven vs. morphology-driven robotics.

Main Results:

Robotics is transitioning towards a bionic direction, integrating principles from biological and evolutionary systems.
The morphological paradigm highlights the crucial role of embodiment, material, environment, and interaction.
This shift represents a fundamental change in control principles and orientation.

Conclusions:

The morphological paradigm offers a new framework for robotics, moving beyond pure AI.
This shift has significant epistemological and potentially political implications for the future of robotics.
Further analysis is needed to explore the broader impact of this paradigm shift.