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A biologically inspired active compliant joint using local positive velocity feedback (LPVF).

Axel Schneider¹, Holk Cruse, Josef Schmitz

¹Department of Biological Cybernetics, Faculty of Biology, University of Bielefeld, Germany. axel.schneider@uni-bielefeld.de

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|December 22, 2005

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Researchers developed a new positive feedback joint inspired by arthropod locomotion for compliant motion tasks. This decentralized system, using local positive velocity feedback (LPVF) controllers, enables robots to perform tasks like turning a crank.

Area of Science:

Robotics
Biomimetics
Control Systems Engineering

Background:

Arthropod locomotion utilizes positive feedback mechanisms in its control systems.
Compliant motion is crucial for robots interacting with unstructured environments.
Decentralized control and embodiment offer advantages in robotic system design.

Purpose of the Study:

To introduce a novel positive feedback-driven joint for compliant motion tasks.
To explore the properties of local positive velocity feedback (LPVF) controllers for motion generation.
To demonstrate the application of these controllers in a real-world robotic scenario.

Main Methods:

Construction of two passive compliant joint prototypes.
Development and analysis of three local positive velocity feedback (LPVF) controllers.

Related Experiment Videos

Implementation of an undelayed dLPVF controller for a planar manipulator performing a crank-turning task.

Main Results:

The proposed joints exhibit passive compliance, suitable for sensitive tasks.
LPVF controllers demonstrate effective motion generation in closed kinematic chains.
The undelayed dLPVF controller successfully controlled a compliant manipulator in a crank-turning task.

Conclusions:

Positive feedback-driven joints offer a viable approach for compliant robotic motion.
Decentralized LPVF control aligns with embodiment principles, allowing systems to reveal their nature through interaction.
This research contributes to the development of more adaptable and responsive robotic systems.