Rendering Forces With a Modular Cable System, Motors, and Brakes

📅 2026-03-09
📈 Citations: 0
Influential: 0
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🤖 AI Summary
This work proposes a modular hybrid-actuation haptic interface architecture to address the challenge of efficiently and flexibly rendering large-scale force feedback in reconfigurable multi-degree-of-freedom systems. The design integrates electric motors and unidirectional brakes within a single compact module, transmitting forces via cables to deliver both smooth active output (up to 6 N) and high-magnitude transient collision feedback (up to 186 N). By enabling arbitrary configuration and supporting high-fidelity force feedback across multiple degrees of freedom, the system significantly expands the dynamic range of haptic rendering while maintaining a compact form factor. This approach facilitates versatile deployment scenarios without compromising the richness or realism of the tactile experience.

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📝 Abstract
We describe the hardware design, force-rendering approach, and evaluation of a new reconfigurable haptic interface consisting of a network of hybrid motor-brake actuation modules that apply forces via cables. Each module contains both a motor and a brake, enabling it to smoothly render active forces up to 6 N using its motor and collision forces up to 186 N using its passive one-way brake. The modular design, meanwhile, allows the system to deliver rich haptic feedback in a flexible number of DoF and widely ranging configurations.
Problem

Research questions and friction points this paper is trying to address.

haptic interface
force rendering
modular system
cable-driven
motor-brake actuation
Innovation

Methods, ideas, or system contributions that make the work stand out.

modular haptic interface
hybrid motor-brake actuation
cable-driven force rendering
reconfigurable haptics
passive brake
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Jan Ulrich Bartels
Haptic Intelligence Department, Max-Planck Institute for Intelligent Systems, Heisenbergstraße 3, 70569 Stuttgart, Germany
A
Alexander Achberger
Visualisierungsinstitut (VISUS), Universität Stuttgart, Allmandring 19, 70569 Stuttgart, Germany
Katherine J. Kuchenbecker
Katherine J. Kuchenbecker
Max Planck Institute for Intelligent Systems
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Michael Sedlmair
Michael Sedlmair
Professor of Computer Science, University of Stuttgart
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