Reconfigurable Haptic Feedback: Comprehensive Design and Control Framework

Haptic interfaces enhance the virtual reality experience by emulating real‐world touch‐based interactions and delivering tactile feedback, while also supporting rehabilitation through interactive systems that speed up recovery. However, current haptic technologies are often built for specific uses, highlighting the need for generalized methods that allow for reconfigurable design and control. In this article, a comprehensive framework is introduced for the design and control of modular soft robotic devices. These modules can be combined in various configurations to develop a wide range of haptic devices capable of dynamically modifying their stiffness and shape to accommodate different applications, including providing haptic feedback in virtual environments and assisting individuals with hand rehabilitation needs. The design methodology of these modules is reported and two potential use cases are presented. Furthermore, it is demonstrated that how it is possible to intuitively control the modular soft robotic devices, monitor their state, and use limited sensing capability with machine learning models to enable interpretations of interactions with users and the surrounding environment.

Authors

Institutions

Publication Details

Journal
Advanced Intelligent Systems
Published
2025-06-16
DOI
https://doi.org/10.1002/aisy.202500142
Primary Topic
Teleoperation and Haptic Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Reconfigurable Haptic Feedback: Comprehensive Design and Control Framework

Jamie Kyujin Paik, Serhat Demirtas, Anke van Oosterhout, Rohit Kadungamparambil John
Advanced Intelligent Systems
Teleoperation and Haptic Systems
article

Reconfigurable Haptic Feedback: Comprehensive Design and Control Framework

Jamie Kyujin Paik, Serhat Demirtas, Anke van Oosterhout, Rohit Kadungamparambil John
article en

Abstract

Haptic interfaces enhance the virtual reality experience by emulating real‐world touch‐based interactions and delivering tactile feedback, while also supporting rehabilitation through interactive systems that speed up recovery. However, current haptic technologies are often built for specific uses, highlighting the need for generalized methods that allow for reconfigurable design and control. In this article, a comprehensive framework is introduced for the design and control of modular soft robotic devices. These modules can be combined in various configurations to develop a wide range of haptic devices capable of dynamically modifying their stiffness and shape to accommodate different applications, including providing haptic feedback in virtual environments and assisting individuals with hand rehabilitation needs. The design methodology of these modules is reported and two potential use cases are presented. Furthermore, it is demonstrated that how it is possible to intuitively control the modular soft robotic devices, monitor their state, and use limited sensing capability with machine learning models to enable interpretations of interactions with users and the surrounding environment.

Advanced Intelligent SystemsVol. 7(9)
École Polytechnique Fédérale de Lausanne (CH), Eindhoven University of Technology (NL)
European Commission, Technische Universiteit Eindhoven
Openalex Percentile: Top 87%
Teleoperation and Haptic Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Reconfigurable Haptic Feedback: Comprehensive Design and Control Framework — Jamie Kyujin Paik, Serhat Demirtas, et al. · Advanced Intelligent Systems (2025) | TGRS Research Map | TGRS