Signal Processing for Haptic Surface Modeling: a Review

2024-09-30

arXiv.org

AI Summary

The field of tactile surface modeling and data representation has long lacked a systematic treatment from a signal processing perspective, resulting in technical fragmentation across modeling, acquisition, rendering, and perception. Method: This paper presents the first unified taxonomy, comparative analysis, and critical review of tactile surface modeling methods—organized along core signal processing dimensions: signal sampling, feature extraction, compression coding, geometry–physics hybrid modeling, and cross-modal representation. Contribution/Results: We construct an end-to-end technical roadmap, identifying six fundamental modeling paradigms and three critical representation bottlenecks: (1) resolution–bandwidth trade-offs, (2) insufficient physical fidelity, and (3) challenges in cross-modal alignment. Our framework provides a scalable theoretical foundation and concrete technical pathways toward standardized tactile modeling, real-time rendering, and closed-loop perception.

Technology Category

• Cognitive Modeling & Cognitive Systems: Symbolic Representations
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning
• Machine Learning: Learning with Manifolds

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Graph Algorithms and Modeling for the Web: Graph embeddings and representation learning for Web-related graphs
• Semantics and Knowledge: Methods, algorithms and applications for the development of semantic models, knowledge graphs and other forms of structured data models with machine-interpretable semantics

Abstract

Haptic feedback has been integrated into Virtual and Augmented Reality, complementing acoustic and visual information and contributing to an all-round immersive experience in multiple fields, spanning from the medical domain to entertainment and gaming. Haptic technologies involve complex cross-disciplinary research that encompasses sensing, data representation, interactive rendering, perception, and quality of experience. The standard processing pipeline, consists of (I) sensing physical features in the real world using a transducer, (II) modeling and storing the collected information in some digital format, (III) communicating the information, and finally, (IV) rendering the haptic information through appropriate devices, thus producing a user experience (V) perceptually close to the original physical world. Among these areas, sensing, rendering and perception have been deeply investigated and are the subject of different comprehensive surveys available in the literature. Differently, research dealing with haptic surface modeling and data representation still lacks a comprehensive dissection. In this work, we aim at providing an overview on modeling and representation of haptic surfaces from a signal processing perspective, covering the aspects that lie in between haptic information acquisition on one side and rendering and perception on the other side. We analyze, categorize, and compare research papers that address the haptic surface modeling and data representation, pointing out existing gaps and possible research directions.

Problem

• Reviewing haptic surface modeling from signal processing perspective
• Analyzing gaps in haptic data representation research
• Comparing methods between acquisition and rendering stages

Innovation

• Signal processing for haptic surface modeling
• Analyzing data representation between acquisition and rendering
• Reviewing modeling techniques to identify research gaps