Haptic Data Quality Rating for Region Classification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Haptic exploration systems face challenges in ensuring that regions to be explored meet user expectations due to varying haptic data quality over time and space, caused by sensor limitations, memory, processing, and modeling complexities, leading to inefficient user experiences.
Innovation Solution
A method and controller that classify regions of interest by obtaining and quality rating haptic and visual data, modifying the data based on quality ratings to define regions of interest, thereby enhancing user experience by directing users to high-quality regions and avoiding low-quality ones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users physically explore regions using haptic actuators, then they can perceive properties of objects and surfaces, but the exploration time increases and user frustration increases due to varying haptic data quality
Solution Approach 1:
The system performs preliminary quality rating of haptic data for different regions before user exploration. Regions are pre-classified as high-quality or low-quality based on haptic data properties, allowing the system to guide users directly to high-quality regions and avoid low-quality ones, thereby reducing exploration time while ensuring reliable haptic experiences
Solution Approach 2:
The system provides feedback to users about region quality through visual indicators or guidance. By informing users which regions have high haptic data quality, the system enables users to make informed exploration decisions, reducing time spent on low-quality regions while maintaining high reliability of haptic interactions
2Loss of information
If haptic data is collected across all regions, then complete coverage is achieved, but processing complexity and energy consumption increase
Solution Approach 1:
Instead of uniformly processing haptic data across all regions, the system applies local quality assessment to identify and prioritize high-quality regions. Processing resources are concentrated on regions with high haptic data quality, while low-quality regions receive minimal or no processing, reducing overall energy consumption while preserving important haptic information
Solution Approach 2:
The system segments the exploration space into high-quality and low-quality regions based on haptic data properties. By dividing the region space and selectively processing only high-quality segments, the system maintains haptic data completeness for important regions while significantly reducing processing complexity and energy consumption
3Reliability
If haptic exploration covers all regions, then comprehensive understanding is achieved, but user frustration increases due to low-quality regions
Solution Approach 1:
The system performs preliminary identification and classification of high-quality regions before user exploration. By pre-marking high-quality regions and guiding users to these areas, the system ensures that users primarily interact with high-quality haptic data, improving user experience quality and reducing frustration from encountering low-quality regions
Data Source
AI summary
There is provided mechanisms for region of interest classifying a region. The region is represented by haptic data and visual data. The method is performed by a controller. The method comprises obtaining the haptic data and the visual data of the region. The method comprises quality rating the haptic data in at least part of the region based on at least one property of the haptic data and with respect to the visual data in the at least part of the region. The method comprises defining at least one region of interest in the region by modifying at least one of the haptic data and the visual data of the at least part of the region according to the quality rating of the haptic data, thereby region of interest classifying the region.