Automated hyperspectral and tactile material identification system
Advanced system integrating hyperspectral imaging and tactile sensors for accurate material identification and segregation. Ideal for recycling and waste management applications, enhancing accuracy through combined sensory data and machine learning.
Overview
The proposed solution is an innovative system that combines hyperspectral imaging and tactile sensor technology to accurately identify and segregate materials, particularly in recycling and waste management applications. By leveraging the complementary strengths of both sensory modalities, this system provides a holistic approach to material classification, overcoming the limitations of traditional methods. The hyperspectral vision module rapidly screens materials, while the tactile sensor confirms material types through touch-based signals. This mimics the human strategy of "look and feel," leading to more accurate segregation of scrap materials.
Technical specifications
Key features:
- Hyperspectral Imaging: Operates in the VNIR/SWIR range (400–2500 nm) to recognize materials by their spectral signatures, effectively identifying non-metals like plastics and rubbers.
- Tactile Sensors: Utilize piezoelectric or triboelectric touch technology to classify materials based on mechanical impedance changes upon contact.
- Machine Learning Integration: Enhances material identification accuracy by learning and recognizing patterns, potentially reducing reliance on touch sensing in the future.
- Dual-Sensor Synchronization: Combines data from both hyperspectral and tactile sensors for improved material classification, addressing issues related to surface anomalies and contamination.
Technology readiness level
This system is currently at a Technology Readiness Level (TRL) of 5. It has been validated in relevant environments and is ready for further development and testing to optimize and expand its application in industrial settings.
About Northeastern University
Northeastern University is a private, comprehensive R1 research university based in Boston with a global campus network. Its century-old cooperative education model integrates full-time, paid placements with academic study, enabling companies to access vetted talent and long-term pipelines worldwide. Industry collaboration is supported by a suburban innovation campus offering test beds, secure labs, and fee-for-use core facilities, alongside co-located partner spaces. The university attracts competitive federal research funding from agencies such as the NSF and NIH. A dedicated technology transfer office streamlines IP, licensing, and startup formation for corporate partnerships.
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