SensiCut: Material-Aware Laser Cutting Using Speckle Sensing and Deep Learning
Mustafa Doga Dogan, Steven Vidal Acevedo Colon, Varnika Sinha, Kaan Akşit, Stefanie Mueller
Abstract
Laser cutter users face difficulties distinguishing between visually similar materials. This can lead to problems, such as using the wrong power/speed settings or accidentally cutting hazardous materials. To support users, we present SensiCut, an integrated material sensing platform for laser cutters. SensiCut enables material awareness beyond what users are able to see and reliably differentiates among similar-looking types. It achieves this by detecting materials’ surface structures using speckle sensing and deep learning.
Topics & Concepts
Speckle patternComputer scienceLaserDeep learningFace (sociological concept)Artificial intelligenceHazardous wasteComputer visionEngineeringOpticsSociologySocial sciencePhysicsWaste managementIndustrial Vision Systems and Defect DetectionTactile and Sensory InteractionsSurface Roughness and Optical Measurements