Stanford AA289/ENGR319 - Robotics and Autonomous Systems Seminar - Stanford Seminar - Using Data for Increased Realism with Haptic Modeling and Devices

Heather Culbertson, USC May 20, 2022 The haptic (touch) sensations felt when interacting with the physical world create a rich and varied impression of objects and their environment. Humans can discover a significant amount of information through touch with their environment, allowing them to assess object properties and qualities, dexterously handle objects, and communicate social cues and emotions. Humans are spending significantly more time in the digital world, however, and are increasingly interacting with people and objects through a digital medium. Unfortunately, digital interactions remain unsatisfying and limited, representing the human as having only two sensory inputs: visual and auditory. This talk will focus on methods for building haptic and multimodal models that can be used to create realistic virtual interactions in mobile applications and in VR. I will discuss data-driven modeling methods that involve recording force, vibration, and sounds data from direct interactions with the physical objects. I will compare this to new methods using machine learning to generate and tune haptic models using human preferences. More about the speaker: https://heatherculbertson.wixsite.com/home Learn more about Stanford's Robotics and Autonomous Systems Graduate Program: https://online.stanford.edu/programs/robotics-and-autonomous-systems-graduate-program 0:00 Introduction 2:31 HAPTOGRAPHY 3:15 HAPTIC RECORDING DEVICE 6:23 HAPTIC TEXTURE RECORDING PROCEDURE 6:43 RECORDED DATA 10:25 SOUND MODELING 13:04 SYNTHESIZING A NEW SOUND OUTPUT 17:05 OLD WAY: HAND TUNING MODELS 17:42 NEW WAY: PREFERENCE-DRIVEN TUNING 19:38 HAPTIC MODELS: FRICTION AND TEXTURE 20:23 TEXTURE GENERATIVE MODEL 21:10 PREFERENCE-DRIVEN MODELING FRAMEWORK 23:19 TUNING TEXTURE MODELS 24:58 REALISM OF MODELS 31:37 ENCOUNTERED-TYPE HAPTIC DEVICE 35:56 COMPARING TO TRADITIONAL RENDERING METHODS 40:17 RESULTS: REALISM 42:18 DATA-DRIVEN SOCIAL TOUCH 43:01 EMOTION ACCURACY 43:34 REAL-TIME TRANSMISSION OF TOUCH 46:12 STUDYING EFFECT OF SPEED ON EMOTION