CAREER: Understanding Complex Touch Sensing and Perception Through a Multimodal Electronic Skin for Human-Intelligent Machine Interfaces

The sense of touch is fundamental to how humans interact with the world. It enables detection of useful qualities such as force, temperature, and wetness that are essential for object manipulation and safe interaction with the environment. Human-operated robots have the potential to enhance human presence in extreme, difficult, and resource-limited environments. However, creating robotic systems that mimic the rich tactile sensing capabilities of human skin remains a challenge, limiting the ability of human users to perceive and respond through remotely operated robots. This CAREER project aims to address that gap by developing a biologically inspired electronic skin for robotic manipulators that can simultaneously detect multiple touch qualities and enable delivery of those sensations to a human operator. The research explores how sensing multiple touch qualities impacts the ability of a human to interact with and control a robot manipulator. Improving the quality of tactile information that can be detected and transmitted through a robot manipulator will help advance systems such as those used in disaster response, deep-sea exploration, and prostheses. Additionally, this project will support the development of an educational toolkit for designing bioinspired touch sensors as well as hands-on educational materials in bioinspired engineering for students across the country. The goal of this CAREER project is to develop a multimodal tactile sensing electronic skin that enables enhanced touch feedback to a human user for enhancing sensorimotor function through a robotic system. Achieving this goal requires scientific understanding of how nuanced tactile information can be detected and processed through bioinspired design. The research team will combine biological behaviors of tactile sensing and signal representation with conductive sensing elements to create a multimodal electronic skin and conduct experiments that evaluate the impact of these tactile inputs on enabling extraction of object information and a user’s ability to perform sensorimotor tasks through a robotic manipulator while receiving tactile feedback. Insights from these experiments will contribute to our understanding of dynamic bidirectional interactions, specifically sensorimotor function and behavior with artificial tactile experiences, for enhancing the functionality and operation of human-intelligent machine interfaces. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.