Lily Behnke — accepted AI-conference papers

2026

Model-Agnostic Meta-Learning for Adaptive Gait Phase and Terrain Geometry Estimation With Wearable Soft Sensors

Zenan Zhu, Wenxi Chen, Pei-Chun Kao, Janelle P. Clark, Lily Behnke, Rebecca Kramer-Bottiglio +2

RA-L 2026

This letter presents a model-agnostic meta-learning (MAML) based framework for simultaneous and accurate estimation of human gait phase and terrain geometry using a small set of fabric-based wearable soft sensors, with efficient adaptation to unseen subjects and strong generalization across differen

Cited by 0 Source ↗Scholar ↗

2023

Dynamic Hand Proprioception via a Wearable Glove with Fabric Sensors

Lily Behnke, Lina Sanchez-Botero, William R. Johnson, Anjali Agrawala, Rebecca Kramer-Bottiglio

IROS 2023poster

Continuous enhancement in wearable technologies has led to several innovations in the healthcare, virtual reality, and robotics sectors. One form of wearable technology is wear-able sensors for kinematic measurements of human motion. However, measuring the kinematics of human movement is a challengi…

Cited by 2 Source ↗Scholar ↗