Robot Learning and Wearable Interfaces in Pursuit of Robotic Caregivers
Assistant Professor, The Robotics Institute, Carnegie Mellon University
April 2, 2026 (Thu)
1:30-2:30pm
Stanford Robotics Center (Packard Electrical Engineering Bldg, basement)
Abstract:
Designing safe and reliable robotic assistance for caregiving is a grand challenge in robotics. A sixth of the United States population is over the age of 65 and more than 1 in 4 (over 70 million) adults in the United States reported having a disability in 2022. Robotic caregivers could positively benefit society; yet, physical robotic assistance presents several challenges and open research questions relating to autonomous control, multimodal sensing and learning, and accessible interfaces. In this talk, I will present recent techniques and technology that my group has developed towards addressing core challenges in robotic caregiving. First, I will introduce inertial and high-density electromyography (HDEMG) wearable interfaces that enable people with severe loss of motor and hand function (due to spinal cord injury or neurodegenerative diseases) to embody physically assistive mobile manipulators in their home. I will then present our recent work in robot learning, including online and offline policy learning, to perform complex manipulation in assistive scenarios. This includes learning reward functions and robot control policies from real-world videos of assistance, a framework for integrating LLMs into physically assistive robots, and new opportunities presented by generative simulation.
Bio:
Zackory Erickson is an Assistant Professor in The Robotics Institute at Carnegie Mellon University, where he leads the Robotic Caregiving and Human Interaction (RCHI) Lab. His research focuses on developing new robot learning, mobile manipulation, and multimodal sensing methods for physical human-robot interaction and healthcare. Zackory received his PhD in Robotics from Georgia Tech. He and his students have received the Best Paper Award at HRI 2024, Best Paper nomination at HRI 2025, Best Student Paper Award at ICORR 2019, and a Best Paper in Service Robotics finalist at ICRA 2019.