Alexis E. Block received her bachelors degree in Mechanical Engineering and Applied Mechanics and two minors in Math and Engineering Entrepreneurship in 2016 from the University of Pennsylvania. The following year, 2017, she received her masters degree in Robotics, also from the University of Pennsylvania.
Alexis E. Block's doctoral research, HuggieBot, focuses on social-physical human-robot interaction. She is a Center for Learning Systems (CLS) Doctoral Fellow. Block currently works in the Computer Science Department at ETH Zürich. Her two ETH co-advisors are Roger Gassert (Rehabilitation Engineering Laboratory) and Otmar Hilliges (Advanced Interactive Technologies). She is looking forward to rejoining her primary doctoral advisor, Dr. Katherine J. Kuchenbecker, and the rest of the Haptic Intelligence Department in January 2020.
Block was named a 2018 HRI Pioneer, and elected a General Chair for HRI Pioneers 2019. She also co-founded the MPI Athena Group to support women in science, technology, engineering, mathematics, robotics, intelligent systems and related fields.
Alexis Block's research has been featured on several radio programs:
16 June 2018, NPR: HuggieBot was the first question discussed during the Panel Questions segment of NPR's "Wait Wait Don't Tell Me" program.
15 June 2018, Paul Ross Show on TalkRadio: Alexis had an 11 minute interview with Paul Ross. It aired between 4:30-5:00 and begins about 8 minutes in.
Block's research has been featured in several news articles:
Work-in-progress paper (2 pages) presented at the IEEE World Haptics Conference (WHC), Tokyo, Japan, July 2019 (misc)
During hugs, humans naturally provide and intuit subtle non-verbal cues that signify the strength and duration of an exchanged hug. Personal preferences for this close interaction may vary greatly between people; robots do not currently have the abilities to perceive or understand these preferences. This work-in-progress paper discusses designing, building, and testing a novel inflatable torso that can simultaneously soften a robot and act as a tactile sensor to enable more natural and responsive hugging. Using PVC vinyl, a microphone, and a barometric pressure sensor, we created a small test chamber to demonstrate a proof of concept for the full torso. While contacting the chamber in several ways common in hugs (pat, squeeze, scratch, and rub), we recorded data from the two sensors. The preliminary results suggest that the complementary haptic sensing channels allow us to detect coarse and fine contacts typically experienced during hugs, regardless of user hand placement.
International Journal of Social Robotics, 11(1):49-64, October 2018 (article)
Hugs are one of the first forms of contact and affection humans experience. Due to their prevalence and health benefits, roboticists are naturally interested in having robots one day hug humans as seamlessly as humans hug other humans. This project's purpose is to evaluate human responses to different robot physical characteristics and hugging behaviors. Specifically, we aim to test the hypothesis that a soft, warm, touch-sensitive PR2 humanoid robot can provide humans with satisfying hugs by matching both their hugging pressure and their hugging duration. Thirty relatively young and rather technical participants experienced and evaluated twelve hugs with the robot, divided into three randomly ordered trials that focused on physical robot characteristics (single factor, three levels) and nine randomly ordered trials with low, medium, and high hug pressure and duration (two factors, three levels each). Analysis of the results showed that people significantly prefer soft, warm hugs over hard, cold hugs. Furthermore, users prefer hugs that physically squeeze them and release immediately when they are ready for the hug to end. Taking part in the experiment also significantly increased positive user opinions of robots and robot use.
Workshop paper (2 pages) presented at the HRI Pioneers Workshop, Chicago, USA, March 2018 (misc)
Hugs are one of the first forms of contact and affection humans experience. Due to their prevalence and health benefits, we want to enable robots to safely hug humans. This research strives to create and study a high fidelity robotic system that provides emotional support to people through hugs. This paper outlines our previous work evaluating human responses to a prototype’s physical and behavioral characteristics, and then it lays out our ongoing and future work.
Workshop Paper (2 pages) presented at the RO-MAN Workshop on Social Interaction and Multimodal Expression for Socially Intelligent Robots, Lisbon, Portugal, August 2017 (misc)
A hug is one of the most basic ways humans can express affection. As hugs are so common, a natural progression of robot development is to have robots one day hug humans as seamlessly as these intimate human-human interactions occur. This project’s purpose is to evaluate human responses to different robot physical characteristics and hugging behaviors. Specifically, we aim to test the hypothesis that a warm, soft, touch-sensitive PR2 humanoid robot can provide humans with satisfying hugs by matching both their hugging pressure and their hugging duration. Thirty participants experienced and evaluated twelve hugs with the robot, divided into three randomly ordered trials that focused on physical robot char- acteristics and nine randomly ordered trials with varied hug pressure and duration. We found that people prefer soft, warm hugs over hard, cold hugs. Furthermore, users prefer hugs that physically squeeze them and release immediately when they are ready for the hug to end.
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems