PhD candidate Michelle A. Lee from the Stanford AI Lab won the best paper award at ICRA 2019 with her work “Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks”. You can read the paper on arxiv here.
Audrow Nash was there to capture her pitch.
And here’s the official video about the work.
Full reference
Lee, Michelle A., Yuke Zhu, Krishnan Srinivasan, Parth Shah, Silvio Savarese, Li Fei-Fei, Animesh Garg, and Jeannette Bohg. “Making sense of vision and touch: Self-supervised learning of multimodal representations for contact-rich tasks.” arXiv preprint arXiv:1810.10191 (2018).
In this episode, Lauren Klein interviews Michal Luria, a PhD candidate in the Human-Computer Interaction Institute at Carnegie Mellon University, about research that explores the boundaries of Human-Robot Interaction. Michal draws inspiration from the Medieval Times for her project to test how historical automata can inform modern robotics. She also discusses her work with cathartic objects to support emotional release.
Michal Luria
Michal Luria is a PhD candidate in the Human-Computer Interaction Institute at Carnegie Mellon University, advised by Professors Jodi Forlizzi and John Zimmerman. Michal’s research centers on exploring alternative ways for humans to interact with agents and social robots. Prior to her PhD, Michal studied Interactive Communication at the Interdisciplinary Center Herzliya in Israel.
Links
In this episode of Robots in Depth, Per Sjöborg speaks with Federico Pecora about AI and robotics. Federico Pecora is Associate Professor in Computer Science at the Center for Applied Autonomous Sensor Systems at Örebro University, Sweden.