Robot Vision and Learning Lab

Welcome

Welcome to the Robot Vision and Learning (RVL) lab. We are part of the Computer Science department at the University of Toronto, the MCS department at UTM, the UofT Robotics Institute, and Vector Institute. The group is led by Prof. Florian Shkurti, and consists of students with backgrounds in robotics, machine learning, computer vision, engineering, control theory, or physics. We develop methods that enable robots to perceive, reason, and act effectively and safely, particularly in dynamic environments and alongside humans. Application areas include robotic manipulation, chemistry/biology lab automation, and field robotics for environmental monitoring.

Research Themes

• reasoning and learning for robotics
• safe robot learning
• 3D vision & generative models for simulation

Application Areas

• robotics for chemistry and biology lab automation
• field robotics for environmental monitoring

News

• Nov 2025: Wei-Cheng's paper on leveraging video models for policy evaluation in robotic manipulation is out on arxiv.
• Sep 2025: Two papers accepted at NeurIPS'25, one on off-policy evaluation with diffusion guidance and another on multi-task failure detection in VLAs. Both papers were collaborations with TRI. Congratulations to Hossein Goli, Mike Gimelfarb, Qiao Gu, Yuanliang Ju, and the rest of the team!
• Sep 2025: One paper accepted at Nature Computational Science on digital twins for chemistry labs and another paper (viewpoint) accepted to Science Robotics. Congratulations to Kourosh Darvish and all the collaborators!
• Sep 2025: New PhD students Hossein Goli, Brandon Huang, Zhengyang Liang, Yuanliang Ju and new postdoc Giseung Park join the lab. Welcome to RVL!
• Aug 2025: Two papers accepted at CoRL'25, one on learning policies for generalizable placement and another on test-time adaptation of VLMs for Bayesian search. Congratulations to Yuchi Zhao, Derek Tan, and the rest of the co-authors!
• Jun 2025: Congratulations to PhD student Qiao Gu, who started another internship at Meta.
• Jan 2025: Our paper SICNav on bilevel optimization for safe crowd navigation was accepted to Transactions of Robotics. Its followup, SICNav-Diffusion was accepted at Robotics and Automation Letters. A large-scale field deployment of the method was published at the ICRA'25 field robotics workshop. Congratulations to Sepehr Samavi, Anthony Lem, Garvish Bhoutani and to the rest of the co-authors!
• Jan 2025: Yewon Lee's paper Stein Task and Motion Planning was accepted to Robotics and Automation Letters. Congratulations to Yewon Lee, Philip Huang, and Andrew Li and the rest of the team!
• Oct 2024: Florian receives the AI2050 Early Researcher Fellowship from Schmidt Sciences.
• Sep 2024: New graduate students Quentin Clark, Nathan De Lara, James Ross, and Daniel Hocevar join the lab. Welcome to RVL!