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Robot Intelligence through Perception Lab






The Robot Intelligence through Perception Lab (RIPL) at TTI-Chicago develops intelligent, perceptually aware robots that are able to work effectively with and alongside people in unstructured environments.

RIPL is directed by Professor Matthew R. Walter. Our research focuses on advanced perception algorithms that endow robots with a rich awareness of their surroundings and the ability to interact safely and naturally with humans. We are particularly interested in algorithms that take as input multi-modal observations of a robot’s surround (e.g., laser range data, image streams, and speech) and infer properties of the objects, places, people, and events that comprise a robot’s environment.

We are looking for talented PhD students who are excited about computer vision, natural language understanding, and machine learning for robotics. If you are interested in joining us, consider applying to TTI-Chicago.

We are also looking to host students who are enthusiastic about robotics as part of TTI-Chicago’s Visiting Student Program, and encourage you to apply.


News

June 2026

We hosted the 2026 Midwest Robotics Workshop, which brought together 150+ students, postdocs, faculty, and industry researchers from across the midwest to network and showcase their work.

June 2026

Our paper Do You Know Where Your Camera Is? View-Invariant Policy Learning with Camera Conditioning received the Best Paper Award on Robot Learning at ICRA 2026!

January 2026

Our AAAI 2011 paper Understanding Natural Language Commands for Robotic Navigation and Mobile Manipulation received the AAAI Classic Paper Award!

September 2025

Jiading Fang received his diploma and is off to Waymo. Congrats!

June 2025

Congrats to Teddy Ayalew for his paper on learning task-agnostic reward functions from human videos and to Shengjie Lin for his paper on learning high-fidelity 3D models of articulated objects, both accepted to ICCV 2025!

Older news is available here.