Perception is the ability to perceive, comprehend, and reason about the surrounding environment. Having a solid perception ability is crucial for autonomous robots to interact with the world. This course aims to offer a holistic understanding of fundamentals and the latest trends in robot perception. We will cover various topics, including sensing techniques, probabilistic state estimation, sensor fusion, SLAM, and learning algorithms. We will also discuss open problems and research frontiers in robot perception, such as perception in dynamic environments, open-world perception, embodiment, sim2real, uncertainty quantification, and perception with provable guarantees. The format of this course will be a mix of lectures, seminar-style discussions, and student presentations. The course will be heavily discussion and project-oriented. Students will be responsible for paper readings, class participation, and completing a hands-on project.

  • Time: Wednesday/Friday 2:00-3:15 pm
  • Location: Zoom
  • Discussion: Piazza
  • Paper review submission: Google Forms
  • Online lectures: The lectures will be live-streamed through Zoom, recorded, and made available on MediaSpace. Please log in with your institution account.
  • Contact: Students should ask all course-related questions on Piazza, where you will also find announcements. For external inquiries, personal matters, or in emergencies, you can email me at shenlong@illinois.edu (email title starts with [CS598]).