CMSC848J

Selected Topics in Information Processing; Cognitive Robotics

Prerequisites: Successful completion (minimum grade of C-) in CMSC351, CMSC420, and CMSC330, as well as one course from (MATH240, MATH341, MATH461); and permission of the CMNS-Computer Science department. This course is open to Master's or Doctoral students in Computer Science, Electrical and Computer Engineering, or Mechanical Engineering programs. Cognitive Robotics explores the application of human cognitive intelligence to the design and development of intelligent robots. The course delves into the fundamental principles of human cognitive intelligence and its integration with robotics and machine learning. Students will learn to develop cognitive robot learning architectures and implement them using simulators like Pybullet, NVIDA Issac-Gym, and Meta Habitat 2.0. Through engaging class projects, students will apply their newly acquired knowledge to solve novel, challenging and practically useful problems, enabling them to make meaningful contributions to the field. This unique opportunity to bridge the gap between cognitive science and robot learning that empowers students to develop smarter andand more capable robotic systems.

Sister Courses: CMSC848B, CMSC848C, CMSC848D, CMSC848E, CMSC848F, CMSC848G, CMSC848I, CMSC848K, CMSC848M, CMSC848N, CMSC848O, CMSC848P, CMSC848Q, CMSC848R, CMSC848T, CMSC848U, CMSC848W, CMSC848Z

Past Semesters

1 review
Average rating: 1.00

During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.

Average GPA of 4.00 between 14 students*

CMSC848J Grade Distribution+-05101520253035404550556065707580% of studentsABCDFWother
A: 7.14%
A+: 71.43%
other: 21.43%
* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.