Semester.ly

Johns Hopkins University | EN.600.636

Algorithms for Sensor-Based Robotics

3.0

credits

Average Course Rating

(4.08)

Graduate level version of EN.600.436 (see description above). Formerly EN.600.436. Students may receive credit for only one of EN.600.336, EN.600.436 or EN.600.636. Recommended Course Background: EN.600.226, AS.110.106, and Prob/Stat.

Spring 2013

(4.25)

Spring 2014

(4.05)

Spring 2015

(3.93)

Spring 2013

Professor: Gregory Hager

(4.25)

The best aspects of the course included the programming assignments and the projects, because students found them very applicable to the real-world. The worst aspects of the course included the lectures and the lecture slides. The lecture slides were not very easy for students to navigate through and the homework assignments were chal enging for students who lacked a strong background in the fundamentals. The course would improve if the lecture slides and the course materials were clearer and better organized. Prospective students should be prepared for some exciting assignments and should have some background in Programming and Fundamentals.

Spring 2014

Professor: Gregory Hager

(4.05)

During this course, students learned about the different methods of planning. The material was interesting and tangible, and the instructor was very responsive to questions. However, homework assignments were not graded until the end of the semester and many students disliked the assignments. In class, tons of algorithms were covered, but they were barely present on homework assignments. Suggestions for improvement include: better and timelier feedback, new homework assignments, more explanation of ROS, and focus on some structured programming. Prospective students should be proficient in C++.

Spring 2015

Professor: Gregory Hager, Simon Leonard

(3.93)

The best aspects of the course included the breadth of topics covered as well as the hands-on, interactive assignments. A few students claimed that the final exam was an ineffective way to evaluate students and that a project would have better served the goals of the class as wel as student interests. Others felt that at times the professors mentioned and applied algorithm concepts that were unfamiliar to non-computer science students. Suggestions for improvement included spending more time explaining the algorithms, and investigating SLAM theory in greater depth. Prospective students may benefit from a background in C++, ROS, and probability. 94