Course Description
This course covers basic theories and practices of autonomous robotics. Concepts of most components in modern robotics systems, including perception, representation, planning, control, actuation, and learning, will be covered in the lectures. The theoretical components will be included in the in-person lectures, weekly assignments, in-class quizzes, midterm, and final exams. For the practical components, the students will participate in two projects, one standardized project in the form of an in-class competition and one open-ended research project proposed by the students. Students will also present their developed robotics software and systems in class presentations and write project reports in the form of a conference paper.
This course is at the introductory undergraduate level and aims to introduce students to various topics in robotics through both theoretical knowledge and hands-on projects. After the students acquire a broad understanding of the field of robotics, they will be ready to dive deeper in any of the sub-fields, such as mapping and localization, motion planning, navigation, and manipulation. In addition to preparing students to future career in robotics, the course also hones the necessary skills for students to engage in future robotics research.
Learning Objective
There are three primary objectives for the course:
- To provide a broad survey of autonomous robotics systems and a deep understanding of their internal components;
- To develop hands-on skills to program simulated and physical robots working in the real world;
- To develop engineering and research skills specific to the field of robotics.
The course is designed to present a solid entry point to the field of robotics. It will provide the foundation to go on to take other upper division robotics courses. For those students with interest, it could possibly lead to subsequent research opportunities.
Course Content
This course comprises two main parts: (1) lectures, in which students learn basic concepts in robotics and (2) projects, in which students apply the learned concepts into practice. To study and implement these advanced topics in robotics, it is assumed that the students are familiar with the following:
- Basic programming skills in C/C++ and Python
- Algorithms and data structures
- Artificial intelligence
- Linear algebra and calculus
The lectures provides a broad introduction to autonomous robotics. Topics include:
- Robot motion: rigid body motion, forward kinematics, inverse kinematics, jacobian, and odometry
- Robot perception: common robot sensors, world representations, maps
- Planning: potential fields, different search methods, MDP
- State Estimation: localization, mapping, SLAM
- Controls: PID, state space, dynamics
- Learning: imitation learning and reinforcement learning