/ECE4078_Lab

For lab sessions of unit ECE4078 (Intelligent Robotics)

Primary LanguagePython

ECE4078 Lab

For lab sessions of unit ECE4078 (Intelligent Robotics)

Instructions

Please see each folder for every week's detailed instrcutions and getting-started codes.

For each lab milestone you will design and implement a key component of an integrated system. These components are then reused in later sessions and together they enable the robot to navigate through a terrain and locate targets accurately. For each milestone there is no single solution and you are encouraged to design your own approach to solve the task.

For discussion please join the Slack channel.

Format

Due to restricted access to the campus, you will be doing the implementation and testing mainly inside a simulator environment during the early weeks.

The lab sessions will start from week 2. Every week there are three sessions as listed below. Please check Moodle to see which one you are allocated to.

Starting from week 2, before each week's lab sessions, the instructions and getting-started codes will be made available to you in this GitHub repo. During each 3-hour lab session, you will get an overview of each week's objectives at the beginning of the lab session. At least one demonstrator will be reachable through Zoom to support you during the whole session. At the end of the lab session, the demonstrator will either show a sample solution or one of your solutions in the simulator or on the physical robot if possible, and you can view it through the shared screen and the webcam.

You will work together with two of your classmates as a group of three throughout the semester. Your mark will depend on your contribution to the group. A scaling factor between 0.9 and 1.1 will be calculated from your answers to the CATME team evaluation surveys. For M1 to M5, each milestone will amount to 4% of your course score. You should submit your codes on Moodle within a week of the milestone. Each group just need to make one submission. If multiple people from the same group have made multiple submissions, the latest submission before the deadline will be graded. The demonstrators will run your codes for evaluation. In the final demonstration / competition, the top 5 teams will be awarded a bonus 1% score. This final demo is also your final assessment (60% of your course score).

Acknowledgement

Part of the lab sessions are inspired by the Robotic Vision Summer School: https://www.roboticvision.org/rvss-2020/