Two
of the above topics will be followed by a tutorial. Each tutorial will
be centered around a case-study which we will design. The tutorial
session will introduce the problem to the students, teach
how to address it, program etc.
Day 2: Tutorials (4th March 10:00 – 15:00)
[Eric] Tutorial (2 hr): How to deploy an existing deep neural network on a robotic platform
Requirements:
Desktop computer, Nvidia GPU or a powerful gaming laptop
Ubuntu 20 LTS, ROS Noetic (Python 3).
Cuda
PyTorch
Webcam (for realtime visual detection)
[Yu Tang]
Tutorial ( 2-3 hrs) Basic RL, setup of RL agent, intro to PPO how to
write a PPO agent + a robotic task example – navigate a turtlebot to a
position.
Requirements:
(same as Tutorial 2)
Day 3: Demo (7th March 10:00 to 14:00)
[Eric] Demo by students (2 hr): DNN-based detectors on quadcopter hardware
[Yu Tang] Demo by students of the robotic example
The students should present the results of their exercises, and lessons learned during the demo