Thematic workshop

Deep Learning Methods in Aerial Robotics


3, 4 & 7 March 2022




Max Planck Institute for Intelligent Systems


Dr. Aamir Ahmad
Eric Price
Yu-Tang Liu


The registration is free but mandatory.


Day 1: Intro and Lectures (3rd March 10:00 – 14:00)

  • [Aamir] Introduction and overview of the workshop topic
  • Topic 1: [Eric] Exploiting (supervised) learning-based detectors for on-board, realtime localization and target tracking.  Lecture (1 hr): IROS 2018 paper    
  • Topic 2: [Rahul] MPC and reinforcement learning based formation control methods.   Lecture (1 hr + questions): IROS 2019 + IEEE-RAL 2020
  • Topic 3: [Yu Tang] Model-free residual reinforcement learning for blimp control.    Lecture (1 hr + questions) ICRA 2022 + IROS 2022

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