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Control a Robot's Navigation Through a Warehouse
Noé Fontana
Noé Fontana
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Control a Robot's Navigation Through a Warehouse

Use Python to plan and control paths for an autonomous mobile robot used to unload containers in a warehouse.

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Tuesdays
 at
12:00
P.M.
 ET /
9:00
A.M.
PT
8 weeks, 2-3 hours per week
Intermediate
No experience required
No experience required
Some experience required
Degree and experience required

Description

Increasing efficiency of robot movements is a constant battle that people in Mechatronics are fighting daily. In this Build Project, you’ll wear the hat of Robotics Mechatronics Engineer and enable a robot to navigate autonomously at dock doors in a simulated warehouse. Under the supervision of an experienced Build Fellow, you'll use Python to implement trajectories planning and following algorithms to allow an autonomous mobile robot to navigate. You’ll become familiar with the state-of-the-art ROS2 (Robot Operating System 2) and testing in simulation. The implemented solution will reflect current industry best practices.

Session timeline

  • Applications open
    June 24, 2024
  • Application deadline
    July 21, 2024
  • Project start date
    Week of July 8, 2024
    Week of
    August 5, 2024
  • Project end date
    Week of

What you will learn

  • Leverage ROS2 to implement a multi-process navigation system
  • Implement a basic 2D path planner
  • Learn how to generate a time-parametrized trajectory from a 2D Path
  • Implement a controller allowing the mobile robots to track a trajectory
  • Visualize your results using the gazebo simulator and rviz2
Build Projects are 8-week experiences that operate on a rolling basis. Selected participants engage in weekly live workshops with a Build Fellow and 2-15 other students.

Project workshops

1
Introductions
2
2D Path Planning
3
Planning in Simulation
4
2D Trajectory Planning
5
Control the Robot
6
Motion Planning and Control
7
Testing in Simulation
8
Presentations

Prerequisites

  • Curiosity, willingness to learn, and proactive communication.
  • Intermediate knowledge of Python for scientific computing: you should have already contributed to a project with multiple files (i.e. be used to importing objects from other packages, modules or files), you should be able to use NumPy to perform array operations
  • Having taken an introductory class covering either robotics, control theory, mechanics or physics: you should be comfortable with the notion of derivatives (especially time derivatives)
  • Being comfortable with 2D geometry and the notion of frame: you should be comfortable using trigonometry in 2D
  • Interest in robotics and autonomous navigation, being keen to dive into the complexity of robotics software systems, being interested in working with complex industrial-grade solutions such as ROS2 and docker.  

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About the expert
Noé Fontana

Noé Fontana

Mechatronics Engineering
Build Fellow
Open Avenues Foundation
Open Avenues Foundation
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Noé
's Linkedin

Hi everyone! I am Noé Fontana, a Mechatronics Engineering Fellow at Open Avenues leading mechatronics and robotics projects. I am also an Applied AI Researcher at Pickle Robot where I solve Computer Vision and Perception problems. Before that, I worked on Navigation, Motion Planning and Control for autonomous Vehicles. I am excited to build with you on projects at the intersection of mechatronics, software developments and robotics.

I did my undergraduate and graduate studies in France, studying a broad range of subjects and culminating in Masters in Mechatronics Engineering and Applied Mathematics. Professionnally, I am enthusiastic about applying mathematics to problems involving physical systems.

Outside of work, some activities I enjoy are hiking, dancing and listening to live music.

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