Planning Workshop
Presented by ERL
Why Planning?
Every robot’s journey eventually faces a crucial challenge: How does a machine choose its actions? Planning is the process that transforms a robot’s understanding of its environment into purposeful decisions. By evaluating options and sequencing tasks, planning enables robots to move beyond simple reactions toward deliberate, goal‑driven behavior. Eventually when combined with mapping and localization, these strategies evolve into SLAM (Simultaneous Localization and Mapping).
Goal
This workshop series aims to introduce basic SLAM robotics concepts to students. Our workshop targets all experience levels and intends to get students more interested in intelligent systems.
Workshop Logistics
Date: TBD
Time: TBD
Location: TBD
Itinerary
5:05 - 5:20: Introduction to ERL
5:20 - 6:35: Planning Algorithms Presentation and Activities
6:35 - 6:50: TBD
6:50 - 7:00: Live Robot Demo and Food
Workshop Prerequisites
To run the mapping simulation on your own laptop (optional), please download the zip file corresponding to your operating system at the bottom of the page. Then, follow the instructions on the README.
What You Will Make
In this workshop, students will learn and practice implementing three major robot path planning algorithms — Dijkstra, A*, and RRT — each designed to help a robot move from a start point to a goal point while avoiding obstacles.
Students will complete guided Colab notebooks for each algorithm, working through fill‑in‑the‑blank coding exercises and progressively building the logic behind each planner. After finishing the RRT notebook, they will move into an Algorithm Comparison exercise, where they directly compare Dijkstra, A*, and RRT on different planning scenarios. Students will discuss trade‑offs, choose which algorithm fits best for each case, and explain their reasoning.
Finally, a demo will be shown to illustrate how these algorithms can be applied in practice. This closing activity will tie the coding work to real‑world decision‑making and help students connect the theory of path planning to autonomous navigation challenges faced by actual robots.
Notebooks (During Workshop)
- Dijkstra's Algorithm: link to notebook
- A* : link to notebook
- RRT : link to notebook
Solution to the Dijkstra's Notebook
Solution to A* Notebook
Solution to RRT Notebook
Workshop Slides
Key Concepts We'll Explore
- Control
- Pure Pursuit
- Planning
- Dijkstra’s and A* Algorithm
- Rapidly Exploring Random Tree (RRT)
- RRT*
Why should I go to this workshop?
Going to this workshop enables you to get further experience and knowledge in robotics. Robotics is a field that is growing rapidly, and there are many applications of robotics in the real world including:
- Manufacturing
- Healthcare
- Agriculture
- Security
- Construction
- ... and more!
Gaining experience in robotics also can help you gain experience in a wide variety of topics including computer vision, machine learning, actuators, autonomous vehicles, and more! The possibilities are near limitless in robotics.
