Robotic Path Planning and Task Execution

Robotic Path Planning and Task Execution

This course is part of Introduction to Robotics with Webots Specialization

Instructor: Nikolaus Correll

What you'll learn

Use discrete planning techniques such as Dijkstra and A* to compute optimal robot trajectories.
Implement complex sequences of behaviors using behavior trees.
Plan and implement a complex robotic controller for autonomous mobile manipulation behavior.

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Assessments

9 assignments

Taught in English

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This course is part of the Introduction to Robotics with Webots Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 5 modules in this course

This course, which is the last and final course in the Introduction to Robotics with Webots specialization, will teach you basic approaches for planning robot trajectories and sequence their task execution. In "Robotic Path Planning and Task Execution", you will develop standard algorithms such as Breadth-First Search, Dijkstra's, A* and Rapidly Exploring Random Trees through guided exercises. You will implement Behavior Trees for task sequencing and experiment with a mobile manipulation robot "Tiago Steel".

It is recommended that you complete the first and second courses of this specialization, “Introduction to Robotics: Basic Behaviors” and "Robotic Mapping and Trajectory Generation" , before beginning this one. This course can be taken for academic credit as part of CU Boulder’s MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder

The first week in this course provides an introduction to path planning and presents a series of optimal algorithms for finding the shortest path on a graph that increase in complexity and efficiency. You will be introduced to various algorithms, including Bread-First Search to Dijkstra's and A*.

What's included

8 videos10 readings2 assignments1 discussion prompt

8 videosTotal 71 minutes

Introduction to the Specialization2 minutesPreview module
Meet the Instructor1 minute
Introduction to "Robotic Path Planning and Task Execution"0 minutes
Path Planning28 minutes
Graph Traversal using Breadth-First Search (BFS)7 minutes
Shortest Path on a Graph with BFS8 minutes
Shortest Path on a Grid with BFS8 minutes
From BFS to Dijkstra's on a Graph12 minutes

10 readingsTotal 130 minutes

Earn Academic Credit for your Work!10 minutes
Course Support10 minutes
Course Activities5 minutes
Why Planning?5 minutes
More on Graphs to Represent Computational Problems10 minutes
The Shortest Path Problem10 minutes
Graph Traversal15 minutes
Dijkstra's Algorithm25 minutes
A* - Dijkstra's with Heuristic15 minutes
Decompression - The Micro Mouse Competition25 minutes

2 assignmentsTotal 250 minutes

Planning on Graphs10 minutes
Implementing a Planner240 minutes

1 discussion promptTotal 10 minutes

Introduce Yourself!10 minutes

In this week, you will learn how to efficiently plan in non-grid worlds and in high-dimensional spaces.

What's included

1 video4 readings3 assignments

1 videoTotal 22 minutes

Randomized Planning and Collision Avoidance22 minutesPreview module

4 readingsTotal 60 minutes

Introduction to RRT10 minutes
The RRT Algorithm20 minutes
Collision Checking10 minutes
Improving Optimality and Speed of RRT20 minutes

3 assignmentsTotal 375 minutes

Improving RRT5 minutes
Hands-On: Implementing RRT220 minutes
Hands-On: Implement Line-Based Collision Checking150 minutes

This week introduces you to a new programming abstraction known as "Behavior Trees", which offers solutions to shortcomings of Finite State Machines and simple reactive controllers.

What's included

1 video4 readings2 assignments1 peer review

1 videoTotal 30 minutes

Behavior Trees30 minutesPreview module

4 readingsTotal 55 minutes

Introduction20 minutes
Parallel Nodes, Decorators and Blackboards15 minutes
Exchanging Data Within BTs - Blackboards10 minutes
Behavior Tree Libraries10 minutes

2 assignmentsTotal 190 minutes

Sequence and Selector nodes10 minutes
Hands-On: Implementing Behavior Trees180 minutes

1 peer reviewTotal 240 minutes

Mapping and Navigation with BTs240 minutes

This week you will learn how to extend a mobile base with a robotic arm and trigger the ability to grasp objects.

What's included

2 readings2 assignments

In this last week, you will complete a final project to demonstrate your knowledge of both this course and the entire specialization. It consists of implementing a complete mobile manipulation solution.