Robotic Path Planning and Task Execution (Coursera)

Robotic Path Planning and Task Execution (Coursera)

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".

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

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 is part of the Introduction to Robotics with Webots Specialization.

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.

Syllabus

Path Planning
Module 1
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*.

Collision Checking and Randomized Algorithms
Module 2
In this week, you will learn how to efficiently plan in non-grid worlds and in high-dimensional spaces.

Behavior Trees
Module 3
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.

Basic Manipulation
Module 4
This week you will learn how to extend a mobile base with a robotic arm and trigger the ability to grasp objects.

Final Project for This Specialization
Module 5
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.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Foundations of Data Science: K-Means Clustering in Python (Coursera) Coursera
University of London,Goldsmiths, University of London

Foundations of Data Science: K-Means Clustering in Python (Coursera)

This MOOC, designed by an academic team from Goldsmiths, University of London, will quickly introduce you to the core concepts of Data Science to prepare you for intermediate and advanced Data Science courses. It focuses on the basic mathematics, statistics and programming skills that are necessary for typical data analysis tasks.

Sep 7th 2026
5-12 Weeks
Estructuras de datos de Python (Coursera) Coursera
University of Michigan

Estructuras de datos de Python (Coursera)

Este curso presentará las estructuras de datos básicas del lenguaje de programación Python. Veremos los conceptos básicos de la programación de procedimientos y exploraremos cómo podemos usar las estructuras de datos integrados de Python, como listas, diccionarios y tuplas, para realizar análisis de datos cada vez más complejos. Este curso abarcará los capítulos 6 a 10 del libro de texto “Python para todos”. Este curso cubre Python 3.

Sep 14th 2026
5-12 Weeks
Data Processing Using Python (Coursera) Coursera
Nanjing University

Data Processing Using Python (Coursera)

This course is mainly for non-computer majors. It starts with the basic syntax of Python, to how to acquire data in Python locally and from network, to how to present data, then to how to conduct basic and advanced statistic analysis and visualization of data, and finally to how to design a simple GUI to present and process data, advancing level by level.

Sep 14th 2026
5-12 Weeks
Programming for Everybody (Getting Started with Python) (Coursera) Coursera
University of Michigan

Programming for Everybody (Getting Started with Python) (Coursera)

This course aims to teach everyone the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python. The course has no pre-requisites and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course.

Sep 7th 2026
5-12 Weeks
An Introduction to Interactive Programming in Python (Part 1) (Coursera) Coursera
Rice University

An Introduction to Interactive Programming in Python (Part 1) (Coursera)

This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera. To make learning Python easy, we have developed a new browser-based programming environment that makes developing interactive applications in Python simple.

Sep 7th 2026
5-12 Weeks
Applied Text Mining in Python (Coursera) Coursera
University of Michigan

Applied Text Mining in Python (Coursera)

This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).

Sep 14th 2026
4 Weeks
An Introduction to Interactive Programming in Python (Part 2) (Coursera) Coursera
Rice University

An Introduction to Interactive Programming in Python (Part 2) (Coursera)

This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera. To make learning Python easy, we have developed a new browser-based programming environment that makes developing interactive applications in Python simple.

Sep 7th 2026
4 Weeks
Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python (Coursera) Coursera
Ludwig-Maximilians-Universität München

Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python (Coursera)

Interested in learning how to solve partial differential equations with numerical methods and how to turn them into python codes? This course provides you with a basic introduction how to apply methods like the finite-difference method, the pseudospectral method, the linear and spectral element method to the 1D (or 2D) scalar wave equation.

Sep 7th 2026
5-12 Weeks