Coursera

Modern Robotics, Course 4: Robot Motion Planning and Control (Coursera)

Offered by Northwestern University,

Do you want to know how robots work? Are you interested in robotics as a career? Are you willing to invest the effort to learn fundamental mathematical modeling techniques that are used in all subfields of robotics? If so, then the "Modern Robotics: Mechanics, Planning, and Control" specialization may be for you. This specialization, consisting of six short courses, is serious preparation for serious students who hope to work in the field of robotics or to undertake advanced study. It is not a sampler.

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

In Course 4 of the specialization, Robot Motion Planning and Control, you will learn key concepts of robot motion generation: planning a motion for a robot in the presence of obstacles, and real-time feedback control to track the planned motion. Chapter 10, Motion Planning, of the "Modern Robotics" textbook covers foundational material like C-space obstacles, graphs and trees, and graph search, as well as classical and modern motion planning techniques, such as grid-based motion planning, randomized sampling-based planners, and virtual potential fields. Chapter 11, Robot Control, covers motion control, force control, and hybrid motion-force control.
Course 4 of 6 in the Modern Robotics: Mechanics, Planning, and Control Specialization.

Syllabus

WEEK 1
Chapter 10: Motion Planning (Part 1 of 2)
C-space obstacles, graphs and trees, and A* graph search.

WEEK 2
Chapter 10: Motion Planning (Part 2 of 2)
Motion planning on a discretized C-space grid, randomized sampling-based planners, virtual potential fields, and nonlinear optimization.

WEEK 3
Chapter 11: Robot Control (Part 1 of 2)
First- and second-order linear error dynamics, stability of a feedback control system, and motion control of robots when the output of the controller commands joint velocities.

WEEK 4
Chapter 11: Robot Control (Part 2 of 2)
Motion control of robots when the output of the controller commands joint torques, force control, and hybrid motion-force control.

Go to Class

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

Related Courses

Coursera

Starweaver

Future of Production (Coursera)

CS: Information & Technology

This course delves into the forefront of manufacturing, exploring how emerging technologies and innovative practices are revolutionizing the industry. Participants will gain insights into the latest trends and advancements in production processes, including the impact of automation, robotics, and sustainable practices.

Oct 12th 2026

4 Weeks

Sustainability Robotics Manufacturing

Coursera

Northwestern University

Modern Robotics, Course 6: Capstone Project, Mobile Manipulation (Coursera)

Engineering Sci: Physics

The capstone project of the Modern Robotics specialization is on mobile manipulation: simultaneously controlling the motion of a wheeled mobile base and its robot arm to achieve a manipulation task. This project integrates several topics from the specialization, including trajectory planning, odometry for mobile robots, and feedback control. Beginning from the Modern Robotics software library provided to you (written in Python, Mathematica, and MATLAB), and software you have written for previous courses, you will develop software to plan and control the motion of a mobile manipulator to perform a pick and place task.

Oct 12th 2026

4 Weeks

Robotics MATLAB Mobile

Robot Mechanics and Control, Part I (edX)

EdX

Seoul National University,SNUx

Robot Mechanics and Control, Part I (edX)

Robotics & Computer Vision

A mathematical introduction to the mechanics and control of robots. This course provides a mathematical introduction to the mechanics and control of robots that can be modeled as kinematic chains. Topics covered include the concept of a robot’s configuration space and degrees of freedom, static grasp analysis, the description of rigid body motions, kinematics of open and closed chains, and the basics of robot control.

No sessions available

4 Weeks

Robots Robotics Mechanics

FutureLearn

University of Leeds

MedTech: AI and Medical Robots (FutureLearn)

Robotics & Computer Vision

Explore human robot interaction and enter the fascinating world of robotics and artificial intelligence in healthcare. Learn how medical robots in healthcare are designed, regulated and used. On this course, you will learn what robots are and explore human robot interaction (HRI) in healthcare. You will identify the challenges of designing robots for healthcare and look at what MedTech scientists are doing to solve them.

Self Paced

2 Weeks

Healthcare Artificial Intelligence Robotics

Robot Mechanics and Control, Part II (edX)

EdX

Seoul National University,SNUx

Robot Mechanics and Control, Part II (edX)

Robotics & Computer Vision

A mathematical introduction to the mechanics and control of robots. This course is Part II of a two-part mathematical introduction to the mechanics and control of robots that can be modeled as kinematic chains. Topics covered include the concept of a robot’s configuration space and degrees of freedom, static grasp analysis, the description of rigid body motions, kinematics of open and closed chains, and the basics of robot control.

No sessions available

4 Weeks

Robots Robotics Mechanics

Udacity

Intro to Artificial Intelligence (Udacity)

Robotics & Computer Vision

This course will introduce you to the basics of AI. Topics include machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing. Artificial Intelligence (AI) is a field that has a long history but is still constantly and actively growing and changing. In this course, you’ll learn the basics of modern AI as well as some of the representative applications of AI.

Self Paced

Self-Paced

Statistics Artificial Intelligence Robotics

Saylor Academy

Saylor.org

Artificial Intelligence (saylor.org)

Robotics & Computer Vision

This course introduces the field of artificial intelligence (AI). Materials on AI programming, logic, search, game playing, machine learning, natural language understanding, and robotics introduce the student to AI methods, tools, and techniques, their application to computational problems, and their contribution to understanding intelligence.

Self Paced

Self-Paced

Artificial Intelligence Robotics Machine Learning

Udacity

Artificial Intelligence for Robotics (Udacity)

Robotics & Computer Vision

Learn how to program all the major systems of a robotic car. Topics include planning, search, localization, tracking, and control. Learn how to program all the major systems of a robotic car from the leader of Google and Stanford's autonomous driving teams. This class will teach you basic methods in Artificial Intelligence, including: probabilistic inference, planning and search, localization, tracking and control, all with a focus on robotics. Extensive programming examples and assignments will apply these methods in the context of building self-driving cars.

Self Paced

Self-Paced

Artificial Intelligence Robotics AI

FutureLearn

Raspberry Pi Foundation,National Centre for Computing Education

Robotics With Raspberry Pi: Build and Program Your First Robot Buggy (FutureLearn)

Computer Science

Build and program your first robot buggy using a Raspberry Pi, learning how to connect motors, add sensors and write algorithms. Learn robotics by building a robot buggy and controlling it with a Raspberry Pi. On this course from the Raspberry Pi Foundation, you’ll build a robot buggy controlled by a Raspberry Pi.

Jan 2nd 2023

3 Weeks

Programming Robotics Algorithms

Coursera

University of Colorado Boulder

Robotic Path Planning and Task Execution (Coursera)

Robotics & Computer Vision

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".

Oct 5th 2026

5-12 Weeks

Robotics Motion Planning Python Programming

Coursera

Northwestern University

Modern Robotics, Course 2: Robot Kinematics (Coursera)

Robotics & Computer Vision

Oct 5th 2026

4 Weeks

Robotics Kinematics Robot Kinematics

EdX

Columbia University,ColumbiaX

Artificial Intelligence (AI) (edX)

Robotics & Computer Vision

Learn the fundamentals of Artificial Intelligence (AI), and apply them. Design intelligent agents to solve real-world problems including, search, games, machine learning, logic, and constraint satisfaction problems. What do self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection have in common? They are all complex real world problems being solved with applications of intelligence (AI).

This course is archived

5-12 Weeks

Artificial Intelligence Robotics Vision