Modern Robotics, Course 4: Robot Motion Planning and Control

Go to Course: https://www.coursera.org/learn/modernrobotics-course4

Introduction

### Course Review: Modern Robotics, Course 4: Robot Motion Planning and Control on Coursera #### Overview If you’ve ever marveled at the capabilities of robots and wondered how they navigate and perform complex tasks in dynamically changing environments, then the "Modern Robotics: Mechanics, Planning, and Control" specialization on Coursera is the perfect resource for you. Course 4, specifically focused on Robot Motion Planning and Control, delves into the sophisticated mathematical frameworks and algorithms that enable effective robot operation, making it an essential piece for anyone looking to carve out a career in robotics or deepen their understanding of the field. #### Who Is This Course For? This course is tailored for aspiring robotics professionals, students in related engineering fields, or hobbyists who are keen to understand the mathematics and mechanics behind robot behavior. If you are willing to commit to the learning of fundamental mathematical modeling techniques that are foundational across all areas of robotics, this course will serve you well. #### Course Content The course is structured into two main chapters: 1. **Motion Planning (Part 1 and 2)**: - In the first part, you will explore concepts such as configuration space (C-space), obstacles within this space, and foundational algorithms like A* graph search, which are critical for navigating a robot through its environment. - The second part introduces you to more advanced techniques such as motion planning on discretized C-space grids and randomized sampling-based planners. Topics like virtual potential fields and nonlinear optimization emphasize real-world applicability. 2. **Robot Control (Part 1 and 2)**: - The control modules provide a deep dive into the dynamics of robots, discussing first and second-order linear error dynamics and assessing the stability of feedback control systems. Understanding how to command joint velocities is vital for effective robot motion control. - The second segment focuses on more advanced control techniques, including commanding joint torques, effective force control mechanisms, and the interplay between motion and force—skills crucial for controlling robots in a wide variety of scenarios. #### Learning Experience The format of the course includes engaging lectures, practical modeling exercises, and programming assignments to solidify your understanding. Throughout the course, you will have the opportunity to apply theoretical concepts to practical situations, making the learning process not only theoretical but also deeply hands-on. #### Recommendations - **For Beginners**: If you are new to robotics, it might be helpful to go through previous courses in the specialization to familiarize yourself with foundational concepts before tackling this advanced course. - **For Experienced Learners**: Those with a background in engineering or related disciplines will greatly benefit from its depth and rigor. The course will challenge your understanding, pushing you to think critically and analytically about robotics. - **Additional Resources**: Engage with the course community through forums and discussions to enhance your understanding and resolve any queries. #### Conclusion Overall, Course 4 of the "Modern Robotics" specialization on Coursera provides a comprehensive and rigorous exploration of robot motion planning and control. It expertly combines theory with practice, equipping learners with essential skills needed in the rapidly evolving field of robotics. Whether you aspire to a career in this domain or seek to expand your academic knowledge, enrolling in this course is a commendable step towards becoming proficient in modern robotics. I highly recommend it to anyone serious about robotic systems and their applications in real-world scenarios.

Syllabus

Chapter 10: Motion Planning (Part 1 of 2)

C-space obstacles, graphs and trees, and A* graph search.

Motion planning on a discretized C-space grid, randomized sampling-based planners, virtual potential fields, and nonlinear optimization.

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.

Motion control of robots when the output of the controller commands joint torques, force control, and hybrid motion-force control.