Course Summary
In this capstone project, students will design and build their own robot that is capable of performing certain tasks. With the help of experts in the field, students will learn about robotics, computer vision, and machine learning.Key Learning Points
- Design and build your own robot capable of performing tasks
- Learn about robotics, computer vision, and machine learning
- Receive guidance and support from experts in the field
Job Positions & Salaries of people who have taken this course might have
- Robotics Engineer
- USA: $85,000 - $150,000
- India: ₹5,00,000 - ₹20,00,000
- Spain: €30,000 - €75,000
- Machine Learning Engineer
- USA: $95,000 - $165,000
- India: ₹6,00,000 - ₹25,00,000
- Spain: €35,000 - €85,000
- Computer Vision Engineer
- USA: $90,000 - $155,000
- India: ₹5,50,000 - ₹22,00,000
- Spain: €32,000 - €80,000
Related Topics for further study
Learning Outcomes
- Design and build a functional robot
- Apply concepts of robotics, computer vision, and machine learning
- Collaborate with experts in the field and receive feedback on project
Prerequisites or good to have knowledge before taking this course
- Completion of relevant courses in robotics, computer vision, and machine learning
- Familiarity with programming languages such as Python and C++
Course Difficulty Level
AdvancedCourse Format
- Project-based
- Collaborative
- Self-paced
Similar Courses
- Control of Mobile Robots
- Robotics: Perception
- Robotics: Estimation and Learning
Related Education Paths
Notable People in This Field
- Rodney Brooks
- Helen Greiner
Related Books
Description
In our 6 week Robotics Capstone, we will give you a chance to implement a solution for a real world problem based on the content you learnt from the courses in your robotics specialization. It will also give you a chance to use mathematical and programming methods that researchers use in robotics labs.
Outline
- Week 1
- Capstone Introduction and Choosing the Capstone Project
- Introduction to the Mobile Inverted Pendulum (MIP) Track
- Introduction to the Autonomous Rover (AR) Track
- Week 1: Lesson Choices
- A1.1 Using MATLAB for Dynamic Simulations
- (Review) Dijkstra's Algorithm
- B1.1 Purchasing the Robot Kit
- B1.2 The Rover Simulator
- A1.2 Integrating an ODE with MATLAB
- Week 2: Lesson Choices
- (Review) Newton's Laws; Damped and Undamped
- (Review) PD Control for a Point Particle in Space
- A2.1 PD Control for Second-Order Systems
- (Review) Infinitesimal Kinematics; RR Arm
- B2.1 Building the Autonomous Rover (AR)
- B2.6 Connecting to the Pi
- B2.2 Soldering tips
- B2.3 Soldering the Motor Hat and IMU
- B2.4 Flashing your Raspberry Pi SD Card
- B2.5 Assembling the Robot
- B2.7 Expanding the SD Card Partition
- B2.8 Remote Access to the Pi
- B2.9 Controlling the Rover
- A2.2 PD Tracking
- Week 3: Lesson Choices
- (Review) Extended Kalman Filter
- A3.1 Using an EKF to get Scalar Orientation from an IMU
- B3.1 Calibration
- B3.2 Camera Calibration
- (Review) Rotations and Translations
- B3.4 Camera to body calibration
- B3.5 Introduction to Apriltags
- B3.3 Motor Calibration
- B3.6 Printing your own AprilTags
- B3.7 Optional: IMU Accelerometer Calibration
- A3.2 EKF for Scalar Attitude Estimation
- B3.8 Calibration
- Week 4: Lesson Choices
- (Review) Lagrangian Dynamics
- A4.1 Modeling a Mobile Inverted Pendulum (MIP)
- (Review) 2-D Quadrotor Control
- B4.1 Designing a Controller for the Rover
- A4.2 Dynamical simulation of a MIP
- Week 5: Lesson Choices
- (Review) Linearization
- A5.1 Local Linearization of a MIP and Linearized Control
- (Review) Kalman Filter Model
- (Review) Extended Kalman Filter Model
- B5.1 An Extended Kalman Filter for the Rover
- A5.2 Balancing Control of a MIP
- Week 6: Lesson Choices
- (Review) Motion Planning for Quadrotors
- A6.1 Feedback Motion Planning for the MIP
- B6.1 Integration
- A6.2 Noise-Robust Control and Planning for the MIP
Summary of User Reviews
The Robotics Capstone course on Coursera has received positive reviews from many users. The course has been praised for its comprehensive content, practical projects, and interactive learning experience. Users have rated the course highly for its ability to provide hands-on experience in robotics and its challenging but rewarding curriculum.Key Aspect Users Liked About This Course
Many users appreciated the practical projects in the course, which allowed them to apply the concepts they learned to real-world problems.Pros from User Reviews
- Comprehensive content that covers a wide range of topics in robotics
- Interactive learning experience that encourages active participation and engagement
- Hands-on projects that provide practical experience in robotics
- Challenging curriculum that pushes students to develop their skills
- Excellent instructors who provide helpful feedback and support
Cons from User Reviews
- Some users found the course to be too challenging and time-consuming
- The course requires a significant amount of equipment and resources, which may be difficult for some students to obtain
- The pace of the course may be too fast for some learners, especially those who are new to robotics
- Some users felt that the course could benefit from more detailed explanations and examples
- The grading system for the course may be unclear or confusing for some students
Sid Deliwala
4.6 Raiting
Modern Robotics, Course 6: Capstone Project, Mobile Manipulation
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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....
Robotics: Capstone
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It will also give you a chance to use mathematical and programming methods that researchers use in robotics labs. Week 1...
