Robotics: Capstone

Por: Coursera . en: , ,

Descripción del Curso

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.

You will choose from two tracks - In the simulation track, you will use Matlab to simulate a mobile inverted pendulum or MIP. The material required for this capstone track is based on courses in mobility, aerial robotics, and estimation. In the hardware track you will need to purchase and assemble a rover kit, a raspberry pi, a pi camera, and IMU to allow your rover to navigate autonomously through your own environment

Hands-on programming experience will demonstrate that you have acquired the foundations of robot movement, planning, and perception, and that you are able to translate them to a variety of practical applications in real world problems. Completion of the capstone will better prepare you to enter the field of Robotics as well as an expansive and growing number of other career paths where robots are changing the landscape of nearly every industry.
Please refer to the syllabus below for a week by week breakdown of each track.

Week 1

Introduction
MIP Track: Using MATLAB for Dynamic Simulations
AR Track: Dijkstra's and Purchasing the Kit
Quiz: A1.2 Integrating an ODE with MATLAB
Programming Assignment: B1.3 Dijkstra's Algorithm in Python

Week 2

MIP Track: PD Control for Second-Order Systems
AR Track: Assembling the Rover
Quiz: A2.2 PD Tracking
Quiz: B2.10 Demonstrating your Completed Rover

Week 3

MIP Track: Using an EKF to get scalar orientation from an IMU
AR Track: Calibration
Quiz: A3.2 EKF for Scalar Attitude Estimation
Quiz: B3.8 Calibration

Week 4

MIP Track: Modeling a Mobile Inverted Pendulum (MIP)
AR Track: Designing a Controller for the Rover
Quiz: A4.2 Dynamical simulation of a MIP
Peer Graded Assignment: B4.2 Programming a Tag Following Algorithm

Week 5

MIP Track: Local linearization of a MIP and linearized control
AR Track: An Extended Kalman Filter for State Estimation
Quiz: A5.2 Balancing Control of a MIP
Peer Graded Assignment: B5.2 An Extended Kalman Filter for State Estimation

Week 6

MIP Track: Feedback motion planning for the MIP
AR Track: Integration
Quiz: A6.2 Noise-Robust Control and Planning for the MIP
Peer Graded Assignment: B6.2 Completing your Autonomous Rover

Plataforma