The overarching learning goal of this specialization in robotics is to create an appreciation for the tight interplay between mechanism, sensor, and control in the design of intelligent systems. By the end of this specialization, you will be able to (1) formally describe the forward and inverse kinematics of a mechanism, (2) discretize the robot’s state from algorithmic reasoning, and (3) understand the sources of uncertainty in sensing or actuation and describe them mathematically. During this specialization, you will gain hands-on experience in Python and use the realistic robotic system simulator, “Webots”.

Applied Learning Project

Learners will utilize the robotics simulator Webots to build their own simulations while learning. In this specialization, you will get "hands-on" with step-by-step instructions to implement a certain device or algorithm in Webots, then encourage you to explore this solution, extend or change it, and finally ask a question that ensures you have understood the concept. Hands-on activities lead to graded peer evaluations that will require reproducing previously learned concepts in the form of a well-defined behavior.

Emphasis on the first course of this specialization is on learning Webots and reading up on key concepts to build a foundation. Activities then gradually shift to include more hands-on activities in the second course of this specialization and culminate into a large project requiring the implementation of a complete mobile manipulation solution.