Overview

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”.

Syllabus

Course 1: Basic Robotic Behaviors and Odometry
Course 2: Robotic Mapping and Trajectory Generation
Course 3: Robotic Path Planning and Task Execution

Courses

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1 day 19 hours 23 minutes
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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". It is recommended that you complete the first and second courses of this specialization, “Introduction to Robotics: Basic Behaviors” and "Robotic Mapping and Trajectory Generation" , before beginning this one. This course can be taken for academic credit as part of CU Boulder’s MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
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1 day 2 hours 24 minutes
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In this second course of the Introduction to Robotics specialization, "Robotic Mapping and Trajectory Generation", you will learn how to perform basic inverse kinematics of (non-)holonomic systems using a feedback control approach. You will also learn how to process multi-dimensional sensor signals such as laser range scanners for mapping. Additionally, you will apply the overarching focus of mechanisms and sensors as sources of uncertainty and gain techniques to how to model and control them. It is recommended that you complete the first course of this specialization, “Introduction to Robotics: Basic Behaviors”, before beginning this one. This course can be taken for academic credit as part of CU Boulder’s MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
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1 day 4 hours 18 minutes
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"Basic Robotic Behaviors and Odometry" provides you with an introduction to autonomous mobile robots, including forward kinematics (“odometry”), basic sensors and actuators, and simple reactive behavior. This course is centered around exercises in the realistic, physics-based simulator, “Webots”, where you will experiment in a hands-on manner with simple reactive behaviors for collision avoidance and line following, state machines, and basic forward kinematics of non-holonomic systems. An overarching objective of this course is to understand the role of the physical system on algorithm design and its role as source of uncertainty that makes robots non-deterministic. If you are interested in getting started with robotics, this course is for you! This course can be taken for academic credit as part of CU Boulder’s MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder