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Robotics

Daniel E. Koditschek, Vijay Kumar, Daniel Lee, Kostas Daniilidis, Sid Deliwala, Jianbo Shi, CJ Taylor, Camillo J. Taylor, and Mark Yim

The Introduction to Robotics Specialization introduces you to the concepts of robot flight and movement, how robots perceive their environment, and how they adjust their movements to avoid obstacles, navigate difficult terrains and accomplish complex tasks such as construction and disaster recovery. You will be exposed to real world examples of how robots have been applied in disaster situations, how they have made advances in human health care and what their future capabilities will be. The courses build towards a capstone in which you will learn how to program a robot to perform a variety of movements such as flying and grasping objects.

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What's inside

Six courses

Robotics: Aerial Robotics

(4 hours)

How can we create agile micro aerial vehicles that can operate autonomously in cluttered indoor and outdoor environments? You will gain an intro to the mechanics of flight and the design of quadrotor flying robots and will be able to develop dynamic models, derive controllers, and synthesize planners for operating in three-dimensional environments.

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Robotics: Computational Motion Planning

(3 hours)

Robotic systems typically include three components: a mechanism, a perception system, and a decision and control system. This course considers how a robot decides what to do to achieve its goals, a problem known as Motion Planning. You will learn common approaches to this problem, including graph-based methods, randomized planners, and artificial potential fields.

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Robotics: Mobility

(0 hours)

How can robots move in unstructured environments? You will understand how to design robot bodies and behaviors that use limbs and appendages to apply physical forces for reliable mobility. Specific topics include: mobility in animals and robots, kinematics and dynamics of legged machines, and design of dynamical behavior via energy landscapes.

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Robotics: Perception

(0 hours)

How can robots perceive the world and their own movements? In this module, we will study how images and videos acquired by cameras mounted on robots are transformed into representations like features and optical flow. Such 2D representations allow us then to extract 3D information about where the camera is and in which direction the robot moves.

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Robotics: Estimation and Learning

(0 hours)

How can robots determine their state and the surrounding environment from noisy sensor measurements in time? In this module, you will learn how to get robots to incorporate uncertainty into estimating and learning from a dynamic and changing world. Specific topics that will be covered include probabilistic generative models, Bayesian filtering for localization and mapping.

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Robotics: Capstone

(0 hours)

In our 6-week Robotics Capstone, you will implement a solution for a real-world problem using the content you learned from the courses in your robotics specialization. You will also use mathematical and programming methods that researchers use in robotics labs.

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Learning objectives

Motion planning
Matlab

Estimation

Motion planning
Matlab
Estimation

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Time

464 hours

Level

Introductory

Via

Coursera

Institution

University of Pennsylvania

Instructors

Daniel E. Koditschek

Vijay Kumar

Daniel Lee

Kostas Daniilidis

Sid Deliwala

Jianbo Shi

CJ Taylor

Camillo J. Taylor

Mark Yim

Level

Introductory

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