この専門講座について

100%オンラインコース

自分のスケジュールですぐに学習を始めてください。

フレキシブルなスケジュール

柔軟性のある期限の設定および維持

初級レベル

約7か月で修了

推奨6時間/週

英語

字幕:英語, スペイン語, 中国語(簡体)

学習内容

  • Check

    Motion Planning

  • Check

    Matlab

  • Check

    Estimation

習得するスキル

Motion PlanningParticle FilterMatlab

100%オンラインコース

自分のスケジュールですぐに学習を始めてください。

フレキシブルなスケジュール

柔軟性のある期限の設定および維持

初級レベル

約7か月で修了

推奨6時間/週

英語

字幕:英語, スペイン語, 中国語(簡体)

専門講座のしくみ

コースを受講しましょう。

Coursera(コーセラ)の専門講座は、一連のコース群であり、技術を身に付ける手助けとなります。開始するには、専門講座に直接登録するか、コースを確認して受講したいコースを選択してください。専門講座の一部であるコースにサブスクライブすると、自動的にすべての専門講座にサブスクライブされます。1つのコースを修了するだけでも結構です。いつでも、学習を一時停止したり、サブスクリプションを終了することができます。コースの登録状況や進捗を追跡するには、受講生のダッシュボードにアクセスしてください。

実践型プロジェクト

すべての専門講座には、実践型プロジェクトが含まれています。専門講座を完了して修了証を獲得するには、成功裏にプロジェクトを終了させる必要があります。専門講座に実践型プロジェクトに関する別のコースが含まれている場合、専門講座を開始するには、それら他のコースをそれぞれ終了させる必要があります。

修了証を取得

すべてのコースを終了し、実践型プロジェクトを完了すると、修了証を獲得します。この修了証は、今後採用企業やあなたの職業ネットワークと共有できます。

how it works

この専門講座には6コースあります。

コース1

Robotics: Aerial Robotics

4.5
1,922件の評価
498件のレビュー
How can we create agile micro aerial vehicles that are able to operate autonomously in cluttered indoor and outdoor environments? You will gain an introduction 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. You will be exposed to the challenges of using noisy sensors for localization and maneuvering in complex, three-dimensional environments. Finally, you will gain insights through seeing real world examples of the possible applications and challenges for the rapidly-growing drone industry. Mathematical prerequisites: Students taking this course are expected to have some familiarity with linear algebra, single variable calculus, and differential equations. Programming prerequisites: Some experience programming with MATLAB or Octave is recommended (we will use MATLAB in this course.) MATLAB will require the use of a 64-bit computer....
コース2

Robotics: Computational Motion Planning

4.2
730件の評価
191件のレビュー
Robotic systems typically include three components: a mechanism which is capable of exerting forces and torques on the environment, a perception system for sensing the world and a decision and control system which modulates the robot's behavior to achieve the desired ends. In this course we will consider the problem of how a robot decides what to do to achieve its goals. This problem is often referred to as Motion Planning and it has been formulated in various ways to model different situations. You will learn some of the most common approaches to addressing this problem including graph-based methods, randomized planners and artificial potential fields. Throughout the course, we will discuss the aspects of the problem that make planning challenging....
コース3

Robotics: Mobility

3.9
430件の評価
110件のレビュー
How can robots use their motors and sensors to move around in an unstructured environment? You will understand how to design robot bodies and behaviors that recruit limbs and more general appendages to apply physical forces that confer reliable mobility in a complex and dynamic world. We develop an approach to composing simple dynamical abstractions that partially automate the generation of complicated sensorimotor programs. Specific topics that will be covered include: mobility in animals and robots, kinematics and dynamics of legged machines, and design of dynamical behavior via energy landscapes....
コース4

Robotics: Perception

4.4
447件の評価
117件のレビュー
How can robots perceive the world and their own movements so that they accomplish navigation and manipulation tasks? 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. You will come to understand how grasping objects is facilitated by the computation of 3D posing of objects and navigation can be accomplished by visual odometry and landmark-based localization....

講師

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Jianbo Shi

Professor of Computer and Information Science
School of Engineering and Applied Science
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Vijay Kumar

Nemirovsky Family Dean of Penn Engineering and Professor of Mechanical Engineering and Applied Mechanics
School of Engineering and Applied Science
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Daniel Lee

Professor of Electrical and Systems Engineering
School of Engineering and Applied Science
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CJ Taylor

Professor of Computer and Information Science
School of Engineering and Applied Science
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Daniel E. Koditschek

Professor of Electrical and Systems Engineering
School of Engineering and Applied Science
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Sid Deliwala

Director, Electrical and Systems Engineering Labs and Lecturer, Electrical and Systems Engineering
Department of Electrical and Systems Engineering
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Kostas Daniilidis

Professor of Computer and Information Science
School of Engineering and Applied Science

ペンシルベニア大学(University of Pennsylvania)について

The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies. ...

よくある質問

  • はい。まず始めに興味のあるコースカードをクリックして登録します。コースに登録して修了することによって、共有できる修了証を取得するか、無料でコースを聴講してコースの教材を確認することができます。専門講座の一部であるコースにサブスクライブすると、専門講座全体に自動的にサブスクライブされます。進捗を追跡するには、受講生のダッシュボードにアクセスしてください。

  • このコースは完全にオンラインで提供されているため、実際に教室に出席する必要はありません。Webまたはモバイル機器からいつでもどこからでも講義、学習用教材、課題にアクセスできます。

  • この専門講座では大学の単位は付与されませんが、一部の大学では専門講座修了証を単位として承認する場合があります。詳細については、大学にお問い合わせください。

  • Time to completion can vary based on your schedule, but learners are able to complete the Specialization in as few as six months.

  • Each course in the Specialization is offered on a regular schedule, with sessions starting about once per month. If you don't complete a course on the first try, you can easily transfer to the next session, and your completed work and grades will carry over.

  • No particular background is necessary, however, some knowledge of engineering and mathematics is helpful.

  • You can receive a full refund up to two weeks after payment. View the full refund policy.

  • We recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.

  • Coursera courses and certificates don't carry university credit.

  • You will be able to program a robot’s movement and flight. The specialization is designed to help you move into a career in Robotics, engineering or other industries where robots are used to make technological advancement in the field.

  • The specialization requires the use of MATLAB which is provided for free from MathWorks. Included in the specialization are instructional videos and download information for the use of MATLAB. MATLAB will require the use of a 64-bit computer.

  • We will provide resources that might help prepare you to take this specialization.

さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。