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.
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机器人 专项课程宾夕法尼亚大学课程信息
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第 4 门课程（共 6 门）
中级
完成时间大约为33 小时
英语（English）
字幕：法语（French）, （欧洲人讲的）葡萄牙语, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）
您将获得的技能
- Computer Vision
- Estimation
- Random Sample Consensus (Ransac)
- Geometry
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
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100% 在线
立即开始，按照自己的计划学习。
第 4 门课程（共 6 门）
中级
完成时间大约为33 小时
英语（English）
字幕：法语（French）, （欧洲人讲的）葡萄牙语, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）
提供方
宾夕法尼亚大学
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.
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完成时间为 10 小时
Geometry of Image Formation
Welcome to Robotics: Perception! We will begin this course with a tutorial on the standard camera models used in computer vision. These models allow us to understand, in a geometric fashion, how light from a scene enters a camera and projects onto a 2D image. By defining these models mathematically, we will be able understand exactly how a point in 3D corresponds to a point in the image and how an image will change as we move a camera in a 3D environment. In the later modules, we will be able to use this information to perform complex perception tasks such as reconstructing 3D scenes from video.
完成时间为 10 小时
15 个视频 （总计 180 分钟）, 1 个阅读材料, 9 个测验
完成时间为 6 小时
Projective Transformations
Now that we have a good camera model, we will explore the geometry of perspective projections in depth. We will find that this projection is the cause of the main challenge in perception, as we lose a dimension that we can no longer directly observe. In this module, we will learn about several properties of projective transformations in depth, such as vanishing points, which allow us to infer complex information beyond our basic camera model.
完成时间为 6 小时
5 个视频 （总计 69 分钟）
完成时间为 8 小时
Pose Estimation
In this module we will be learning about feature extraction and pose estimation from two images. We will learn how to find the most salient parts of an image and track them across multiple frames (i.e. in a video sequence). We will then learn how to use features to find the position of the camera with respect to another reference frame on a plane using Homographies. We will also learn about how to make these techniques more robust, using least squares to hand noisy feature points or RANSAC to remove completely erroneous feature points.
完成时间为 8 小时
8 个视频 （总计 126 分钟）
完成时间为 9 小时
Multi-View Geometry
Now we will use what we learned from two view geometry and extend it to sequences of images, such as a video. We will explain the fundamental geometric constraints between point features in images, the Epipolar constraint, and learn how to use it to extract the relative poses between multiple frames. We will finish by combining all this information together for the application of Structure from Motion, where we will compute the trajectory of a camera and a map throughout many frames and refine our estimates using Bundle adjustment.
完成时间为 9 小时
14 个视频 （总计 221 分钟）
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- 5 stars59.77%
- 4 stars25.11%
- 3 stars7.63%
- 2 stars4.13%
- 1 star3.33%
来自ROBOTICS: PERCEPTION的热门评论
由 LL 提供Feb 26, 2017
The 4th week content is hard to follow than the previous three. It would be better if more detailed math and examples are provided in the 4th week.
由 JS 提供Jan 5, 2018
Extremely fast-paced course that gives a great overview of Perception but leaves a lot of things unexplained or without proofs.
由 DA 提供Jan 31, 2021
This course was truly amazing. It was challenging and I learned a lot of cool stuff. It would have been better if more animations were included in explaining complex concepts and equations.
由 JM 提供Jun 25, 2018
For Computer Vision enthusiast who wants to learn about Multiple View Geometry, this is the best beginner course
关于 机器人 专项课程
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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