課程信息
4.2
692 個評分
182 個審閱
專項課程

第 2 門課程(共 6 門)

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
完成時間(小時)

完成時間大約為15 小時

建議:3 hours/week...
可選語言

英語(English)

字幕:英語(English), 西班牙語(Spanish)

您將獲得的技能

Motion PlanningAutomated Planning And SchedulingA* Search AlgorithmMatlab
專項課程

第 2 門課程(共 6 門)

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
完成時間(小時)

完成時間大約為15 小時

建議:3 hours/week...
可選語言

英語(English)

字幕:英語(English), 西班牙語(Spanish)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間(小時)
完成時間為 4 小時

Introduction and Graph-based Plan Methods

Welcome to Week 1! In this module, we will introduce the problem of planning routes through grids where the robot can only take on discrete positions. We can model these situations as graphs where the nodes correspond to the grid locations and the edges to routes between adjacent grid cells. We present a few algorithms that can be used to plan paths between a start node and a goal node including the breadth first search or grassfire algorithm, Dijkstra’s algorithm and the A Star procedure....
Reading
5 個視頻 (總計 27 分鐘), 4 個閱讀材料, 4 個測驗
Video5 個視頻
1.2: Grassfire Algorithm6分鐘
1.3: Dijkstra's Algorithm4分鐘
1.4: A* Algorithm6分鐘
Getting Started with the Programming Assignments3分鐘
Reading4 個閱讀材料
Computational Motion Planning Honor Code10分鐘
Getting Started with MATLAB10分鐘
Resources for Computational Motion Planning10分鐘
Graded MATLAB Assignments10分鐘
Quiz1 個練習
Graph-based Planning Methods8分鐘
2
完成時間(小時)
完成時間為 2 小時

Configuration Space

Welcome to Week 2! In this module, we begin by introducing the concept of configuration space which is a mathematical tool that we use to think about the set of positions that our robot can attain. We then discuss the notion of configuration space obstacles which are regions in configuration space that the robot cannot take on because of obstacles or other impediments. This formulation allows us to think about path planning problems in terms of constructing trajectories for a point through configuration space. We also describe a few approaches that can be used to discretize the continuous configuration space into graphs so that we can apply graph-based tools to solve our motion planning problems....
Reading
6 個視頻 (總計 19 分鐘), 3 個測驗
Video6 個視頻
2.2: RR arm2分鐘
2.3: Piano Mover’s Problem3分鐘
2.4: Visibility Graph3分鐘
2.5: Trapezoidal Decomposition1分鐘
2.6: Collision Detection and Freespace Sampling Methods4分鐘
Quiz1 個練習
Configuration Space8分鐘
3
完成時間(小時)
完成時間為 1 小時

Sampling-based Planning Methods

Welcome to Week 3! In this module, we introduce the concept of sample-based path planning techniques. These involve sampling points randomly in the configuration space and then forging collision free edges between neighboring sample points to form a graph that captures the structure of the robots configuration space. We will talk about Probabilistic Road Maps and Randomly Exploring Rapid Trees (RRTs) and their application to motion planning problems....
Reading
3 個視頻 (總計 17 分鐘), 2 個測驗
Video3 個視頻
3.2: Issues with Probabilistic Road Maps4分鐘
3.3: Introduction to Rapidly Exploring Random Trees6分鐘
Quiz1 個練習
Sampling-based Methods6分鐘
4
完成時間(小時)
完成時間為 1 小時

Artificial Potential Field Methods

Welcome to Week 4, the last week of the course! Another approach to motion planning involves constructing artificial potential fields which are designed to attract the robot to the desired goal configuration and repel it from configuration space obstacles. The robot’s motion can then be guided by considering the gradient of this potential function. In this module we will illustrate these techniques in the context of a simple two dimensional configuration space....
Reading
4 個視頻 (總計 19 分鐘), 2 個測驗
Video4 個視頻
4.2: Issues with Local Minima2分鐘
4.3: Generalizing Potential Fields2分鐘
4.4: Course Summary6分鐘
Quiz1 個練習
Artificial Potential Fields6分鐘
4.2
182 個審閱Chevron Right
工作福利

33%

通過此課程獲得實實在在的工作福利

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創建者 FCNov 28th 2018

The course was challenging, but fulfilling. Thank you Coursera and University of Pennsylvania for giving this wonderful experience and opportunity that I might not experience in our local community!

創建者 ADJul 3rd 2018

The topic was very interesting, and the assignments weren't overly complicated. Overall, the lesson was fun and informative , despite the bugs in the learning tool(especially, the last assignment.)

講師

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CJ Taylor

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

關於 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. ...

關於 机器人 專項課程

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....
机器人

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