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Motion PlanningAutomated Planning And SchedulingA* Search AlgorithmMatlab

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강의 계획 - 이 강좌에서 배울 내용

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1

1

완료하는 데 4시간 필요

Introduction and Graph-based Plan Methods

완료하는 데 4시간 필요
5개 동영상 (총 27분), 4 개의 읽기 자료, 4 개의 테스트
5개의 동영상
1.2: Grassfire Algorithm6m
1.3: Dijkstra's Algorithm4m
1.4: A* Algorithm6m
Getting Started with the Programming Assignments3m
4개의 읽기 자료
Computational Motion Planning Honor Code10m
Getting Started with MATLAB10m
Resources for Computational Motion Planning10m
Graded MATLAB Assignments10m
1개 연습문제
Graph-based Planning Methods8m
2

2

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Configuration Space

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6개 동영상 (총 19분)
6개의 동영상
2.2: RR arm2m
2.3: Piano Mover’s Problem3m
2.4: Visibility Graph3m
2.5: Trapezoidal Decomposition1m
2.6: Collision Detection and Freespace Sampling Methods4m
1개 연습문제
Configuration Space8m
3

3

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Sampling-based Planning Methods

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3개 동영상 (총 17분)
3개의 동영상
3.2: Issues with Probabilistic Road Maps4m
3.3: Introduction to Rapidly Exploring Random Trees6m
1개 연습문제
Sampling-based Methods6m
4

4

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Artificial Potential Field Methods

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4개 동영상 (총 19분)
4개의 동영상
4.2: Issues with Local Minima2m
4.3: Generalizing Potential Fields2m
4.4: Course Summary6m
1개 연습문제
Artificial Potential Fields6m

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ROBOTICS: COMPUTATIONAL MOTION PLANNING의 최상위 리뷰

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로봇 공학 특화 과정 정보

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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