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Robotics: Computational Motion Planning
Course
en
English
Subtitles available
12 h
This content is rated 0 out of 5
- Self-paced
- Free Access
- Fee-based Certificate
- 4 Sequences
- Introductive Level
- Subtitles in Spanish
Course details
Syllabus
- Week 1 - 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 rou... - Week 2 - 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 wh... - Week 3 - 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... - Week 4 - 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...
Prerequisite
None.
Instructors
CJ Taylor
Professor of Computer and Information Science
School of Engineering and Applied Science
Editor
The University of Pennsylvania (commonly known as Penn), founded in 1740, is a private university located in Philadelphia, Pennsylvania, USA. A member of the Ivy League, Penn is the fourth oldest institution of higher learning in the United States and considers itself the first university in the United States to offer both undergraduate and graduate degrees.
Platform
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