Title:
Factor Graphs for Flexible Inference in Robotics and Vision
Factor Graphs for Flexible Inference in Robotics and Vision
Author(s)
Dellaert, Frank
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Abstract
In robotics and computer vision, Simultaneous Localization and Mapping (SLAM) and Structure from Motion (SFM) are important and closely related problems in robotics and vision. I will review how SLAM, SFM and other problems in robotics and vision can be posed in terms of factor graphs, which provide a graphical language in which to develop and collaborate on such problems. The theme of the talk will be to emphasize the advantages and intuition that come with that. I will show how using these insights we have developed both batch and incremental algorithms defined on graphs in the SLAM/SFM domain, as well as more sophisticated approaches to trajectory optimization. Many of these ideas are embodied in the Skydio R1, a commercially available, fully autonomous drone I helped develop at Skydio, a San Francisco Bay area startup.
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Date Issued
2019-01-09
Extent
59:54 minutes
Resource Type
Moving Image
Resource Subtype
Lecture