Automatic Scene Graph Generation

Scene graphs allow to easily model dynamic environments for robots: Every object is a node in a graph and can be moved around, with edges combining nodes based on geometric or semantic proximity, and connections to higher levels grouping nodes per room, floor, and building. In this thesis, we want to create a tool that easily and automatically creates such scene graphs from a single iPad scan of the room, such that a robot can be deployed to the environment. We base this on LabelMaker, where we add instance segmentation, and separation of rooms and floors. Requirements: experience with a python, ideally with open3d; docker is a plus

Scene graphs allow to easily model dynamic environments for robots: Every object is a node in a graph and can be moved around, with edges combining nodes based on geometric or semantic proximity, and connections to higher levels grouping nodes per room, floor, and building.

In this thesis, we want to create a tool that easily and automatically creates such scene graphs from a single iPad scan of the room, such that a robot can be deployed to the environment. We base this on LabelMaker, where we add instance segmentation, and separation of rooms and floors.

Requirements: experience with a python, ideally with open3d; docker is a plus

Our goal is to create an easy tool that anybody can use, but to also be able to process large datasets such as Taskonomy, to create the first large, multi-room scene-graph dataset for the research community.

Our goal is to create an easy tool that anybody can use, but to also be able to process large datasets such as Taskonomy, to create the first large, multi-room scene-graph dataset for the research community.

please send your CV and transcript to blumh@ethz.ch

please send your CV and transcript to blumh@ethz.ch