Introduction
This repository contains related code for the RSS 2021 paper "Move Beyond Trajectories: Distribution Space Coupling for Crowd Navigation" by Muchen Sun, Francesca Baldini, Pete Trautman and Todd Murphey.
Tutorials
We provide a Jupyter notebook tutorials for our algorithm. You can find them under the "notebooks" directory.
- Tutorial 1: distribution space coupling in one-dimensional space: In the first tutorial, we will build from scratch on a one-dimensional two-agents toy example to show how DistNav optimization works. We will show both the analytical solution with numerical integration and approximated solution with sampling and Monte-Carlo integration, and how they can match with each other. You can find a copy of the notebook in Google Colaboratory here.
Metadata
Release files for distnav 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| distnav-0.0.1.tar.gz | 2.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| distnav-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.6 kB