Jackrabbot

Introduction

 

JackRabbot

Humans have the innate ability to "read" one another. When people walk in a crowed public space such as a sidewalk, an airport terminal, or a shopping mall, they obey a large number of (unwritten) common sense rules and comply with social conventions. For instance, as they consider where to move next, they respect personal space and yield right-of-way. The ability to model these “rules” and use them to understand and predict human motion in complex real world environments is extremely valuable for the next generation of social robots.

Our work at the CVGL is making practical a new generation of autonomous agents that can operate safely alongside humans in dynamic crowded environments such as terminals, malls, or campuses.  This enhanced level of proficiency opens up a broad new range of applications where robots can replace or augment human efforts. One class of tasks now susceptible to automation is the delivery of small items – such as purchased goods, mail, food, tools and documents – via spaces normally reserved for pedestrians.

In this project, we are exploring this opportunity by developing a demonstration platform to make deliveries locally within the Stanford campus.  The Stanford “Jackrabbot”, which takes it name from the nimble yet shy Jackrabbit, is a self-navigating automated electric delivery cart capable of carrying small payloads. In contrast to autonomous cars, which operate on streets and highways, the Jackrabbot is designed to operate in pedestrian spaces, at a maximum speed of five miles per hour.

 

NEWS & Press release

 

Team

image

Silvio Savarese

Assistant Professor    
ssilvio at stanford dot edu 
Web

Alexandre Alahi

Research Scientist  
alahi at stanford dot edu
web

Amir Sadeghian

PhD Candidate,  
amirabs at stanford dot edu
Web

Patrick Goebel

Research staff  
pgoebel at stanford dot edu
web

Zhenkai Wang

Master Student  
zackwang at stanford dot edu

Haihong Li

Master Student  
hhli at stanford dot edu 

Lin Sun

Visiting Student, Stanford
PhD Candidate, HKUST
sunlin1 at stanford dot edu 

Jerry Kaplan

Visiting lecturer  
jerrykaplan at stanford dot edu 
web

Alumni

Alexandre Robicquet

Master's Student,  
arobicqu at stanford dot edu

Chris Cruise

Master's Student,  
ccruise at stanford dot edu

Vignesh Ramanathan

Research Scientist, Facebook  
vigneshram.iitkgp at gmail dot com

 

Publication

  • T. Bagautdinov, A. Alahi, F. Fleuret, P. Fua, S. Savarese, Social Scene Understanding: End-to-End Multi-Person Action Localization and Collective Activity Recognition., in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. oral. pdf
  • A. Sadeghian, A. Alahi, S. Savarese, Tracking The Untrackable: Learning To Track Multiple Cues with Long-Term Dependencies, To come (arxiv). pdf
  • A. Alahi*, K. Goel*, V. Ramanathan, A. Robicquet, L. Fei-Fei, S. Savarese, Social LSTM: Human Trajectory Prediction in Crowded Spaces, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016 spotlight. pdf bibtex
  • A. Robicquet, A. Sadeghian A. Alahi, S. Savarese, Learning Social Etiquette: Human Trajectory Understanding in Crowded Scenes, in European Conference on Computer Vision (ECCV), 2016. pdf
  • L. Ballan, F. Castaldo, A. Alahi, F. Palmieri, S. Savarese, Knowledge Transfer for Scene-specific Motion Prediction, in European Conference on Computer Vision (ECCV), 2016. pdf

 

Dataset and Code

  • The Stanford Drone Dataset is available (here)

 

JR life

 

 

JR at the dressing room! JR ready for california winter! JR suit up! JR in red!    

 

Related videos

 

JR Quartz! JR on CBS!

 

JR view! JR on PBS!

 

JR on Financial Times! JR on abc7news!

 

JR on BBC news!

 

 

Acknowledgements

We acknowledge the support of ONR, MURI, Toyota and Panasonic..

 

Contact : amirabs (at) stanford (dot) edu

Last update : 06/08/2017