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

[31/17/2017] JR has been featured in CBS News: "‘Socially Aware’ Robot Studies Behavior Of Stanford Students"

[01/17/2017] Our work in Quartz: "Stanford scientists are teaching a robot how not to be awkward in public"

[01/17/2017] Our work in Voice of America: "US Scientist Trains Robot to Learn to Be More Human"

[01/17/2017] Our work in Viceland TV: "THE AI ROBOT THAT RESPECTS PERSONAL SPACE"

[08/01/2016] JR has been featured in Stanford Daily! Link

[07/27/2016] JR has been featured in BBC NEWS! Link

[06/07/2016] JR has been featured in ABC7 NEWS! Link

[06/02/2016] JR has been featured in TechCrunch! Link

[05/17/2016] JR has been featured by the MIT Technology Review! Link

[05/10/2016] JR has been featured in the financial times! Link

[05/05/2015] JR on PBS

[04/15/2015] First TV for JR (ScienFi channel)

[03/01/2015] First day out on Stanford campus for JR!

Team

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	Agrim Gupta Master Student agrim at stanford dot edu
Noriaki Hirose Visiting Scholar, Stanford Toyota Centeral R&D Labs hirose 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
	Lin Sun Visiting Student, Stanford PhD Candidate, HKUST sunlin1 at stanford dot edu

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