Stanford’s ‘Jackrabbot’ paves way for social robotics

Caitlin Ju for The Stanford Daily:  Stanford researchers in the Computational Vision and Geometry Lab have designed an autonomously navigating robot prototype that they say understands implicit social conventions and human behavior. Named “Jackrabbot” after the swift but cautious jackrabbit, the visually intelligent and socially amicable robot is able to maneuver crowds and pedestrian spaces.

A white ball on wheels, the Jackrabbot is built on a Segway system and contains a computing unit and multiple sensors that acquire a 3-D structure of the surrounding environment. 360-degree cameras and GPS also enhance the robot’s navigation and detection capabilities.

To interact smoothly in public settings, the robot has to know how to avoid someone in a natural way, how to yield the right-of-way and how to leave personal space, among other skills.  Cont'd...

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Maplesoft - Free Whitepaper: Developing a Robot Model using System-Level Design

Maplesoft - Free Whitepaper: Developing a Robot Model using System-Level Design

This paper uses NAO, the humanoid robot from Aldebaran Systems, to demonstrate how MapleSim can be used to develop a robot model, and how the model can be further analyzed using the symbolic computation engine within Maple.