Ruby Robo

Ruby – The Robot Waitress

IT’s Time for Robots

Hello World

Ruby – The Robot Waitress

Designed to deliver food to customers at restaurant : Ruby has been designed to efficiently work in restaurant as servers. A fully charged Ruby can work upto 6 hours continuously.

Beautiful design and aesthetics : Ruby is designed to be attractive and people-friendly. It’s shape, blinking eyes, height and body structure has been designed to resemble human so that people fall in love with a robotic waiter straightway.

Payload capacity : Ruby has an attached tray that can support weight of food upto 10 kg. Speed of Ruby has been optimized to 0.3 m/s per second to serve all kinds of food.

Autonomous navigation : Ruby can navigate around the restaurant premises on its own following a magnetic strip. With in-built obstacle sensor, it also avoids static and dynamic obstacles. The restaurant must not contain uneven surfaces and it must be flat.

9 USP (Unique Selling Proposition)

Intelligent Welcome, Save Manpower

1

Smart Delivery
2

Menu Introduction
3

Dish Return
4

Trackless Navigation
5

Auto Docking
6

Autonomous Obstacle Avoidance
7

Double Tray
8

Mobile Ads
9

Reception Work

Product Feature

Automatic Delivery

Precision navigation to deliver dishes to designated points; The shock absorption system effectively enhances the stability of the drive process and prevents the dishes from spilling out.

About Menu

Recommend today's special with combo sets at clients' request

Dish Return

Hang around designated area to collect dirty dishes until loading full. Super large capacity by the help of multiple sesors, greatly reducing restaurant waiters'repetitive work pressure

Trackless Navigation

Lidar + infrared sensor + ultrasonic sensor

High precision indoor navigation, resonably select the best route among all.

Auto Docking

Once time set, auto back the charging pile, super long standby time up to 12 hour embedded with lithium battery.

Automatic Obstacle Avoidance

Carried with multiple sensor, robot could be autonomously positioned in the enviroment. Through the deep optimization of the obstacle avoidance alogorithm, it can perceive the real-time enviromental changes around it, bypass the obstacle in the planning path.

Press Release