Cloud Indoor Robot Control Using Shared Facility Maps
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Solution Overview
Problem
The high cost of manufacturing indoor autonomous robots is due to the need for various sensors and processors for navigation and service provision, as well as the requirement for users to generate and maintain indoor maps, which is resource-intensive and costly.
Innovation Solution
A cloud-based system that generates and manages indoor maps for facilities, allowing service providers to pre-create maps and control multiple service robots through a cloud service, reducing the need for expensive sensors and equipment on individual robots, and enabling efficient sharing of services within a facility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If various sensors and processors are included for autonomous driving and service provision, then the robot can perform navigation and obstacle avoidance functions, but the manufacturing cost increases significantly
Solution Approach 1:
The patent introduces a server as an intermediary that performs complex path planning and obstacle avoidance calculations remotely. The robot includes a communication unit to exchange data with the server, which processes sensing information and generates navigation paths. This transfers computational burden from the robot's onboard processor to the server, reducing the robot's hardware requirements and manufacturing cost while maintaining autonomous driving capability.
Solution Approach 2:
The patent uses pre-generated indoor maps stored on the server as a copy of the physical environment. Instead of requiring the robot to process and interpret raw sensor data in real-time for navigation, the system uses pre-processed map data that can be efficiently queried and followed. This copying approach simplifies the robot's onboard processing requirements.
2Measurement precision
If users generate and maintain indoor maps using measurement equipment, then accurate navigation is achieved, but resource consumption and cost increase
Solution Approach 1:
The patent implements preliminary action by having the server generate and store indoor maps in advance before the robot needs them for navigation. The mapping process is performed separately and beforehand, creating reusable map data that the robot can query during operation. This separates the resource-intensive map generation process from the robot's operational energy consumption.
Solution Approach 2:
The server acts as an intermediary that handles the resource-intensive task of indoor map generation and maintenance. The robot communicates with the server to obtain pre-generated maps, transferring the computational and resource burden of map creation from the robot to the server infrastructure.
Data Source
AI summary
A method and system for controlling an indoor autonomous robot. A method of controlling an indoor autonomous driving of a robot in a cloud system includes receiving, by the cloud system, first sensing data that is generated by a mapping robot autonomously driving in a target facility using a first sensor that detects the first sensing data with respect to an inside of the target facility; generating an indoor map of the target facility based on the first sensing data; receiving, from a service robot present in the target facility through a network, second sensing data that is generated by the service robot using a second sensor that detects the second sensing data with respect to the inside of the target facility; and controlling an indoor autonomous driving of the service robot with respect to the target facility based on the second sensing data and the generated indoor map.