Mobile Robot Cloud Teleoperation and Sensor Fusion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current mobile robot systems lack efficient integration with cloud computing for remote operation, navigation, and data management, limiting their ability to effectively interact with humans and navigate complex environments.
Innovation Solution
A mobile robot system incorporating a controller, a cloud computing service, and a remote computing device that enables remote teleoperation, map production, and data storage, along with a portal for user interaction, utilizing a holonomic drive system and advanced sensor systems for navigation and obstacle avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If mobile robot systems use traditional local computing and control, then system simplicity is maintained, but remote operation capability and cloud integration are limited
Solution Approach 1:
The patent introduces a cloud computing service as an intermediary between the mobile robot and remote computing devices. The cloud service receives commands from remote devices, processes them, and sends control signals to the robot, enabling remote operation without direct peer-to-peer connection and reducing the complexity of remote communication infrastructure.
Solution Approach 2:
The system transitions from local-only computing to a distributed computing architecture by adding the cloud dimension. The robot controller, cloud computing service, and remote computing devices operate across different spatial and functional dimensions, allowing versatile remote operation while distributing system complexity across multiple layers.
2Productivity
If mobile robots operate autonomously without cloud integration, then operational independence is maintained, but collaboration and data sharing capabilities are reduced
Solution Approach 1:
The cloud computing service provides universal communication and coordination functions for multiple robots and users. It handles task assignment, data sharing, and collaboration protocols in a unified manner, enabling efficient multi-robot collaboration without requiring complex peer-to-peer communication infrastructure between each robot pair.
3Measurement precision
If mobile robots use basic navigation systems, then system simplicity is maintained, but navigation precision in complex environments deteriorates
Solution Approach 1:
The patent combines multiple sensor types (cameras, LIDAR, inertial sensors, wheel encoders) into an integrated sensor system that feeds data to the controller. The controller fuses this multi-source data to achieve high navigation precision in complex environments, overcoming the limitations of individual sensors while managing complexity through integrated processing.
4Adaptability or versatility
If mobile robots store data locally, then data access speed is maintained, but data management scalability and remote access capability are limited
Solution Approach 1:
The patent segments data storage and management into local and cloud components. The robot stores frequently accessed data locally for immediate access, while the cloud computing service provides scalable storage for large datasets and historical records. This segmentation enables both fast local access and scalable remote access, with the cloud serving as supplemental storage that doesn't bottleneck real-time operations.
Data Source
AI summary
A robot system includes a mobile robot having a controller executing a control system for controlling operation of the robot, a cloud computing service in communication with the controller of the robot, and a remote computing device in communication with the cloud computing service. The remote computing device communicates with the robot through the cloud computing service.