Robot Path Planning for Stable Cloud Radio Communication
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Solution Overview
Problem
Current robotic systems lack effective cloud-based coordinated control due to unreliable wireless/wired links and strategic decision-making, limiting the potential of cloud robotics in industrial environments.
Innovation Solution
A method and system that process data related to a robotic device's path of movement to improve radio communication by updating the path based on processed data, utilizing a cloud platform to optimize signal strength, bandwidth, and signal-to-noise ratio, and adjusting the orientation, speed, and coordinates of the robotic device to enhance communication efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If cloud-based control is implemented for robotic devices, then centralized processing and coordination capabilities are improved, but communication reliability and latency are worsened due to unreliable wireless/wired links
Solution Approach 1:
The system pre-calculates multiple alternative paths of movement before the robotic device begins its operation. These pre-computed paths account for potential communication failures and environmental constraints, allowing the device to switch to backup paths without real-time cloud communication when needed.
Solution Approach 2:
A local intermediary system processes path updates and communication data between the robotic device and cloud platform. This intermediary can operate autonomously when cloud connection is unreliable, buffering and forwarding data when connection is available, thus mediating the communication reliability issue.
2Productivity
If the robotic device moves quickly along its path, then productivity is improved, but radio communication quality is worsened due to movement-induced signal variations
Solution Approach 1:
The system dynamically adjusts the robotic device's movement speed based on real-time radio communication quality assessments. When communication quality degrades, the device automatically slows down to maintain connection stability; when quality improves, speed increases to maximize productivity.
Solution Approach 2:
The system continuously monitors radio communication quality metrics and feeds this information back to adjust the path execution speed. This closed-loop feedback mechanism ensures that productivity is optimized while maintaining communication reliability throughout the device's movement.
3Reliability
If the path of movement is frequently updated to optimize communication, then communication efficiency is improved, but device complexity increases due to additional processing requirements
Solution Approach 1:
The path update process is segmented into discrete evaluation points along the robotic device's trajectory. At each point, only specific communication parameters are assessed and updated, rather than continuously recalculating the entire path. This segmentation reduces processing complexity while maintaining communication efficiency.
4Extent of automation
If cloud platform processing is used for path optimization, then centralized coordination is improved, but communication bandwidth requirements increase
Solution Approach 1:
The system extracts and processes only the essential path optimization parameters locally on the robotic device, transmitting only these critical data points to the cloud platform. This extraction approach reduces the volume of communication data while maintaining centralized coordination capabilities for the most important decisions.
Data Source
AI summary
We generally describe a method comprising: processing (S602) data relating to a path of movement of a robotic device (122) comprising or coupled to a sensor (124) in radio communication with a cloud platform (112); and updating (S604), based on the processed data, the path of movement to improve the radio communication.