Robot Wireless Capacity Control Through Location-Aware Access Management
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Solution Overview
Problem
Existing wireless network capacity management systems for robots are inefficient in ensuring sufficient network capacity for data transfer and control signal reception, leading to potential congestion and impaired robot functionality.
Innovation Solution
An apparatus and method that identify robots requiring wireless network capacity, determine their locations, and obtain information on available capacity, allowing for controlled access point management to maintain sufficient capacity by limiting robot access, ensuring continuous data exchange with control centers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If robots are allowed to freely access the wireless network without capacity management, then ease of operation is improved, but network congestion occurs and reliability deteriorates
Solution Approach 1:
The system continuously monitors network capacity usage by robots and provides feedback to the control center. When network capacity thresholds are approached, the system sends commands to robots to relocate to different areas, creating a closed-loop control system that maintains network reliability while allowing operational freedom within limits.
Solution Approach 2:
The system dynamically adjusts robot access to the wireless network based on real-time capacity conditions. Rather than static access control, robots can freely access the network when capacity is sufficient, but are dynamically redirected when congestion is detected, allowing the system to adapt to changing network conditions.
2Reliability
If the number of robots using a given access point is limited to maintain network capacity, then reliability is improved, but productivity may be affected due to location constraints
Solution Approach 1:
The workspace is segmented into multiple zones, each with its own access point and capacity characteristics. Robots are redirected to specific zones based on network capacity conditions, allowing the system to distribute load across multiple segments rather than limiting access at a single point, thereby maintaining both reliability and productivity.
3Object-affected harmful factors
If robot locations are controlled to maintain network capacity, then network congestion is prevented, but robot mobility is restricted
Solution Approach 1:
Different location constraints are applied to different robots based on their specific tasks, priorities, and network usage patterns. Rather than uniform location control, the system applies localized quality control where high-priority robots may have greater location flexibility while low-priority robots face stricter constraints, maintaining adaptability while preventing congestion.
Data Source
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AI summary
The application relates to apparatus, methods and computer programs for controlling wireless network capacity. The apparatus comprises means for: identifying one or more robots that require wireless network capacity and identifying the locations of the one or more robots that require wireless network capacity. The means may also be configured to obtain information indicative of available wireless network capacity in the locations corresponding to the locations of the one or more robots. This information could provide an indication of the likelihood of congestion within the wireless network. The congestion could be disadvantageous as this may affect the transfer of information between the one or more robots and one or more control centres. Therefore the available wireless network capacity may affect whether or not the robots can correctly perform the functions that have been assigned to them. The means may also be configured to enable control of the location of one or more robots that require wireless network capacity so as to enable the one or more robots to maintain sufficient wireless network capacity.