Multi-Robot Deployment Control for Variable Crowd Density
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional robots deployed in areas like airports or train stations are often underutilized as they are limited to specific zones and may wander off, failing to efficiently provide services due to inadequate control mechanisms.
Innovation Solution
A system that uses a communication unit and processor to analyze images of deployment areas, calculate user density, and redistribute robots based on workload and location variations, ensuring optimal service distribution by prioritizing high-density areas and adjusting robot positions dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robots are deployed in specific assigned areas, then service coverage is ensured in those areas, but robot utilization efficiency deteriorates when user density varies across different areas
Solution Approach 1:
The patent implements dynamic area assignment where robot working areas are not fixed but are periodically adjusted based on real-time user density measurements. The processor calculates user density in multiple areas and reallocates robots to high-density areas, making the system adaptable to changing conditions rather than relying on static area assignments.
Solution Approach 2:
The system continuously monitors user density in different areas using sensors or image processing, feeds this information back to the processor, and uses the feedback to adjust robot deployment. This closed-loop control ensures that service coverage is maintained while optimizing robot utilization based on actual demand patterns.
2Adaptability or versatility
If robots are allowed to move freely in the entire area, then robot flexibility is improved, but service reliability deteriorates as robots may stray from their working areas
Solution Approach 1:
The patent dynamically adjusts robot working areas based on real-time user density measurements. Instead of allowing completely free movement or restricting to fixed areas, the system periodically recalculates optimal working areas and assigns robots to these dynamic zones. This maintains service reliability through controlled deployment while providing flexibility through adaptive area reassignment.
3Reliability
If more robots are deployed to high-density areas, then service quality in those areas is improved, but the complexity of robot management and control increases
Solution Approach 1:
The patent implements autonomous robot deployment where robots automatically navigate to their assigned areas and begin service operations without manual intervention. The system self-manages robot allocation by having robots report their status and the controller automatically reassigning them based on density measurements, eliminating the need for complex manual management protocols.
Solution Approach 2:
The system uses automated feedback loops where robots report their operational status and the controller receives real-time density information, then automatically makes deployment decisions. This automated feedback mechanism simplifies management complexity compared to manual coordination while maintaining high service quality through responsive reallocation.
Data Source
AI summary
Disclosed is a device and method of controlling a plurality of robots. According to an embodiment, a device and method of controlling a plurality of robots periodically measures variations in the density of people per unit quarter and deploys a robot, which is positioned close to a high-density unit quarter and has a low workload, in the unit quarter. According to an embodiment, the artificial intelligence (AI) module may be related to unmanned aerial vehicles (UAVs), robots, augmented reality (AR) devices, virtual reality (VR) devices, and 5G service-related devices.