AI Robot Guidance Control for Dynamic Crowd Urgency
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Solution Overview
Problem
In airports and multiplexes, robots struggle to effectively provide guidance services due to limited zone allocation, leading to inadequate coverage during crowded situations and inefficient movement when leaving allocated zones.
Innovation Solution
An artificial intelligence server determines the zone with the highest guidance urgency based on situation information, using image recognition models to calculate user density and prioritize robot movement, ensuring efficient guidance service distribution and maintaining robot formation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a robot is located only in a zone allocated thereto, then the robot can maintain stable service in its allocated zone, but it cannot actively cope with situations where people are densely crowded and more guidance services are needed
Solution Approach 1:
The robot's zone allocation is made dynamic rather than static. The server continuously monitors crowd density in real-time and dynamically adjusts robot positions by transmitting movement commands to robots, allowing them to transition between allocated zones and crowded zones as needed. This resolves the contradiction by enabling robots to maintain stability in their base zones while adapting to temporary crowd situations.
Solution Approach 2:
The system implements feedback through continuous crowd density monitoring using image recognition models. The server receives real-time density information from multiple zones, compares it against thresholds, and triggers robot movement when density exceeds thresholds. This feedback loop enables the system to respond adaptively to changing crowd conditions while maintaining organized zone management.
2Productivity
If a robot leaves a zone allocated thereto and wanders, then the robot can provide guidance services in crowded areas, but proper guidance service may not be provided in the allocated zone
Solution Approach 1:
Multiple robots share the responsibility of providing guidance services across different zones. When one robot leaves its allocated zone to serve a crowded area, other robots in the system can compensate by providing services in the originally allocated zone. This multi-functionality ensures continuous service coverage throughout the facility regardless of individual robot positions.
Solution Approach 2:
The server continuously monitors crowd density in both the robot's current zone and its allocated zone. Before authorizing a robot to leave its allocated zone, the system checks whether another robot can cover the allocated zone. This feedback mechanism ensures that service reliability is maintained in allocated zones even when robots are deployed to crowded areas.
3Productivity
If multiple robots are deployed to densely crowded areas, then guidance service efficiency is improved, but robot arrangement must be optimized to maintain reception sensitivity
Solution Approach 1:
The server applies different control strategies to different spatial locations. In densely crowded zones, multiple robots are deployed to handle high user volumes. In less crowded zones, fewer robots are positioned to maintain optimal reception sensitivity. This local quality approach optimizes service efficiency in crowded areas while maintaining operational simplicity in less demanding areas.
Solution Approach 2:
The system dynamically changes robot deployment parameters based on crowd density. When density exceeds a threshold, the server authorizes additional robots to leave their allocated zones and join the crowded area. The number of robots in each zone becomes a variable parameter that changes with crowd conditions, optimizing service efficiency without requiring complex manual arrangement control.
Data Source
AI summary
An artificial intelligence server for controlling a plurality of robots using artificial intelligence includes a communication unit configured to receive a captured image of each of a plurality of zones and a processor configured to acquire situation information of each zone based on the received image, acquire degrees of guidance urgency respectively corresponding to the plurality of zones based on the acquired situation information of each zone, determine whether there is a degree of guidance urgency greater than a predetermined value in the acquired degrees of guidance urgency, and, when there is a degree of guidance urgency greater than the predetermined value, transmit a first control command for moving one or more robots to a zone corresponding to the degree of guidance urgency.