Airport Service Robot Control for Wandering User Recognition
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Solution Overview
Problem
Existing methods for providing airport services through robots are inefficient due to the high cost of high-tech devices and the limited number of robots in airports, leading to suboptimal navigation services as robots often need to cover all areas of the airport.
Innovation Solution
A method that identifies behavior direction recognition in airport users by learning their movement information, determining if services are necessary, and using AI processing to control intelligent robot devices to approach users who require services, thereby optimizing service delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the number of airport robots is increased to provide better services, then service quality improves, but device cost and system complexity increase
Solution Approach 1:
The robot autonomously identifies users needing services through AI processing of movement information, automatically determines service requirements, and navigates to provide services without human intervention, enabling the system to serve itself and reduce the need for multiple robots
Solution Approach 2:
The system changes the operational parameters of individual robots by dynamically adjusting their service areas and targets based on real-time analysis of user movement patterns, allowing limited robots to efficiently cover varying service needs through parameter optimization rather than increasing robot quantity
2Area of stationary object
If robots move to all areas of the airport to provide navigation services, then service coverage improves, but service efficiency deteriorates
Solution Approach 1:
The system performs preliminary analysis of user movement information to identify potential service requesters before robots arrive, pre-determines which users need services and their locations, allowing robots to directly navigate to target users rather than searching all areas, thus maintaining coverage while improving efficiency
Solution Approach 2:
The system continuously monitors and analyzes user movement patterns, using this feedback to dynamically adjust robot navigation targets and service areas, ensuring robots respond to actual service needs rather than uniformly covering all areas, thereby optimizing both coverage and efficiency
3Measurement precision
If AI processing is implemented to identify service requesters, then service precision improves, but computational requirements and system complexity increase
Solution Approach 1:
The system extracts only the critical features from user movement information that are necessary for identifying service requesters, such as movement patterns and behavioral characteristics, rather than processing all available data, thereby achieving high service precision while reducing computational complexity through selective feature extraction
Data Source
AI summary
A method of identifying a behavior direction recognition based service requester includes a plurality of intelligent robot devices arranged in the airport and a server controlling movement of one or more intelligent robot devices of the plurality of intelligent robot devices. The intelligent robot includes a communication unit transmitting movement information of an airport user moving in the airport from the server, and a processor configured to receive the movement information of the airport user from the communication unit, learn movement of the airport user, recognize a wandering state of the airport user based on the learned movement of the airport user, and move to the airport user based on a result of the recognition. The intelligent robot device may be associated with an artificial intelligence module, an unmanned aerial vehicle (UAV), a robot, an augmented reality (AR) device, a virtual reality (VR) device, and devices related to 5G services.