Unmanned Robot Coordination for UAM Ground Collision Prevention
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Solution Overview
Problem
Urban air mobility vehicles face collisions with other objects and workers during ground operations, and passengers may be confused about moving paths, leading to potential accidents and safety issues.
Innovation Solution
An unmanned robot system that includes a processor, communication module, and storage medium to control unmanned robots that move in synchronization with the vehicle to prevent collisions and guide passengers safely through predefined paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If unmanned robots are deployed to surround and monitor the urban air mobility vehicle during ground operations, then collision prevention capability is improved, but device complexity and operational cost increase
Solution Approach 1:
The monitoring system is divided into multiple independent unmanned robots that can be deployed in different positions around the vehicle. Each robot independently performs monitoring tasks, allowing the system to achieve comprehensive coverage while maintaining modular complexity that can be scaled according to needs.
Solution Approach 2:
The unmanned robots are designed with multi-functional capabilities including collision monitoring, passenger guidance, and obstacle detection. This universal design allows a single robot platform to perform multiple tasks, reducing overall system complexity compared to having separate specialized systems for each function.
2Ease of operation
If unmanned robots are used to guide passengers along predefined paths between take-off/landing areas and gates, then passenger safety and clarity are improved, but operational complexity increases
Solution Approach 1:
The unmanned robots autonomously navigate predefined paths and independently guide passengers without requiring constant human intervention. The robots self-manage their movement along designated routes and provide guidance information, reducing the operational burden on human controllers while maintaining clear passenger direction.
Solution Approach 2:
The guidance paths for the unmanned robots are predefined in advance based on optimal routes between take-off/landing areas and gates. This preliminary planning of navigation paths simplifies real-time operational complexity while ensuring passengers receive clear and efficient guidance.
3Measurement precision
If multiple unmanned robots operate in synchronization with the vehicle, then real-time monitoring effectiveness is improved, but coordination complexity and communication requirements increase
Solution Approach 1:
The unmanned robots implement feedback mechanisms where each robot continuously reports its position, sensor data, and status to a central coordination system. This feedback loop enables real-time monitoring accuracy while the automated coordination algorithm manages the complexity of synchronizing multiple robots, converting coordination challenges into manageable information processing tasks.
Data Source
AI summary
A unmanned robot for an urban air mobility vehicle includes: a processor; a communication module; and at least one storage medium operatively connected to the processor, wherein a program configured to be executable by the processor is recorded in the at least one storage medium, wherein the program may include commands for a control module configured to control performance of an operation according to the received command according to one of a first mode and a second mode, wherein the first mode may be a mode in which one or more of the unmanned robots move in synchronization with the urban air mobility vehicle, and the second mode may be a mode in which one or more of the unmanned robots are arranged on a road surface between a take-off and landing area of the urban air mobility vehicle and a gate to provide a moving path.