UV Movement and Data Control System for Autonomous Hazard Detection
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Solution Overview
Problem
Current unmanned vehicle (UV) systems lack efficient integration into workflows, particularly in ambiguous environments, due to limitations in movement and data control, which hinders their utilization in various tasks such as package delivery, agriculture, and pipeline inspection.
Innovation Solution
A UV movement and data control system that utilizes a hardware-implemented mission manager and event detector to assign missions, manage UVs, sensors, and crew, and adjust movement plans in real-time based on detected events, incorporating sensors like video cameras, gas detectors, and infrared cameras for tasks like pipeline leak detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If UV systems use remote controlled operation with line-of-sight requirement, then operator can directly control UV behavior, but operator exposure to hazardous environments increases and operational efficiency decreases
Solution Approach 1:
The UV system performs self-service through autonomous operation capabilities. The vehicle can independently navigate, detect events using onboard sensors, and execute missions without continuous human intervention. This eliminates the need for operators to be exposed to hazardous environments while maintaining reliable control through automated decision-making algorithms and real-time sensor processing.
2Object-affected harmful factors
If UV systems implement fully autonomous operation, then operator exposure to hazardous conditions is reduced, but system complexity and difficulty of detecting and measuring events increase
Solution Approach 1:
The autonomous UV system is segmented into distinct functional modules: navigation module for path planning, sensor module for environmental perception, event detection module for identifying significant occurrences, and control module for executing decisions. This modular architecture manages system complexity by allowing each component to specialize in specific tasks while communicating through standardized interfaces.
Solution Approach 2:
An event detection and filtering system acts as an intermediary between raw sensor data and autonomous decision-making. This intermediary layer processes sensor inputs, identifies meaningful events, and translates them into actionable commands, thereby managing the complexity of autonomous operation without requiring direct human intervention in hazardous environments.
3Object-affected harmful factors
If UV systems use task following operation without line-of-sight, then operator safety is improved, but real-time adaptive control capability is reduced
Solution Approach 1:
The UV system implements continuous feedback loops where onboard sensors constantly monitor environmental conditions and vehicle status. This feedback is processed in real-time to detect events and trigger adaptive responses. The system can adjust its behavior dynamically based on sensor inputs, maintaining versatility and adaptability without requiring operator line-of-sight, thereby ensuring both operator safety and real-time control capability.
Data Source
AI summary
Unmanned vehicle (UV) movement and data control may include controlling a UV according to a movement plan. Formatted movement and status metadata may be received from a sensor of the UV during movement of the UV. The movement and status metadata may include time and location information for the UV during the movement of the UV. An unformatted data stream may be received from the sensor of the UV. The time and location information may be injected into metadata of the unformatted data stream to generate a time and location correlated (TLC) stream. The TLC stream may be analyzed to identify an event related to the UV, and a notification related to the event may be generated.