Autonomous Sensor Fusion for Reliable Artificial Vision Navigation
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Solution Overview
Problem
Conventional autonomous systems rely heavily on human intervention and are not fully autonomous, lacking the ability to operate independently with advanced autonomy.
Innovation Solution
The implementation of a Hierarchical Intelligence Model (HIM) that utilizes computational input and output on structural and behavioral properties, incorporating vision and image processing, and sensor data fusion from RADAR, LIDAR, and other sensors to enable autonomous functioning in self-driving systems, including UAS drones and military vehicles, allowing for advanced awareness and decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional autonomous systems are designed with human-in-the-loop interactions, then system reliability is improved, but extent of automation deteriorates
Solution Approach 1:
The system segments autonomous operation into multiple levels (reflexive, imperative, adaptive, autonomous, cognitive) with different degrees of human involvement. Each level handles specific types of decisions, allowing the system to achieve high automation for routine tasks while maintaining human oversight for complex situations, thus resolving the contradiction between automation extent and reliability.
Solution Approach 2:
The system dynamically adjusts the level of human involvement based on operational context, task complexity, and system confidence. The human-in-the-loop interaction is not static but adapts in real-time, increasing automation for predictable scenarios and reducing it for uncertain situations, thereby maintaining both high automation and reliability.
2Measurement precision
If sensor data fusion from multiple sources is implemented, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The sensor fusion system is segmented into modular processing units, each handling specific sensor types or processing functions. This modular architecture allows the system to integrate multiple sensor sources while managing complexity through organized, independent processing modules that can be developed and maintained separately.
Solution Approach 2:
The patent introduces an intermediary processing layer that standardizes and harmonizes data from diverse sensor sources before integration. This intermediary layer provides a unified interface and common data format, reducing the complexity of direct multi-sensor integration while maintaining high measurement precision through coordinated processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables self-aware mobile systems to operate with improved autonomy, providing advanced awareness and decision support for automated guidance and collision avoidance, and enabling full automation in vehicles and aircraft, enhancing their ability to handle unanticipated events without human intervention.
Implementation Method 1
a plurality of sensors, comprising at least RADAR and LIDAR, adapted to obtain information about surroundings
Implementation Method 2
a plurality of sensors, comprising at least RADAR and LIDAR, adapted to obtain information about surroundings
Data Source
AI summary
Embodiments may provide techniques for operating autonomous systems with improved autonomy so as to operate largely or completely, autonomously. For example, in an embodiment, a self-aware mobile system may comprise a vehicle, vessel, or aircraft comprising a plurality of sensors, comprising at least RADAR and LIDAR, adapted to obtain information about surroundings of the vehicle, vessel, or aircraft, and at least one computer system configured to receive data from the plurality of sensors, perform fusion of the received data to generate artificial vision data representing the surroundings of the vehicle, vessel, or aircraft, and to use the artificial vision data to provide autonomous functioning of the vehicle, vessel, or aircraft.