Federated Multi-Drone Path Planning With Hierarchical Sensor Fusion
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Solution Overview
Problem
Current path planning methods for unmanned vehicles face challenges in optimizing navigation in complex environments, particularly in unknown or partially known areas, as they often require extensive knowledge of the environment and may not be optimized for diverse sensor data from multiple sources.
Innovation Solution
A system that integrates heterogeneous information from multiple sensors using a hierarchical platform, where aerial, ground, and stationary robots acquire and process information at different resolutions and noise levels, and a gateway powered by machine learning models aggregates this data to adjust paths dynamically, enabling efficient and optimized path planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple heterogeneous sensors from multiple unmanned vehicles are used to gather information, then the coverage and diversity of environmental information is improved, but the complexity of integrating and processing this heterogeneous information increases
Solution Approach 1:
The system segments the information gathering task by assigning different sensors (aerial, ground, stationary) to different spatial zones and resolution levels. Each sensor type captures environmental information within its specific field of view and resolution characteristics, dividing the complex integration task into manageable segments that can be processed hierarchically
Solution Approach 2:
The system implements nested information integration where field of views are hierarchically nested based on hierarchical order of unmanned vehicles. The processing device integrates information from multiple sensors by nesting their respective fields of view, with higher-level vehicles providing broader context and lower-level vehicles providing detailed local information, thereby managing complexity through hierarchical organization
2Adaptability or versatility
If path planning is performed in unknown or partially known environments, then the adaptability to diverse environments is improved, but the reliability of path planning decreases due to lack of environmental knowledge
Solution Approach 1:
The system performs preliminary information gathering using multiple sensors before path planning begins. The processing device integrates heterogeneous sensor information to create an initial environmental model, and uses this pre-acquired information to inform path planning decisions, thereby improving reliability in unknown environments through advance information collection
Solution Approach 2:
The system implements continuous feedback loops where the processing device analyzes integrated sensor information, determines adjustments required to paths, and generates new commands for unmanned vehicles. This closed-loop feedback mechanism allows the system to adapt to environmental changes in real-time while maintaining reliability through continuous verification and adjustment based on actual sensor data
3Productivity
If traditional path planning methods are used without heterogeneous sensor integration, then the device complexity is reduced, but the productivity and mission performance of unmanned vehicles decreases
Solution Approach 1:
The processing device serves multiple functions: it integrates heterogeneous information from multiple sensors, analyzes integrated information against assigned paths, determines path adjustments, and generates commands for unmanned vehicles. This multi-functional approach consolidates what would otherwise require separate systems, managing complexity while enhancing productivity through unified information processing and control
Data Source
AI summary
Disclosed herein is a device for facilitating managing of paths for unmanned vehicles. Further, the device is configured to be communicatively coupled with the unmanned vehicles. Further, the device comprises a communication device configured for receiving heterogeneous information from sensors and transmitting commands to unmanned vehicles. Further, the device comprises a processing device communicatively coupled with the communication device. Further, the processing device is configured for integrating the heterogeneous information, generating integrated information based on the integrating, analyzing the integrated information based on paths assigned to the unmanned vehicles for performing a mission, determining an adjustment required to be made in the paths by the plurality of unmanned vehicles, and generating the commands for the unmanned vehicles. Further, the device comprises a storage device communicatively coupled with the processing device. Further, the storage device is configured for storing the paths.