Rugged Terrain Route Planning With Drone-Based Mapping
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Solution Overview
Problem
Conventional navigation systems fail to provide adequate route optimization for vehicles traversing rugged terrain, especially in remote areas with limited road infrastructure, as they do not utilize real-time data from environment observations and vehicle fleets to select the most suitable vehicles based on off-road capabilities, payload, and terrain conditions.
Innovation Solution
A system that uses drones and vehicle sensors to collect real-time terrain data, combining it with existing map data, to optimize routes and select the appropriate vehicle for delivery tasks, considering terrain difficulties, obstacles, and vehicle characteristics, and continuously improves map information through feedback from fleet vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional navigation systems are used for rugged terrain, then urban navigation functionality is maintained, but route optimization for off-road terrain is inadequate
Solution Approach 1:
The navigation system dynamically adapts to different terrain types by switching between conventional map-based navigation for urban areas and sensor-based real-time terrain analysis for rugged off-road environments. The system continuously adjusts its navigation approach based on detected terrain characteristics, making it both reliable for standard routes and adaptable for challenging terrains.
Solution Approach 2:
A fleet of vehicles acts as intermediaries by collecting and sharing real-time terrain data through vehicle-to-vehicle communication networks. This crowd-sourced terrain information enhances the navigation system's ability to optimize routes for rugged terrain without requiring each individual vehicle to have complete terrain knowledge beforehand.
2Loss of information
If online navigation services are used, then real-time route updates are available, but navigation in remote areas with few other vehicles is insufficient
Solution Approach 1:
The system performs preliminary terrain assessment using onboard sensors (LIDAR, cameras, radar) before navigation updates are needed. By proactively mapping and characterizing terrain features in advance, the vehicle builds a local terrain database that can be used offline in remote areas without requiring real-time communication with other vehicles or servers.
Solution Approach 2:
Each vehicle independently generates and utilizes its own terrain data through onboard sensors and processors. The system is self-sufficient in remote areas by relying on its own sensing capabilities and previously collected data, rather than depending on other vehicles for navigational information.
3Productivity
If vehicle fleet data is not utilized, then individual vehicle navigation is simple, but route optimization for rough terrains is limited
Solution Approach 1:
The navigation system serves multiple functions: it performs standard navigation, collects terrain data, shares information with the fleet, and optimizes routes based on aggregated knowledge. This multi-functionality allows the system to improve delivery efficiency across the entire fleet while each vehicle maintains its own independent navigation capability.
Solution Approach 2:
The system implements feedback loops where terrain data collected by each vehicle is shared with the fleet, and this aggregated information feeds back into route optimization algorithms. This continuous feedback mechanism progressively improves route selection for rugged terrain, enhancing overall delivery efficiency without requiring complex centralized control.
Data Source
AI summary
Method and system for providing a mobility service is described. The mobility service can include delivering goods in rough terrain, rural areas, and other similar environments, by selecting and configuring vehicles for terrain considerations based on known and dynamically changing information. The disclosed system can include a vehicle configured with a deployable autonomous drone, and can determine optimized vehicle routes to remote locations using the deployable drone and vehicle navigation sensors, for real time mapping that can be combined with existing map/terrain data. The terrain data may also be sent to a vehicle in a vehicle fleet, and/or to a cloud-based server, and be used to compute the best available vehicles designed for the mobility service. The system may deploy one or more mobility solutions, collect telematics, road information, navigational data, and other information during the delivery. This feedback may then be used for future mobility services.