Mobile Path Planning for Low-Connectivity Navigation Zones
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Solution Overview
Problem
Existing path planning systems for mobile devices, such as aerial vehicles, rely on cloud-based solutions that assume perfect connectivity, which is not always feasible, leading to potential deadlocks and safety issues when encountering dynamic obstacles in zones with insufficient connectivity.
Innovation Solution
A method that allows mobile devices to switch between global path planning in a communication network and local path planning onboard, using a protocol that partitions regions into sub-regions based on connectivity levels, ensuring the device always has a safe path by maintaining a safe subgraph and recalculating locally when connectivity drops below a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cloud-based path planning is used, then path planning accuracy is improved, but system reliability deteriorates in low-connectivity zones
Solution Approach 1:
The system segments path planning into two parts: global path planning performed in the cloud using comprehensive map data, and local path planning performed onboard using a pre-loaded subgraph. This segmentation allows the mobile device to maintain autonomous path planning capability in low-connectivity zones while still benefiting from accurate cloud-based planning when connected.
Solution Approach 2:
The system performs preliminary action by pre-loading a subgraph (a simplified version of the complete map) onto the mobile device before it enters low-connectivity zones. This preparation ensures that the device has the necessary path planning data available locally, maintaining reliability even when cloud connectivity is unavailable.
2Extent of automation
If the mobile device stores the entire map for local re-planning, then path planning autonomy is improved, but memory consumption increases
Solution Approach 1:
The system extracts only the essential path planning data needed for autonomous operation by creating and storing a subgraph - a simplified representation of the complete map that contains only the critical connectivity information required for local re-planning. This extraction reduces memory consumption from hundreds of MBs/GBs to a manageable size while preserving the autonomy needed for safe operation in low-connectivity zones.
3Reliability
If global path planning is used, then collision-free paths are obtained, but adaptability to dynamic obstacles deteriorates
Solution Approach 1:
The system implements dynamics by enabling the mobile device to switch between following the globally planned path and performing local re-planning based on real-time conditions. When dynamic obstacles are detected or connectivity is lost, the device can autonomously recalculate paths using the local subgraph, providing adaptability while maintaining the safety benefits of global planning when connected.
Data Source
AI summary
A mobile device for travelling to a destination using a communication network is provided. The mobile device obtains from one or more network nodes in the communication network, a first path over a first sub-region of a region, comprising one or more sub-regions, towards the destination. The mobile device further follows the first path; and upon entering, or being in, a second sub-region of the region having a level of connectivity below a threshold, switches to follow a second path calculated locally at the mobile device.