Mobile Path Planning Across Low-Connectivity Zones
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Solution Overview
Problem
Existing path planning systems for mobile devices are inadequate in handling dynamic obstacles and varying connectivity zones, leading to potential deadlocks and safety risks due to reliance on perfect connectivity and limited onboard memory and compute resources.
Innovation Solution
A method and mobile device that switch between global and local path planning, using a safe subgraph protocol to ensure continuous path availability by intelligently distributing autonomy between network nodes and the device, with adaptive computation and resource management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If path planning is done globally in the cloud, then collision-free paths with respect to known obstacles are obtained, but the system cannot handle dynamic obstacles in zones with low or no connectivity
Solution Approach 1:
The patent segments path planning into two parts: global path planning done in the cloud for known obstacles, and local path planning done on the mobile device for dynamic obstacles. This segmentation allows the system to maintain reliable path availability through global planning while gaining adaptability to dynamic obstacles through local planning capabilities that work independently of cloud connectivity.
Solution Approach 2:
The patent implements preliminary action by pre-computing alternative paths and storing them in the mobile device before the device enters low-connectivity zones. This allows the device to have backup paths readily available when connectivity is lost, ensuring continuous path availability without needing to communicate with the cloud during critical moments.
2Adaptability or versatility
If the mobile device stores the entire map for local re-planning, then autonomy is achieved in low-connectivity zones, but memory and compute resources are exceeded
Solution Approach 1:
The patent extracts only the essential elements needed for local path planning from the complete environmental map. Instead of storing the entire map, the device stores a reduced representation containing only critical path information and alternative routes. This extraction maintains local autonomy capability while significantly reducing memory occupancy to fit within device constraints.
Solution Approach 2:
The patent implements partial action by providing the mobile device with a subset of the full map data - specifically, alternative paths and key environmental features needed for local re-planning, rather than the complete environmental model. This partial information is sufficient for local autonomy in low-connectivity zones while avoiding the memory burden of storing the entire map.
3Reliability
If the mobile device traces back to previous zones with adequate connectivity to communicate obstacles, then cloud-based re-planning is obtained, but energy is wasted and time is lost
Solution Approach 1:
The patent implements self-service by enabling the mobile device to perform local path re-planning autonomously using the pre-stored alternative paths and local map data. When dynamic obstacles are detected in low-connectivity zones, the device can immediately re-plan its path locally without needing to trace back to high-connectivity zones or communicate with the cloud, thus saving both time and energy while maintaining reliable path updates.
Data Source
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AI summary
A mobile device for travelling to a destination using a communication network is provided. The mobile device (10) 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 (10) 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.