Robotic Relay Nodes for Dynamic Mesh Network Formation
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Solution Overview
Problem
Current methods for deploying and maintaining wireless ad-hoc networks in indoor and obstacle-rich environments are labor-intensive and fail to adapt dynamically to changing warfighter positions and environment conditions, leading to unreliable communication links.
Innovation Solution
A self-configuring algorithm that enables autonomous adaptation of mesh networks by robotic relay nodes, which can identify and adjust to connectivity junctions through radio frequency sensing, allowing for reliable network formation regardless of initial node deployment positions or environmental changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static relay nodes are placed at fixed locations, then network deployment is simplified, but the network fails to adapt to changing warfighter positions and environment conditions
Solution Approach 1:
The patent transforms static relay nodes into mobile robotic nodes that can dynamically reposition themselves. The nodes use RF sensing to detect connectivity opportunities and autonomously navigate to optimal positions, enabling the network to adapt to changing warfighter locations and environmental conditions while maintaining operational simplicity through automated behavior.
2Manufacturing precision
If manual deployment of relay nodes is used, then network configuration is precise, but the process is labor intensive and cannot work in inaccessible environments
Solution Approach 1:
The robotic relay nodes autonomously perform deployment tasks without human intervention. Each node independently senses the RF environment, identifies connectivity opportunities, navigates to optimal positions, and self-configures into the mesh network. This eliminates the need for manual deployment while achieving precise node placement through automated RF-based positioning.
3Adaptability or versatility
If robotic nodes autonomously navigate to optimal positions, then network adaptability is improved, but the system complexity increases
Solution Approach 1:
The patent combines RF sensing, navigation, and network configuration functions into integrated robotic nodes. The nodes use the existing RF communication infrastructure for both data transmission and environmental sensing, eliminating the need for separate sensing and navigation systems. This merging of functions achieves dynamic adaptability while controlling overall system complexity.
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
The algorithm enables the formation of robust, dynamic, and adaptive mesh networks that maintain reliable communication links even in complex environments, such as buildings or caves, by autonomously adjusting node positions and behaviors to ensure continuous connectivity.
Implementation Method 1
identify and adjust to connectivity junctions through radio frequency sensing
Data Source
AI summary
A distributed coordination and control protocol may enable a set of mobile, self-organizing, robotic relay nodes to adaptively seek positions in such an environment that establishes a network, meeting desired coverage in terms of connected warfighters. Distributed coordination of robotic relay nodes may allow the network to dynamically adapt as positions of warfighters change and/or the network demands change. An algorithm is provided that may be scalable to a large number of robots and may be robust to random deployment of robots, robot platform failures, channel dynamics, and changing warfighter positions.