Collaborative Robot Manifold Tracking via Straddle Formation
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Solution Overview
Problem
Existing technologies face challenges in tracking coherent structures and manifolds in fluid flows, particularly in ocean environments, where sensors tend to escape due to the unstable nature of Lagrangian coherent structures, requiring effective methods for maintaining monitoring regions.
Innovation Solution
A collaborative control method using at least three autonomous sensors, where one sensor acts as a tracking sensor and the others as herding sensors, maintaining a straddle formation to predict global fluid flow structures based on local velocity measurements, enabling the tracking of stable and unstable manifolds in 2D conservative flows without requiring a global picture of ocean dynamics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If sensors are deployed to monitor Lagrangian coherent structures in ocean flows, then global information about flow dynamics can be obtained, but sensors tend to escape from monitoring regions due to the unstable nature of LCS
Solution Approach 1:
The system divides the monitoring task among multiple autonomous sensors (at least three) that operate cooperatively. Each sensor monitors a portion of the LCS while the team collectively maintains coverage of the entire coherent structure, preventing information loss while individual sensors remain within stable monitoring regions.
Solution Approach 2:
The system continuously measures local flow velocity and uses this feedback to dynamically adjust sensor positions. By computing LCS trajectories from velocity measurements and comparing current sensor positions to desired positions on the LCS, the system maintains sensors within monitoring regions despite the unstable nature of the coherent structures.
2Measurement precision
If autonomous sensors are used to track coherent structures, then measurement capabilities are improved, but device complexity increases due to collaborative control requirements
Solution Approach 1:
Each autonomous sensor is equipped with onboard processing capabilities to compute local LCS trajectories and determine its own desired position on the coherent structure. The sensors independently calculate control commands based on local velocity measurements and shared position information, reducing the need for complex centralized control while maintaining high tracking accuracy.
3Manufacturing precision
If sensors maintain straddle formation across LCS boundaries, then boundary tracking precision is improved, but ease of operation deteriorates due to formation control requirements
Solution Approach 1:
The straddle formation is not a rigid static configuration but a dynamic formation that adapts to the evolving LCS geometry. The desired positions of sensors on the LCS are continuously updated based on real-time velocity measurements and LCS trajectory computations, allowing the formation to maintain precision while automatically adjusting to flow changes without requiring manual reconfiguration.
Data Source
AI summary
A collaborative control method for tracking Lagrangian coherent structures (LCSs) and manifolds on flows employs at least three autonomous sensors each equipped with a local flow sensor for sensing flow in a designated fluid medium, e.g. water or air. A first flow sensor is a tracking sensor while the other sensors are herding sensors for controlling and determining the actions of the tracking sensor. The tracking sensor is positioned with respect to the herding sensors in the fluid medium such that the herding sensors maintain a straddle formation across a boundary; obtaining a local fluid flow velocity measurement from each sensor. A global fluid flow structure is predicted based on the local flow velocity measurements. In a water medium, mobile autonomous underwater flow sensors may be deployed with each tethered to a watersurface craft.