Underwater Vehicle State-Machine Control for Adaptive Missions
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Solution Overview
Problem
Existing autonomous control systems for underwater vehicles are rigid and require significant user involvement, lacking adaptability and flexibility to react to environmental changes, leading to potential mission failures.
Innovation Solution
A state machine-based control system that transitions between operating states based on pre-configured or dynamically altered entrance and exit criteria, allowing for autonomous decision-making and adaptability, including multi-agent states for teamwork with other vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a rigid autonomous control system is used, then user interaction is reduced, but the system lacks adaptability to environmental changes
Solution Approach 1:
The control system transitions from a rigid static structure to a dynamic state machine with multiple operating states (e.g., inspection state, transit state, hover state) that can adapt to environmental changes. The system dynamically transitions between states based on sensor inputs and pre-configured criteria, enabling autonomous adaptation without user intervention.
Solution Approach 2:
The system changes operational parameters dynamically by transitioning between different operating states with distinct parameter sets (velocity, altitude, mission objectives). Each state has associated entrance and exit criteria that trigger parameter changes based on environmental conditions, allowing the system to maintain autonomy while adapting to changing circumstances.
2Device complexity
If a rigid control protocol is used, then system simplicity is maintained, but mission continuity is compromised when tasks cannot be completed
Solution Approach 1:
The state machine provides a structured yet flexible framework that maintains operational simplicity through predefined states while enabling mission continuity. When the current state's exit criteria cannot be met, the system dynamically transitions to alternative states (e.g., from inspection state back to transit state, or to hover state), ensuring the mission can continue without aborting.
Solution Approach 2:
The system continuously monitors operational parameters and environmental conditions against pre-configured entrance and exit criteria for each state. This feedback mechanism enables autonomous decision-making about state transitions, allowing the system to maintain mission continuity by switching to appropriate states when current objectives cannot be achieved, without requiring complex ad-hoc control protocols.
3Adaptability or versatility
If manual operation is used, then adaptability to changing conditions is maintained, but user involvement is excessive
Solution Approach 1:
The control system performs self-service by autonomously monitoring environmental conditions, evaluating entrance and exit criteria, and transitioning between operating states without user intervention. The system serves itself by making adaptive decisions based on sensor inputs and pre-configured logic, eliminating the need for continuous manual operation while maintaining high adaptability to changing conditions.
Solution Approach 2:
The feedback loop continuously compares actual system state and environmental conditions against pre-configured criteria, enabling autonomous reactive behavior. This feedback mechanism allows the system to automatically adapt to environmental changes by transitioning between states, replacing manual adaptability with autonomous feedback-driven decision-making that requires minimal user involvement.
Data Source
AI summary
Methods and structures are disclosed for providing autonomous control of an underwater vehicle using a state machine. A controller is used onboard the underwater vehicle and includes a state machine having a plurality of operating states. Each of the plurality of operating states includes one or both of entrance criteria and exit criteria. The controller is configured to transition from executing a first operating state of the plurality of operating states to executing a second operating state of the plurality of operating states in response to the exit criteria of the first operating state and the entrance criteria of the second operating state both being met. The plurality of operating states includes a first portion of operating states associated with a first task, a second portion of operating states associated with a second task, and a third portion of operating states associated with both the first and second tasks.