Adaptive Virtual Dead Man's Switch for Connectivity-Safe Robotics
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Solution Overview
Problem
Autonomous robotic systems (ARSs) face challenges in maintaining safe and efficient operation due to varying connectivity conditions with remote-control centers, as existing technologies fail to adapt operational parameters effectively in response to changing communication performance metrics, potentially leading to off-nominal operation states.
Innovation Solution
The implementation of an Adaptive Virtual Dead Man's Switch (AVDMS) that determines current connection performance metrics and adjusts operational parameters, such as maximum velocity and altitude, to ensure safe and efficient operation by selecting appropriate safety envelope definitions based on these metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If autonomous robotic systems operate with fixed operational parameters, then safety can be maintained under known conditions, but the system cannot adapt to varying connectivity conditions, leading to off-nominal operation states
Solution Approach 1:
The system dynamically adjusts operational parameters based on real-time connectivity conditions. The autonomous robotic system transitions from static fixed parameters to dynamic adaptive parameters by continuously monitoring connection performance metrics and adjusting operational envelopes accordingly, allowing the system to adapt to varying connectivity while maintaining safety through defined parameter ranges
Solution Approach 2:
The system changes operational parameters (velocity, altitude, acceleration) based on connectivity quality. When connectivity deteriorates, the system automatically adjusts parameters such as reducing maximum velocity or altitude limits to maintain safe operation within the determined operational envelope, thus adapting to conditions while preserving reliability
2Adaptability or versatility
If the system continuously monitors connection performance metrics and adjusts operational parameters, then adaptability to changing conditions is improved, but system complexity increases
Solution Approach 1:
The system implements a feedback loop where connection performance metrics are continuously monitored and fed back to adjust operational parameters. The autonomous robotic system receives feedback on connectivity quality and automatically adjusts its operational envelope accordingly, enabling dynamic adaptation through a closed-loop control mechanism that manages complexity through systematic feedback processing
Solution Approach 2:
The autonomous robotic system performs self-adjustment of operational parameters without external intervention. The system independently monitors its own connectivity status and automatically modifies operational envelopes based on determined performance metrics, reducing the need for complex external control systems while maintaining adaptability
3Reliability
If operational parameters are adjusted based on connection performance, then safe operation under varying conditions is improved, but the system may enter off-nominal states more frequently
Solution Approach 1:
The system dynamically adjusts operational parameters to maintain safety while minimizing impact on productivity. By continuously adapting the operational envelope to current connectivity conditions, the system ensures safe operation without unnecessarily restricting mission execution when conditions permit, thus balancing reliability with productivity through dynamic parameter adjustment
Data Source
AI summary
A method for managing a robotic system includes determining connection performance metrics indicating current performance characteristics of a connection with a remote-control center; determining a safety envelope description from a set based on the connection performance metrics, wherein each description includes a mapping of connection performance metrics to operational parameters defining operating parameters for the system, and the determined safety envelope description maps the connection performance metrics to first operational parameters. The method further includes determining that the first operational parameters differ from second operational parameters currently being used by the system; and applying the first operational parameters to govern operation of the system.


