Drone Control System with Operator Validation Loop
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Solution Overview
Problem
Current drone systems face safety risks due to potential catastrophic actions resulting from corrupted or erroneous data transmitted from a human-machine interface to the onboard entity, leading to malfunctions and increased certification costs.
Innovation Solution
A system where the onboard entity generates a message from received data, transmits it to the control entity, and only executes actions based on an intention message validated by the operator, reducing the risk of erroneous actions and minimizing certification costs by not requiring critical certification for the human-machine interface and warning means.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the human-machine interface and warning means are certified in compliance with criticality standards, then the safety and reliability of the drone system is improved, but the cost and complexity of certification increases
Solution Approach 1:
The system divides certification requirements into two segments: critical components (control entity, onboard entity, validation means) that require certification, and non-critical components (human-machine interface, warning means) that do not require certification. This segmentation allows the system to maintain safety through certification of essential components while avoiding the complexity and cost of certifying all components.
Solution Approach 2:
The validation means requires the operator to perform a preliminary validation action before the onboard entity executes actions based on data from the human-machine interface. This preliminary action creates a safety checkpoint that compensates for the lack of certification of the human-machine interface and warning means, ensuring that even if these components fail, the drone will not execute erroneous actions without operator confirmation.
2Productivity
If the onboard entity executes actions based on data from the human-machine interface, then the productivity and responsiveness of the drone is improved, but the risk of catastrophic actions from corrupted or erroneous data increases
Solution Approach 1:
The system implements a feedback loop where the onboard entity sends data to the control entity, which displays it through warning means for operator verification. The operator's validation action serves as feedback that confirms the data is correct before execution. This feedback mechanism allows the drone to remain responsive while providing a safety check to prevent catastrophic actions from erroneous data.
Solution Approach 2:
The validation means acts as an intermediary between the human-machine interface and the onboard entity's action execution. It mediates the data flow by requiring operator confirmation before allowing actions to be executed, thus blocking potentially harmful actions while permitting valid ones to proceed, balancing productivity with safety.
Data Source
AI summary
A system includes a drone including an onboard entity; and a control entity for controlling the drone and situated remotely from the drone. The control entity enables an operator to select data for sending to the onboard entity, the onboard entity being adapted to execute actions as a function of the received data. The onboard entity is arranged to generate a message on the basis of the data as produced by the control entity and as received by the onboard entity, and to transmit the message to the control entity. The control entity acts via warning means to generate an information signal representative of said message. The operator can then act via validation means to cause an intention message to be transmitted that authorizes or does not authorize execution of said actions by the drone.