Drone Takeoff Diagnosis Using Configuration and Environment Checks
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Solution Overview
Problem
Autonomous drones used for spraying agricultural chemicals lack sufficient safety measures, particularly in Japan where farmland is small and complex, and there is a risk of accidents due to the weight of the drones and non-expert operators.
Innovation Solution
A drone system with a remote controller connected through a network, featuring a flight control unit, configuration determination unit, and external environment determination unit, which transitions through multiple states to ensure safe takeoff and operation by assessing the drone's configuration and external conditions before flight, including battery, motor, and sensor checks, as well as environmental factors like radio wave interference and GPS sensitivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous flight is implemented to improve operational efficiency and reduce manual control requirements, then productivity is improved, but safety deteriorates due to lack of expert operator judgment and insufficient foolproof mechanisms
Solution Approach 1:
The patent implements a pre-flight diagnosis system that checks drone configuration and external environment conditions before takeoff. The flight control unit executes diagnosis routines that verify battery status, motor functionality, sensor operation, and environmental suitability (wind speed, GPS signal, radio wave interference). Only when all diagnosis items are confirmed normal does the system permit takeoff, preventing unsafe autonomous operations before they can occur.
Solution Approach 2:
The system continuously monitors drone status and environmental conditions through sensors and feedback loops. The flight control unit receives real-time data from various sensors (battery level, motor temperature, GPS position, wind speed) and adjusts operations or triggers alerts based on predefined safety thresholds. This closed-loop feedback ensures ongoing safety verification during autonomous flight operations.
2Reliability
If comprehensive safety checks and state transition mechanisms are implemented to improve safety, then reliability is improved, but device complexity increases due to multiple diagnosis states and transition conditions
Solution Approach 1:
The patent divides the safety verification process into distinct diagnostic modules: configuration diagnosis (battery, motor, sensors) and external environment diagnosis (wind speed, GPS signal, radio wave interference). Each module independently evaluates specific parameters and reports results to the flight control unit. This segmentation allows comprehensive safety checking while maintaining modular, manageable system architecture that simplifies implementation and maintenance.
Solution Approach 2:
The system performs all necessary safety diagnoses and environment assessments before the drone begins flight operations. The flight control unit executes complete diagnosis routines during the pre-flight phase, confirming all safety conditions are met before permitting takeoff. This preliminary verification prevents the need for complex real-time safety interventions during flight, reducing overall system complexity.
3Reliability
If pre-flight diagnosis and environment verification are conducted to prevent accidents, then safety is improved, but loss of time increases due to additional checking procedures before takeoff
Solution Approach 1:
The system performs safety diagnoses and environment verifications automatically during the pre-flight preparation phase, before the operator needs to make go/no-go decisions. The flight control unit executes diagnosis routines that quickly assess battery status, motor functionality, sensor operation, and environmental conditions. By completing these checks beforehand and providing clear results, the system enables faster takeoff decisions without compromising safety verification.
Solution Approach 2:
When diagnosis results confirm normal conditions across all parameters, the system rapidly transitions from diagnosis mode to flight mode without unnecessary delays. The state transition mechanism is optimized to quickly permit takeoff once safety is confirmed, minimizing the time penalty of comprehensive checking. Critical safety parameters are verified efficiently, and normal operations proceed without prolonged interruptions.
Data Source
AI summary
A highly safe drone is provided. A remote controller and a drone are connected to each other through a network and cooperate to operate. The drone includes a flight control unit, a flight start command reception unit receiving a flight start command from a user, a drone determination unit determining a configuration of the drone itself, an external environment determination unit determining an external environment of the drone. The drone system has a plurality of states including a takeoff diagnosis state and satisfies a condition transitioning to another state. The takeoff diagnosis state includes a drone determination state where the drone determination unit determines the configuration of the drone itself and an external environment determination state where the external environment determination unit determines the external environment. The drone system makes the drone to takeoff after transitioning to the takeoff diagnosis state upon receiving the flight start command.