Indoor Drone Navigation Using Dynamic Spatial Maps
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Solution Overview
Problem
Existing drone navigation systems struggle with autonomous navigation in indoor environments due to changes in the configuration of doors and windows, which common spatial tracking techniques often fail to capture sufficiently, especially when users are remote from the property.
Innovation Solution
A drone device generates and utilizes a dynamic multi-dimensional spatial representation of the indoor environment to identify and update the status of dynamic objects, allowing it to navigate effectively by periodically updating or adjusting paths in real-time to account for changes in the environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If common spatial tracking techniques are used for drone navigation, then the system is simple to operate, but the measurement precision of dynamic environment changes is insufficient
Solution Approach 1:
The patent applies the Dynamics principle by implementing a dynamic spatial representation that continuously updates the status of doors and windows in real-time. The system transitions from static environmental maps to dynamic models that reflect current environmental states, enabling the drone to adapt its navigation path based on changing conditions without requiring complex manual reconfiguration.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring the status of dynamic objects (doors, windows) and using this information to adjust navigation paths. The drone receives feedback about environmental changes and modifies its behavior accordingly, creating a closed-loop control system that improves measurement precision of dynamic changes while managing system complexity through automated feedback processing.
2Reliability
If the drone periodically updates the dynamic spatial representation to capture changes, then the reliability of navigation is improved, but the use of energy increases
Solution Approach 1:
The patent applies periodic action by implementing scheduled updates of the dynamic spatial representation at predetermined time intervals. This approach ensures that the navigation system maintains reliable information about environmental changes without requiring continuous monitoring, thereby balancing navigation reliability with energy conservation through interval-based rather than continuous operation.
Solution Approach 2:
The system changes operational parameters by adjusting the update frequency of the dynamic spatial representation based on mission requirements and battery status. The drone can modify the period between updates dynamically, reducing energy consumption during low-priority phases while maintaining higher update frequencies when navigation reliability is critical, thus optimizing the trade-off between reliability and energy use.
3Adaptability or versatility
If the drone adjusts paths in real-time based on dynamic object status, then the adaptability to environment changes is improved, but the device complexity increases
Solution Approach 1:
The patent implements dynamics by creating a flexible navigation system that can dynamically adjust paths based on real-time status changes of doors and windows. The system transitions from rigid pre-planned routes to adaptive dynamic pathfinding, allowing the drone to respond to environmental changes automatically without requiring complex manual intervention or reconfiguration procedures.
Solution Approach 2:
The navigation system applies self-service by autonomously detecting environmental changes and adjusting its own path without external intervention. The drone independently processes spatial representation data, identifies obstacles or opportunities created by dynamic objects, and modifies its navigation plan automatically, reducing the need for complex external control systems while maintaining high adaptability.
Data Source
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AI summary
Techniques are described for enabling a drone device to use a dynamic multi-dimensional spatial representation of an indoor property environment to improve autonomous navigation. In some implementations, an instruction to perform an action at a particular location of a property is received by a drone device. A spatial representation of the property that identifies a dynamic object is obtained by the drone device. The status of the dynamic object impacts an ability of the drone device to navigate near the dynamic object. Sensor data collected by one or more sensors of a monitoring system of the property and that indicates a present status of the dynamic object is obtained by the drone device. A path to the particular location is determined by the drone device. The path to the particular location is finally navigated by the drone device.