Indoor Drone Navigation Using Dynamic Spatial Maps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing drone navigation systems face challenges in autonomously navigating indoor environments with dynamic changes, such as moving objects, as they often rely on static spatial tracking techniques that fail to capture sufficient information for informed decision-making, especially when users are remote from the property.
Innovation Solution
The implementation of a dynamic multi-dimensional spatial representation that identifies and updates the locations and statuses of dynamic objects within a property, allowing the drone to generate new paths or adjust existing ones in real-time to navigate effectively through changing environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If static spatial tracking techniques are used for drone navigation, then the navigation system is simple to implement, but it fails to capture sufficient information about dynamic changes in the environment
Solution Approach 1:
The patent transforms the static spatial map into a dynamic multi-dimensional spatial representation that continuously updates to reflect changes in the environment. The system periodically regenerates the spatial map and updates dynamic objects' statuses, enabling the navigation system to adapt to real-time changes while maintaining a structured approach to information management
Solution Approach 2:
The patent introduces temporal and status dimensions to the traditional spatial map, creating a multi-dimensional representation. This includes adding time-based updates and status states (e.g., open/closed for doors and windows) to the spatial data, allowing the system to capture dynamic changes without requiring complete system redesign
2Reliability
If the drone periodically updates the dynamic multi-dimensional spatial representation, then the navigation accuracy improves, but the computational load and time consumption increase
Solution Approach 1:
The patent implements periodic updates of the dynamic multi-dimensional spatial representation at scheduled intervals rather than continuously. This allows the system to maintain navigation accuracy by regularly refreshing the spatial map and detecting status changes, while avoiding the computational overhead of continuous real-time updates
Solution Approach 2:
The system performs path computation and spatial map updates in advance before navigation is critically needed. By periodically regenerating the spatial representation and pre-computing routes based on current environmental states, the system reduces last-minute computational demands and ensures accurate navigation without excessive time pressure
3Adaptability or versatility
If the drone uses real-time monitoring of dynamic objects, then it can adapt to environmental changes, but the energy consumption increases
Solution Approach 1:
The patent implements a feedback mechanism where the drone monitors status changes of dynamic objects (such as doors and windows opening or closing) and uses this information to adjust its navigation path. The system detects changes in the dynamic multi-dimensional spatial representation and triggers path recalculation only when relevant environmental changes occur, rather than continuously monitoring all parameters
Solution Approach 2:
The system focuses monitoring efforts on specific parameters that directly impact navigation, such as the status of doors and windows. By tracking only these critical parameters rather than all environmental variables, the system achieves adaptability to environmental changes while minimizing energy consumption associated with comprehensive real-time monitoring
Data Source
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.