Indoor Drone Navigation With Obstacle-Aware Landing Paths
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Solution Overview
Problem
Existing property monitoring systems, particularly those utilizing drones, face challenges in navigating through obstacles, distinguishing between real and noise obstacles, identifying doors, and performing safe landings, especially in complex environments with varying layouts and furniture configurations.
Innovation Solution
The drone employs a combination of onboard sensors and data from the property monitoring system to detect obstacles, determine obstacle confidence scores, plan navigation paths, wait for doors to open, and perform non-vertical landings to avoid damage and turbulence, using techniques such as obstacle detection, path planning, and adaptive landing approaches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the drone uses traditional vertical landing approach, then the landing process is simple, but the drone may cause turbulence and damage to surrounding objects
Solution Approach 1:
The patent inverts the traditional vertical landing approach by implementing a non-vertical landing method. The drone approaches the landing surface at an angle rather than straight down, which reduces the impact velocity in the vertical direction and minimizes turbulence generation. This inversion of the landing trajectory directly addresses the harmful effects while maintaining operational feasibility
Solution Approach 2:
The patent changes the landing parameters by transitioning from a vertical trajectory to a non-vertical trajectory. This involves modifying the approach angle, velocity vector, and landing orientation parameters. By adjusting these parameters, the drone achieves a controlled landing that reduces harmful turbulence and prevents damage to surrounding objects while completing the landing function
2Reliability
If the drone restricts landing to traditional flat surfaces, then the landing safety is high, but the available landing locations are limited
Solution Approach 1:
The patent makes the drone's landing capability universal by enabling it to land on various surface types including walls and inclined surfaces, not just traditional flat horizontal surfaces. The non-vertical landing approach allows the drone to adapt to different geometries and orientations of landing surfaces, significantly expanding the versatility of available landing locations while maintaining safety through controlled descent
Solution Approach 2:
The patent introduces dynamic adaptability in the landing process by allowing the drone to adjust its approach trajectory and orientation based on the characteristics of the target landing surface. Whether landing on a wall, incline, or flat surface, the drone dynamically modifies its landing parameters to ensure safe and controlled contact, thereby expanding location versatility without compromising reliability
3Device complexity
If the drone uses simple obstacle detection, then the system complexity is low, but the drone cannot distinguish between real obstacles and noise
Solution Approach 1:
The patent implements feedback mechanisms in the obstacle detection system where the drone continuously monitors detected obstacles, analyzes their characteristics over time, and adjusts its navigation accordingly. By providing feedback loops that process detection data and refine obstacle identification, the system achieves higher measurement precision in distinguishing real obstacles from noise without requiring excessively complex hardware
Solution Approach 2:
The patent applies preliminary action by pre-processing and analyzing sensor data before making obstacle identification decisions. The system performs initial filtering, characteristic analysis, and probability assessment of detected objects to determine whether they represent real obstacles or noise. This preliminary processing enhances measurement precision while keeping the overall system complexity manageable by organizing the detection workflow efficiently
Data Source
AI summary
Methods, systems, and apparatus for drone navigation within a property. A method includes detecting an obstacle in a navigation path of a drone, determining a classification of the obstacle, determining whether to temporarily land based on the classification of the obstacle, and temporarily landing the drone until the obstacle clears the navigation path of the drone.