UAV Landing Surface Evaluation Using Stereo Depth Maps
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Solution Overview
Problem
The challenge in landing unmanned aerial vehicles (UAVs) is the need for skilled human operators to manually control the landing process, which can result in damage due to rough landings caused by human error, especially when the operator lacks direct visual perception of the UAV's flight trajectory and attitude.
Innovation Solution
The implementation of a computer-implemented method that allows UAVs to automatically identify suitable landing spots by receiving images of the landing surface, generating depth maps through stereo matching, and selecting candidate areas based on cost values associated with best fit planes, thereby eliminating the need for human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual control by human operators is used for UAV landing, then human judgment and flexibility are maintained, but the risk of rough landings and damage increases due to human error and lack of direct visual perception
Solution Approach 1:
The UAV performs self-landing by autonomously evaluating the landing surface and executing the landing sequence without human intervention. The system uses onboard sensors to capture images, process terrain data, identify suitable landing spots, and control the landing mechanism, enabling the vehicle to serve itself during the critical landing phase and eliminate human error
Solution Approach 2:
The patent replaces manual mechanical control with an automated system combining optical sensors (cameras), computational algorithms (stereo matching, cost function evaluation), and electronic control mechanisms. This substitution of human operator actions with sensor-processing-actuation systems enables more precise and reliable landing control
2Measurement precision
If automated landing surface evaluation is implemented, then landing precision and safety are improved, but system complexity and computational requirements increase
Solution Approach 1:
The landing surface evaluation is divided into discrete computational steps: capturing multiple images, performing stereo matching to generate depth maps, identifying candidate areas, evaluating cost functions for each candidate, and selecting the optimal landing spot. This segmentation of the evaluation process into modular stages makes the complex system more manageable and implementable
Solution Approach 2:
The system performs preliminary actions by capturing images and generating depth maps of the landing surface before the actual landing occurs. Candidate areas are identified and evaluated in advance, allowing the UAV to make informed decisions about the optimal landing spot before committing to the descent, thereby improving landing precision
Data Source
AI summary
Automatic terrain evaluation of landing surfaces, and associated systems and methods are disclosed herein. A representative method includes receiving a request to land a movable object and, in response to the request, identifying a target landing area on a landing surface based on at least one image of the landing surface obtained by the movable object. The method can further include directing the movable object to land at the target landing area.