UAV Touchdown Detection via Dynamics-Based Support Estimation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous unmanned aerial vehicles (UAVs) face challenges in safely and accurately detecting touchdown on various surfaces without tactile force sensors, especially when encountering obstacles or changing landing conditions, which is critical for safe and gentle landing.
Innovation Solution
The technique combines information from onboard sensors, such as cameras and inertial measurement units, with a dynamics model to estimate external forces and torques acting on the UAV, enabling it to determine if it is sufficiently supported by a landing surface and adjust its propulsion system accordingly, without relying on tactile sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If tactile force sensors are used to detect touchdown, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces tactile force sensors with a computational approach that uses existing onboard sensors (accelerometers, gyroscopes, propeller torque sensors) combined with a dynamics model to estimate external forces and detect touchdown. This substitutes a mechanical sensing system with a computational estimation system, reducing hardware complexity while maintaining detection capability.
Solution Approach 2:
The patent introduces a dynamics model as an intermediary that processes data from existing sensors to infer touchdown conditions. Instead of directly measuring contact force, the system uses the dynamics model to estimate external forces based on propeller torque and motion data, acting as a computational mediator between raw sensor data and touchdown detection.
2Reliability
If multiple sensors are integrated to improve detection reliability, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent merges data from multiple existing onboard sensors (accelerometers, gyroscopes, propeller torque sensors) into a unified touchdown detection algorithm. Instead of adding separate sensor systems, it combines information from already-present sensors through a dynamics model, achieving reliable detection without increasing overall system complexity.
Solution Approach 2:
The patent makes existing onboard sensors serve multiple functions: they continue to provide navigation and flight control data while also contributing to touchdown detection through the dynamics model. This multi-functional use of existing sensors improves reliability without requiring additional dedicated sensors for touchdown detection.
3Adaptability or versatility
If the UAV reduces thrust gradually to detect touchdown on moving surfaces, then adaptability is improved, but loss of time increases
Solution Approach 1:
The patent implements continuous feedback through the dynamics model that monitors estimated external forces in real-time during the thrust reduction phase. This feedback mechanism allows the system to quickly detect touchdown conditions and adjust, reducing the time penalty associated with gradual thrust reduction while maintaining adaptability to different surface conditions.
Data Source
AI summary
A technique is introduced for touchdown detection during autonomous landing by an aerial vehicle. In some embodiments, the introduced technique includes processing perception inputs with a dynamics model of the aerial vehicle to estimate the external forces and/or torques acting on the aerial vehicle. The estimated external forces and/or torques are continually monitored while the aerial vehicle is landing to determine when the aerial vehicle is sufficiently supported by a landing surface. In some embodiments, semantic information associated with objects in the environment is utilized to configure parameters associated with the touchdown detection process.