UAV Touchdown Detection via Dynamics-Based Force Estimation
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Solution Overview
Problem
Autonomous unmanned aerial vehicles (UAVs) face challenges in detecting touchdown on various surfaces without tactile force sensors, especially when landing gently or encountering obstacles during the landing phase.
Innovation Solution
The technique utilizes information from onboard sensors and a dynamics model of the UAV to estimate external forces and torques acting on the UAV, enabling it to land on multiple surface types, including flat, sloped, and rough surfaces, and recover from obstacles during landing.
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 and cost increase
Solution Approach 1:
The patent replaces tactile force sensors with a computational approach using existing onboard sensors (accelerometers, gyroscopes, barometers) combined with a dynamics model to estimate external forces and detect touchdown. This substitutes mechanical sensing with a software-based 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 sensor readings, acting as a computational mediator between raw sensor data and touchdown detection.
2Measurement precision
If tactile force sensors are used to detect touchdown, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent replaces expensive tactile force sensors with a computational approach using existing onboard sensors combined with a dynamics model. This substitution eliminates the need for costly specialized hardware while achieving the same measurement objective through software-based force estimation.
Solution Approach 2:
The patent enables the UAV to use its own existing sensors and computational resources to perform touchdown detection, rather than relying on additional specialized sensors. The system serves its own measurement needs using already-available components, reducing overall system cost.
3Object-generated harmful factors
If the UAV lands gently on soft surfaces, then object-generated harmful factors are reduced, but touchdown detection becomes more difficult
Solution Approach 1:
The patent uses continuous feedback from onboard sensors (accelerometers, barometers) during the landing process to monitor external forces in real-time. The dynamics model processes this feedback data to detect touchdown conditions, allowing the system to adapt to varying surface conditions including soft surfaces where gentle landing is required.
Solution Approach 2:
The patent replaces direct mechanical force measurement with computational estimation using sensor feedback and dynamics modeling. This approach can detect touchdown on soft surfaces where traditional force sensors might be overwhelmed or damaged, as the system estimates forces from multiple sensor readings rather than direct contact measurement.
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.