Movable Platform Sensor Pose Calibration for Stable Transformation Control
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Solution Overview
Problem
The control of movable platforms, such as aerial vehicles, that transform between multiple states is challenging due to changes in the center of gravity and relative pose of sensors, leading to displacement and instability during transformation operations.
Innovation Solution
A real-time control method and device that obtain sensor data from arm assemblies of a movable platform, perform real-time calibration to determine the relative pose of sensors, and adjust movement control accordingly to maintain stability and accuracy during transformations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the movable platform performs transformation operations through arms to expand functionality, then the photographing range and working mode are improved, but the shape changes significantly causing control instability and displacement
Solution Approach 1:
The system dynamically adjusts control parameters based on the real-time transformation state of the arms. The controller continuously updates control instructions according to the current pose and movement state, enabling the system to adapt to changing configurations while maintaining control stability throughout the transformation process.
Solution Approach 2:
The system changes control parameters in real-time based on the transformation state. By monitoring arm position, speed, and acceleration, the controller adjusts control parameters such as gain values and threshold levels to maintain stability during shape changes, allowing the platform to transition between different functional states reliably.
2Measurement precision
If real-time calibration is performed to characterize relative pose of sensors, then measurement precision is improved, but computational complexity and processing time increase
Solution Approach 1:
The system performs preliminary calibration of sensor relative poses before transformation operations begin. By pre-establishing the spatial relationships between sensors in known configurations, the system reduces the computational burden during real-time operation, as only incremental adjustments are needed during actual transformations rather than full recalibration.
Solution Approach 2:
The system uses feedback from sensor data to continuously refine pose estimates during transformation. By comparing actual sensor measurements with expected values based on the transformation model, the controller makes incremental corrections to maintain accuracy without requiring computationally intensive full recalibration at every moment.
3Adaptability or versatility
If the arms move relative to the center body to change shape, then adaptability is improved, but displacement occurs affecting control accuracy
Solution Approach 1:
The system introduces a coordinate transformation model as an intermediary between the arm movements and the control system. This model mathematically describes the relationship between arm positions and overall platform configuration, allowing the controller to compensate for displacements caused by shape changes and maintain control accuracy across different configurations.
Data Source
AI summary
A control method includes obtaining, in real time during operation of a movable platform, data of a plurality of sensors located at one or more arm assemblies of the movable platform, performing real-time calibration using the data to obtain a calibration result that characterizes a relative pose between the plurality of sensors, and performing movement control on the movable platform according to the calibration result.