Manipulator Calibration With Camera-Sensor Error Correction
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Solution Overview
Problem
Current object handling devices face challenges in achieving high accuracy and flexibility in object manipulation due to limitations in calibration and grasping techniques, leading to inefficiencies in handling diverse objects with varying sizes and materials.
Innovation Solution
The object handling device incorporates a manipulator with a camera and sensor system, a calibration unit, and a control system that uses automatic calibration and real-time visual feedback to adjust the manipulator's position and grasp strategy based on object database and grasp database information, enabling precise and flexible handling of objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration is used to achieve high accuracy in manipulator positioning, then positioning precision is improved, but calibration time and operational complexity increase
Solution Approach 1:
The system performs preliminary automatic calibration by capturing images of a calibration board and computing transformation matrices between coordinate systems before actual object handling operations. This preliminary calibration action establishes the spatial relationships needed for accurate manipulation without requiring time-consuming manual calibration during operation.
Solution Approach 2:
The patent replaces manual mechanical calibration procedures with an automated vision-based calibration system. The camera captures images of a calibration board, and the system automatically computes coordinate transformations, substituting the mechanical adjustment process with computational image processing and matrix calculations.
2Measurement precision
If the manipulator is designed for high precision handling, then handling accuracy is improved, but adaptability to various objects decreases
Solution Approach 1:
The system achieves universality by integrating multiple functions into a single manipulator platform: vision-based object recognition, automatic calibration, grasp planning, and execution. The manipulator can handle diverse objects by adapting its grasp strategy based on object characteristics detected by the vision system, rather than requiring specialized mechanisms for each object type.
Solution Approach 2:
The system employs dynamic adaptation through real-time image processing and automated grasp planning. The grasp strategy is not fixed but dynamically adjusted based on the detected object properties such as size, shape, and position, allowing the same manipulator to accurately handle various objects with different characteristics.
3Measurement precision
If complex calibration procedures are implemented to minimize errors, then positioning accuracy is improved, but device complexity increases
Solution Approach 1:
The calibration board serves as an intermediary object that facilitates accurate calibration without requiring complex direct measurements between the camera and manipulator. By capturing images of the calibration board with known geometric features, the system computes coordinate transformations through the intermediary, simplifying the calibration process while maintaining high accuracy.
Solution Approach 2:
The system creates a computational model (copy) of the physical coordinate systems through image processing. Instead of physically aligning coordinate systems through complex mechanical procedures, the system captures images and computes transformation matrices that represent the spatial relationships, replacing physical complexity with computational simplicity.
4Measurement precision
If real-time visual feedback is used to adjust manipulator position, then positioning precision is improved, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary calibration and object recognition before the actual manipulation task. By capturing images of the calibration board and computing transformation matrices in advance, and by identifying object features before grasp execution, the system reduces the computational load during real-time operation, allowing fast response during actual manipulation.
Solution Approach 2:
The system implements visual feedback by capturing images, comparing detected object positions with planned positions, and adjusting manipulator movements accordingly. The feedback loop uses image processing to detect position deviations and computes correction amounts, enabling real-time positioning adjustments while maintaining efficient processing through optimized image analysis algorithms.
Data Source
AI summary
According to an embodiment, an object handling device includes a base, a manipulator, a first camera, a sensor, a manipulator control unit and a calibration unit. The manipulator is arranged on the base, and includes a movable part and an effector that is arranged on the movable part and acts on an object. The first camera and the sensor are arranged on the manipulator. The manipulator control unit controls the manipulator so that the movable part is moved to a position corresponding to a directed value. The calibration processing unit acquires a first error in a first direction based on an image photographed by the first camera, acquire a second error in a second direction intersecting with the first direction based on a detection result obtained by the sensor, and acquire a directed calibration value with respect to the directed value based on the first error and the second error.