Robotic Arm End Effector Mass Identification for Precise Force Control
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Solution Overview
Problem
Conventional robotic arm control methods fail to accurately obtain the mass and center of mass of end effectors due to discrepancies between theoretical CAD models and actual assembly, leading to imprecise position and force control.
Innovation Solution
A method for automatically identifying end effector parameters using a six-dimensional force sensor to collect gravity matrix data at multiple poses, calculating rotation transformation matrices, and determining the center of mass and mass of the end effector, which accounts for sensor static errors, enabling real-time parameter updates without offline modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CAD model parameters are used to obtain end effector mass and center of mass, then the control system can operate without additional sensors, but the mass and center of mass values are inaccurate due to discrepancies between theoretical models and actual assembly
Solution Approach 1:
The robotic arm system performs self-identification of end effector parameters by automatically collecting gravity matrix data at multiple poses and calculating mass and center of mass values through computational algorithms, eliminating the need for external measurement devices or manual parameter input while achieving high measurement precision
Solution Approach 2:
The patent replaces traditional mechanical measurement methods (such as physical weighing and dimensional measurement) with a computational approach using gravity matrix data collection and algorithmic calculation to determine end effector mass and center of mass, achieving higher precision without additional hardware complexity
2Measurement precision
If offline model parameter modifications are performed to adjust for end effector parameters, then accurate control can be achieved, but the process is time-consuming and reduces productivity
Solution Approach 1:
The system performs preliminary identification of end effector parameters by automatically collecting gravity matrix data and calculating mass and center of mass values before actual control operations begin, enabling accurate control from the start without time-consuming offline parameter adjustments or model modifications
Solution Approach 2:
The robotic arm system autonomously identifies and determines its own operational parameters through self-testing procedures, eliminating the need for external engineers to perform manual model parameter modifications and significantly reducing setup time while maintaining high accuracy
3Measurement precision
If a six-dimensional force sensor is used to collect gravity matrix data at multiple poses, then accurate end effector parameters can be determined, but the device complexity and measurement process are increased
Solution Approach 1:
The six-dimensional force sensor serves multiple functions: it measures gravity matrix data at different poses, enables calculation of both mass and center of mass values, and provides data for determining the end effector's moment of inertia, thereby achieving comprehensive parameter identification with a single multi-functional device
Solution Approach 2:
The patent combines the functions of multiple separate measurement devices (such as mass scales, center of mass measurement apparatus, and inertia measurement devices) into a single six-dimensional force sensor system that performs all measurements through one integrated device, reducing overall system complexity despite the advanced capabilities required
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables precise robotic arm control by accurately determining end effector parameters, improving position and force control accuracy and reducing calculation time, while accommodating sensor errors.
Implementation Method 1
obtain, by a sensor of the robotic arm, n gravity matrix data of an end effector in an end coordinate system when the robotic arm is in n different poses
Data Source
AI summary
A method for controlling a robotic arm that includes an end effector and a sensor that are mounted at an end of the robotic arm includes: obtaining, by the sensor, n gravity matrix data, wherein the n gravity matrix data are gravity matrix data of the end effector in an end coordinate system when the robotic arm is in a different poses, n≤3; determining n rotation transformation matrices from a base coordinate system of the robotic arm to the end coordinate system when the robotic arm is in n different poses; calculating coordinates of a center of mass and mass of the end effector based on the n gravity matrix data and the a rotation transformation matrices; and controlling the robotic arm based on the coordinates of the center of mass and the mass.