Robot Arm External Force Estimation via Motor Current Analysis
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Solution Overview
Problem
In automation lines using robot arms, the current teaching methods require significant time and labor, and the use of visual and force sensors to achieve teaching-less control is costly and prone to errors, with force sensors being expensive and fragile.
Innovation Solution
A robot control device that estimates external forces at the tip of the arm based on encoder values from motor driving joints, using a derivation part to calculate variations in rotation angles and motor currents, allowing for the detection of external forces without additional sensors, such as a force sensor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual sensor and force sensor are used for teaching-less control, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces the mechanical force sensor system with a computational approach using encoder data from existing motors. The external force is estimated through mathematical calculation of motor current variations and robot dynamics modeling, eliminating the need for separate force sensing hardware while achieving comparable measurement precision.
Solution Approach 2:
The robot arm uses its own existing sensors (encoders on motor shafts) to estimate external forces. The system leverages data already being collected for position control, processing motor current and position information through dynamic modeling to derive force estimates without requiring additional sensing infrastructure.
2Measurement precision
If force sensor is installed at tip of robot arm, then external force detection capability is improved, but device complexity and cost increase
Solution Approach 1:
The patent substitutes the physical force sensor installation with a virtual sensing approach. By modeling the robot arm's dynamics and monitoring motor current variations, the system calculates external forces mathematically, replacing complex hardware installation with computational processing of existing motor data.
Solution Approach 2:
The existing motor and encoder system, originally designed only for position control, is made multi-functional by also enabling external force estimation. The same motor current and position data used for basic motion control are additionally processed to provide force sensing capabilities, eliminating the need for dedicated force sensor hardware.
3Measurement precision
If teaching method is used to store position data, then positioning accuracy is improved, but time consumption and labor increase
Solution Approach 1:
The robot arm performs self-teaching by autonomously estimating external forces during operation and automatically adjusting its control parameters. The system uses its own sensor data and dynamic model to learn optimal positioning without human intervention, eliminating the time-consuming manual teaching process while maintaining accuracy.
Solution Approach 2:
The system implements continuous feedback loops where estimated external forces are used to adjust control commands in real-time. This feedback mechanism enables the robot to adapt to varying load conditions and achieve accurate positioning automatically, replacing the open-loop manual teaching approach with closed-loop autonomous operation.
Data Source
AI summary
According to one embodiment, a robot control device is used for a robot arm including a link and a motor for rotationally driving the link. The robot control device includes a derivation part. The derivation part derives a first estimated value including a variation of a rotation angle of the link and a second estimated value including a variation of a rotation angle of the motor, based on an angular velocity and a current reference value of the motor. Furthermore, the derivation part derives an external force generated to the robot arm, based on a difference between the first estimated value and the second estimated value.