Hand-Guided Robot End-Effector Correction From Joint Moments
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Solution Overview
Problem
Conventional robotic models fail to accurately predict the position of a robot's end effector when interacting with external objects, leading to significant positioning errors due to unaccounted forces and moments, especially during hand-guided operations.
Innovation Solution
A method that measures moments at each joint of a hand-guided robot's arm while interacting with external objects, computes a positional correction factor to account for external moments, and updates the end effector's position for improved precision, incorporating dynamic influences like centrifugal and Coriolis forces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional robotic models are used to predict end effector position, then the model is simple and easy to implement, but positioning accuracy deteriorates significantly when interacting with external objects
Solution Approach 1:
The patent implements feedback by measuring actual moments at robot joints using torque sensors, comparing these with modeled moments, and using the difference (external moment) to correct position predictions. This closed-loop approach continuously refines positioning accuracy based on real-time measurements.
Solution Approach 2:
The patent replaces pure mathematical modeling with a hybrid approach that incorporates physical measurements from torque sensors. Instead of relying solely on computational models, the system uses actual mechanical measurements to detect and compensate for external forces, achieving higher accuracy without requiring an overly complex model.
2Measurement precision
If the robot model accounts for all dynamic influences like centrifugal and Coriolis forces, then positioning accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
The patent introduces an intermediary approach by using torque sensor measurements as a mediator between the physical system and the mathematical model. Rather than computing all dynamic effects directly, the system uses sensor data to capture the net effect of external forces, simplifying computation while maintaining accuracy.
Solution Approach 2:
The patent changes the approach from computing multiple dynamic parameters (centrifugal forces, Coriolis forces) separately to measuring the combined effect through torque sensors. This parameter transformation converts a complex multi-parameter computation problem into a simpler measurement-based correction approach.
Data Source
AI summary
A method for operating a hand-guided robot having a jointed arm and an end effector is provided. As part of the method, a moment is measured at each joint while the robot is being hand-guided or subjected to a mechanical tension due to contact with an external object. Based on the measured moment, an external moment affecting the robot is determined. Then, a correction factor for a position of the end effector is computed based on the external moment and an absolute accurate model of the robot. Then, a current position of the end effector is computed based on a correction model in dependence on the correction factor. A corresponding storage medium, data processing device, robotic system, and tracking system are also provided.