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Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
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A survey team is tasked with determining the elevation difference between points Point A and Point B, separated by uneven terrain. They use a leveling instrument and a leveling rod.Common MistakesMisreading the Rod: During a backsight reading at Point A, the instrumentman observes the rod partially obscured by tall grass. Instead of reading 1.135 m, they mistakenly record 1.735 m due to the misalignment of the crosshair with the wrong graduation. This error adds 0.600 m to all subsequent...
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GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
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To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
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Absolute Positioning Accuracy Improvement in an Industrial Robot.

Yizhou Jiang1, Liandong Yu1, Huakun Jia1

  • 1School of Instrument Science and Opto-Electronics Engineering, Hefei University of Technology, Hefei 230009, China.

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This study introduces an artificial neural network optimized by differential evolution to enhance robot absolute positioning accuracy. The method effectively compensates for kinematic and non-kinematic errors, significantly improving robot performance.

Keywords:
absolute positioning accuracydifferential evolution algorithmindustrial robotneural network

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Machine Learning

Background:

  • Robot absolute positioning accuracy is crucial for performance but limited by kinematic and non-kinematic errors.
  • Existing calibration methods often overlook non-kinematic errors, hindering optimal accuracy.
  • Improving absolute positioning accuracy is essential for advanced robotic applications.

Purpose of the Study:

  • To develop a novel method for enhancing robot absolute positioning accuracy.
  • To address limitations of traditional calibration by incorporating non-kinematic error compensation.
  • To improve both the accuracy and efficiency of robot calibration.

Main Methods:

  • An artificial neural network (ANN) was proposed for compensating positioning deviations.
  • The ANN's structure and parameters were optimized using the differential evolution (DE) algorithm.
  • The trained network was validated through simulations and experiments on a six-degree-of-freedom robot using a laser tracker.

Main Results:

  • The proposed method significantly improved the robot's average positioning accuracy from 0.8497 mm to 0.0490 mm.
  • Differential evolution optimization enhanced the ANN's accuracy and efficiency in error compensation.
  • Experimental results confirmed the substantial improvement in absolute positioning accuracy.

Conclusions:

  • The ANN optimized by DE effectively compensates for kinematic and non-kinematic errors in robots.
  • This approach offers a significant advancement in achieving high absolute positioning accuracy for industrial robots.
  • The method demonstrates practical applicability and substantial performance gains in real-world robotic systems.