All Outputs (10)

Enhancing single camera calibration results using artificial bee colony optimisation within a virtual environment (2024)
Conference Proceeding

Close range photogrammetry is among the top candidates for non-contact metrology in high precision applications. It is frequently used within industrial environments for high precision measurement, automation, and control tasks. When using off-the-sh... Read More about Enhancing single camera calibration results using artificial bee colony optimisation within a virtual environment.

Uncertainty analysis of an augmented industrial robot (2023)
Conference Proceeding

Industrial robots are often used in additive manufacturing (AM) environments to automate the process of creating complex parts and structures. One example of an industrial robot used in AM is for wire and arc additive manufacturing. This process invo... Read More about Uncertainty analysis of an augmented industrial robot.

High-accuracy robotic metrology for precise industrial manipulation tasks (2023)
Conference Proceeding

The majority of industrial production processes can be divided into a series of object manipulation and handling tasks that can be adapted for robots. Through significant advances in compliant grasping, sensing and actuation technologies, robots are... Read More about High-accuracy robotic metrology for precise industrial manipulation tasks.

Intelligent Static Calibration of Industrial Robots using Artificial Bee Colony Algorithm (2023)
Conference Proceeding

This paper proposes an industrial robot calibration methodology using an artificial bee colony algorithm. Open loop industrial robot positions are usually calculated using joint angle readings and industrial robot forward kinematics, where feedback c... Read More about Intelligent Static Calibration of Industrial Robots using Artificial Bee Colony Algorithm.

Trinocular vision system for pose determination (2022)
Conference Proceeding

Improving the Positional Accuracy of Industrial Robots by Forward Kinematic Calibration using Laser Tracker System (2022)
Conference Proceeding

Precision object handling and manipulation require precise positioning of industrial robots. The common practice to perform end effector positioning is to use joint angle readings and industrial robot forward kinematics. However, forward kinematics o... Read More about Improving the Positional Accuracy of Industrial Robots by Forward Kinematic Calibration using Laser Tracker System.

Frequency scanning interferometry for accurate robot position measurement (2022)
Conference Proceeding

This paper presents a frequency scanning interferometry (FSI) shortwave infrared (IR) setup developed for position and orientation measurement of industrial robots. Within contemporary and future industrial frameworks, robots—in particular collaborat... Read More about Frequency scanning interferometry for accurate robot position measurement.

A novel non-iterative parameter estimation method for interval type-2 fuzzy neural networks based on a dynamic cost function (2019)
Conference Proceeding

Non-iterative methods for parameter estimation for interval type-2 neuro-fuzzy structure are fast to implement, when compared to online methods, and need no –or a few– parameters to be tuned. In this paper, a novel dynamic cost function, which define... Read More about A novel non-iterative parameter estimation method for interval type-2 fuzzy neural networks based on a dynamic cost function.

Ensemble of Deep Belief Network and Bayesian Adaptive Aggregation for Regression (2019)
Conference Proceeding

Ensemble modeling of Neural Networks is a strategy where multiple alternative models (ensemble members) are constructed and then their forecasts are ensembled using various combination approaches. Ensemble of Neural Networks has proved the concept be... Read More about Ensemble of Deep Belief Network and Bayesian Adaptive Aggregation for Regression.

Nonlinear System Identification Using Type-2 Fuzzy Recurrent Wavelet Neural Network (2019)
Conference Proceeding

In this paper, the integration of Type-2 fuzzy set theory and recurrent wavelet neural network(WNN) is proposed to allow managing of non-uniform uncertainties for identifying non-linear dynamic system. The proposed Type-2 fuzzy WNN is inherently a re... Read More about Nonlinear System Identification Using Type-2 Fuzzy Recurrent Wavelet Neural Network.