Comparative Analysis of methods for Predicting the Trajectory of Object Movement  in a Collaborative Robot-Manipulator Working Area

Svitlana Maksymova; Amer Abu-Jassar; Dmytro Gurin; Vladyslav Yevsieiev

Comparative Analysis of methods for Predicting the Trajectory of Object Movement in a Collaborative Robot-Manipulator Working Area

Svitlana Maksymova

Department of Computer-Integrated Technologies, Automation and Robotics, Kharkiv National University of Radio Electronics, Ukraine

Amer Abu-Jassar

Department of Computer Science, College of Computer Sciences and Informatics, Amman Arab University, Amman, Jordan

Dmytro Gurin

Department of Computer-Integrated Technologies, Automation and Robotics, Kharkiv National University of Radio Electronics, Ukraine

Vladyslav Yevsieiev

Department of Computer-Integrated Technologies, Automation and Robotics, Kharkiv National University of Radio Electronics, Ukraine

##semicolon## Industry 5.0##common.commaListSeparator## Collaborative Robot##common.commaListSeparator## Work Area##common.commaListSeparator## Computer Vision##common.commaListSeparator## Trajectory Prediction

सार

This article presents a comparative analysis of methods for predicting object movement trajectories in a collaborative robots-manipulator working area. The following approaches are evaluated: linear method, Kalman filter, extended Kalman filter (EKF), behavioral models and LSTM models. A mathematical description of each method is accompanied by an analysis of their advantages and disadvantages, including prediction accuracy, implementation complexity, and resource requirements. The results show that the choice of the method depends on the specifics of the task and the robot's operating conditions, which allows for an optimal combination of efficiency and computational costs.

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