Machine Learning

Machine Learning  (ML) builds a mathematical model based on a “training data” in order to make predictions or decisions to perform some specific task.
The powerful combination of robots and machine learning enables entirely new possibilities.

All Publications

Safety Aura Visualization for Variable Impedance Actuated Robots.

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Makhateva, Z.; Zhakatayev, A.; and Varol, H. A.

In Jan 2019. In 2019 IEEE/SICE International Symposium on System Integration (SII)

Computer Vision-Based Pose Estimation of Tensegrity Robots Using Fiducial Markers.

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Moldagalieva, A.; Fadeyev, D.; Kuzdeov, A.; Khan, V.; Alimzhanov, B.; and Varol, H. A.

In Jan 2019. In 2019 IEEE/SICE International Symposium on System Integration (SII)

Optimal Sensor Placement of Variable Impedance Actuated Robots.

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Rakhim, B.; Zhakatayev, A.; Adiyatov, O.; and Varol, H. A.

In Jan 2019. In 2019 IEEE/SICE International Symposium on System Integration (SII)

Generalized Dynamics of Stacked Tensegrity Manipulators.

#dynamics #mathematical #model #bars #actuators #manipulator #dynamics #nonlinear #dynamical #systems

Fadeyev, D.; Zhakatayev, A.; Kuzdeuov, A.; and Varol, H. A.

Fadeyev, D.; Zhakatayev, A.; Kuzdeuov, A.; and Varol, H. A. IEEE Access,1-1. 2019.