Augmented Reality for Robotics: A Review
Augmented reality (AR) is used to enhance the perception of the real world by integrating virtual objects to an image sequence acquired from various camera technologies. The paper provides an overview of AR research in robotics during the five year period from 2015 to 2019. Selected papers were classified based on application areas into four […]
Authors: Zhanat Makhataeva, Huseyin Atakan VarolAnalytical Modeling and Design of Negative Stiffness Honeycombs
The paper mostly describes proposed analysis and design methods of negative stiffness honeycombs. Negative stiffness honeycombs (NSHs) have unique properties, such as negative stiffness behavior, ability to sustain multiple loading-unloading cycles, relatively long plateau in force-displacement characteristics, and more. As a result, researchers and scientists are focusing their attention to understand and investigate new applications of NSH. Our […]
Authors: Altay Zhakatayev, Zhanat Kappassov, Huseyin Atakan VarolNeural Network Augmented Sensor Fusion for Pose Estimation of Tensegrity Manipulators
In this paper, we present a pose estimation strategy for the end effector of a tensegrity manipulator, based on the use of an extended Kalman filter and a deep feedforward neural network with three hidden layers. Our scheme is based on the fusion of sensor data obtained from an inertial measurement unit and ArUco fiducial markers. The method was implemented on a six bar tensegrity prism manipulator, tested using ground truth acquired from an external vision-based motion capture system, and compared with other estimation methods. The experimental results show the ability of our method to provide reliable pose estimates, also dealing with the problems caused by the tensegrity structure, including marker occlusions due to the presence of bars and strings
Authors: Askat Kuzdeuov ; Matteo Rubagotti ; Huseyin Atakan Varol