3 citations · 7 across the 8 of their papers we have counts for
9 papers
PRAG: Procedural Action Generator
Michal Vavrecka, Radoslav Skoviera, Gabriela Sejnova +1
We present a novel approach for the procedural construction of multi-step contact-rich manipulation tasks in robotics. Our generator takes as input user-defined sets of atomic acti…
Robotic Calibration Based on Haptic Feedback Improves Sim-to-Real Transfer
Juraj Gavura, Michal Vavrecka, Igor Farkas +1
When inverse kinematics (IK) is adopted to control robotic arms in manipulation tasks, there is often a discrepancy between the end effector (EE) position of the robot model in the…
Bridging Language, Vision and Action: Multimodal VAEs in Robotic Manipulation Tasks
Gabriela Sejnova, Michal Vavrecka, Karla Stepanova
In this work, we focus on unsupervised vision-language-action mapping in the area of robotic manipulation. Recently, multiple approaches employing pre-trained large language and vi…
Adaptive Compression of the Latent Space in Variational Autoencoders
Gabriela Sejnova, Michal Vavrecka, Karla Stepanova
Variational Autoencoders (VAEs) are powerful generative models that have been widely used in various fields, including image and text generation. However, one of the known challeng…
How language of interaction affects the user perception of a robot
Barbara Sienkiewicz, Gabriela Sejnova, Paul Gajewski +2
Spoken language is the most natural way for a human to communicate with a robot. It may seem intuitive that a robot should communicate with users in their native language. However,…
Benchmarking Multimodal Variational Autoencoders: CdSprites+ Dataset and Toolkit
Gabriela Sejnova, Michal Vavrecka, Karla Stepanova +1
Multimodal Variational Autoencoders (VAEs) have been the subject of intense research in the past years as they can integrate multiple modalities into a joint representation and can…