Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Štěpánová, Karla"'
Autor:
Vanc, Petr, Franzese, Giovanni, Behrens, Jan Kristof, Della Santina, Cosimo, Stepanova, Karla, Kober, Jens
Learning from demonstration is a promising way of teaching robots new skills. However, a central problem when executing acquired skills is to recognize risks and failures. This is essential since the demonstrations usually cover only a few mostly suc
Externí odkaz:
http://arxiv.org/abs/2409.20173
Autor:
Nazarczuk, Michal, Behrens, Jan Kristof, Stepanova, Karla, Hoffmann, Matej, Mikolajczyk, Krystian
Embodied reasoning systems integrate robotic hardware and cognitive processes to perform complex tasks typically in response to a natural language query about a specific physical environment. This usually involves changing the belief about the scene
Externí odkaz:
http://arxiv.org/abs/2404.15194
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 vision models have been proposed for this task. However, they are comput
Externí odkaz:
http://arxiv.org/abs/2404.01932
As human-robot collaboration is becoming more widespread, there is a need for a more natural way of communicating with the robot. This includes combining data from several modalities together with the context of the situation and background knowledge
Externí odkaz:
http://arxiv.org/abs/2404.01702
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 challenges in using VAEs is the model's sensitivity to its hyperparameters, su
Externí odkaz:
http://arxiv.org/abs/2312.06280
Human-Robot collaboration in home and industrial workspaces is on the rise. However, the communication between robots and humans is a bottleneck. Although people use a combination of different types of gestures to complement speech, only a few roboti
Externí odkaz:
http://arxiv.org/abs/2303.04451
Collaborative robots became a popular tool for increasing productivity in partly automated manufacturing plants. Intuitive robot teaching methods are required to quickly and flexibly adapt the robot programs to new tasks. Gestures have an essential r
Externí odkaz:
http://arxiv.org/abs/2301.09899
Autor:
Sedlar, Jiri, Stepanova, Karla, Skoviera, Radoslav, Behrens, Jan K., Tuna, Matus, Sejnova, Gabriela, Sivic, Josef, Babuska, Robert
Publikováno v:
IEEE Robotics and Automation Letters, vol. 8, no. 5, pp. 2788-2795, 2023
This paper introduces a dataset for training and evaluating methods for 6D pose estimation of hand-held tools in task demonstrations captured by a standard RGB camera. Despite the significant progress of 6D pose estimation methods, their performance
Externí odkaz:
http://arxiv.org/abs/2209.07976
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 thus serve as a promising tool for both data classification and gener
Externí odkaz:
http://arxiv.org/abs/2209.03048
Autor:
Pliska, Michal, Patni, Shubhan, Mares, Michal, Stoudek, Pavel, Straka, Zdenek, Stepanova, Karla, Hoffmann, Matej
Publikováno v:
IEEE Transactions on Robotics, vol. 40, pp. 4414-4426, 2024
In haptic object discrimination, the effect of gripper embodiment, action parameters, and sensory channels has not been systematically studied. We used two anthropomorphic hands and two 2-finger grippers to grasp two sets of deformable objects. On th
Externí odkaz:
http://arxiv.org/abs/2204.06343