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2022 IEEE International Conference on Systems, Man, and cybernetics, SMC 2022

作者： Huptych, Michal Zdrahal, Zdenek Czech Technical University in Prague Czech Institute of Informatics Robotics and Cybernetics Prague Czech Republic

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Many first-year university students do not complete the study plan and drop out. By investigating how students earn ECTS credits we create a model that makes it possible to predict students who are at risk of failure and drop out of the university. Weekly analysis of student data allows us to identify patterns important for prediction. Early predictions inform students about the potential danger of failure and also allow tutors to intervene. On the other hand, from the data of successful students, it is possible to derive study trajectories leading to the successful completion of the academic year and offer these trajectories to students. The described techniques for student support are demonstrated by examples. © 2022 IEEE.

关键词： Students

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How Language of Interaction Affects the User Perception of a Robot 15th

How Language of Interaction Affects the User Perception of...

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15th International Conference on Social robotics, ICSR 2023

作者： Sienkiewicz, Barbara Sejnova, Gabriela Gajewski, Paul Vavrecka, Michal Indurkhya, Bipin Cognitive Science Department Jagiellonian University Krakow Poland Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Prague Czech Republic Institute of Computer Science AGH University of Science and Technology Krakow Poland

ISBN: (纸本)9789819987146

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, it is not clear if a user’s perception of a robot is affected by the language of interaction. We investigated this question by conducting a study with twenty-three native czech participants who were also fluent in English. The participants were tasked with instructing the Pepper robot on where to place objects on a shelf. The robot was controlled remotely using the Wizard-of-Oz technique. We collected data through questionnaires, video recordings, and a post-experiment feedback session. The results of our experiment show that people perceive an English-speaking robot as more intelligent than a czech-speaking robot (z = 18.00, p-value = 0.02). This finding highlights the influence of language on human-robot interaction. Furthermore, we discuss the feedback obtained from the participants via the post-experiment sessions and its implications for HRI design. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Feedback

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Comparative Evaluation of 3D Reconstruction Methods for Object Pose Estimation

Comparative Evaluation of 3D Reconstruction Methods for Obje...

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IEEE Workshop on Applications of Computer Vision (WACV)

作者： Varun Burde Assia Benbihi Pavel Burget Torsten Sattler Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

Current generalizable object pose estimators, i.e., approaches that do not need to be trained per object, rely on accurate 3D models. Predominantly, CAD models are used, which can be hard to obtain in practice. At the same time, it is often possible to acquire images of an object. Naturally, this leads to the question of whether 3D models reconstructed from images are sufficient to facilitate accurate object pose estimation. We aim to answer this question by proposing a novel benchmark for measuring the impact of 3D reconstruction quality on pose estimation accuracy. Our benchmark provides calibrated images suitable for reconstruction and registered with the test images of the YCB-V dataset for pose evaluation under the BOP benchmark format. Detailed experiments with multiple state-of-the-art 3D reconstruction and object pose estimation approaches show that the geometry produced by modern reconstruction methods is often sufficient for accurate pose estimation. Our experiments lead to interesting observations: (1) Standard metrics for measuring 3D reconstruction quality are not necessarily indicative of pose estimation accuracy, which shows the need for dedicated benchmarks such as ours. (2) Classical, non-learning-based approaches can perform on par with modern learning-based reconstruction techniques and can even offer a better reconstruction time-pose accuracy tradeoff. (3) There is still a sizable gap between performance with reconstructed and with CAD models. To foster research on closing this gap, the benchmark is made available at https://***/VarunBurde/reconstruction_pose_benchmark.

关键词： Geometry Solid modeling Three-dimensional displays Accuracy Pose estimation Benchmark testing Reconstruction algorithms Rendering (computer graphics) Image reconstruction Standards

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Some Adventures in Learning Proving, Instantiation and Synthesis

Some Adventures in Learning Proving, Instantiation and Synth...

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Formal Methods in Computer Aided Design (FMCAD)

作者： Josef Urban Czech Institute of of Informatics Robotics and Cybernetics Prague Czech Republic

ISBN: (数字)9783854480655

ISBN: (纸本)9798331524784

Human problem solvers often combine deductive reasoning and exploration with learning and pattern matching. In the recent years such combinations are also increasingly developed for building stronger automated theorem provers, SMT solvers and conjecturing and synthesis systems. The methods in this field include equipping the current deductive systems with efficient statistically learned guidance that controls the choice of the inference steps, using for example fast decision trees, graph neural networks and their combinations. Learning and AI methods can also be used to automatically design new symbolic strategies for today's ATPs and SMTs. This has the advantage of producing explainable ideas for steering the search space, which can be further taken up and modified by the systems' developers. I will also discuss several methods that try to directly synthesize reasoning objects such as instantiations and OEIS explanations, using various neural approaches. Perhaps the most interesting aspect of this research are the positive feedback loops between the proving and the learning methods. I will show that some of them can today go quite far and create quite interesting “alien” solutions.

关键词： Learning systems Feedback loop Design automation Buildings Aerospace electronics Search problems Cognition Graph neural networks Decision trees Pattern matching

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Ethical Engineer: Enhancing AI Education in Engineering 21

Ethical Engineer: Enhancing AI Education in Engineering

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21st International Conference on Information Technology Based Higher Education and Training, ITHET 2024

作者： Friesel, Anna Lhotska, Lenka Hrad, Jaromir MacKu, David Member of Eaeeie Professor Retired Dtu Copenhagen Denmark Czech Technical University in Prague Czech Institute of Informatics Robotics and Cybernetics Prague Czech Republic Czech Technical University in Prague Department of Telecommunications Engineering Prague Czech Republic

ISBN: (纸本)9798331516635

This paper presents the developments of the Erasmus+ project Ethical Engineer: Integrating teaching ethics in artificial intelligence and robotics into Engineering Education. The Ethical Engineer project goal is to enhance AI education by promoting truthful AI in Europe, with authentic ethical, social, and legal aspects in engineering education and training. We focus on engineering and robotics students on university level. In general, ethics in engineering education today is multifaceted, reflecting the complexity and global impact of the engineering profession. By integrating ethics into every aspect of engineering education, from classroom learning to professional development, engineering programs will graduate not just skilled engineers, but responsible, ethical professionals committed to the greater society. The project brings together a diverse mix of participating organizations that complement each other in terms of expertise, experience, and perspectives. The consortium consists of universities with a strong academic foundation with advanced knowledge in AI, robotics, and data science, as well as access to cutting-edge research and innovation. The organization of engineering education facilitate the exchange of best practices, ideas, and resources among their member institutions, broadening the project's results and impact. This collaboration is further enhanced by the practical industry experience and insights on AI ethics by professional company partners. We describe the goals of this project and give a case example of how to include ethics in engineering education. © 2024 IEEE.

关键词： Engineering education

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TransforMerger: Transformer-based Voice-Gesture Fusion for Robust Human-Robot Communication

arXiv

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arXiv 2025年

作者： Vanc, Petr Stepanova, Karla Czech Technical University in Prague Czech Institute of Informatics Robotics and Cybernetics Czech Republic

As human-robot collaboration advances, natural and flexible communication methods are essential for effective robot control. Traditional methods relying on a single modality or rigid rules struggle with noisy or misaligned data as well as with object descriptions that do not perfectly fit the predefined object names (e.g.’Pick that red object’). We introduce TransforMerger, a transformer-based reasoning model that infers a structured action command for robotic manipulation based on fused voice and gesture inputs. Our approach merges multimodal data into a single unified sentence, which is then processed by the language model. We employ probabilistic embeddings to handle uncertainty and we integrate contextual scene understanding to resolve ambiguous references (e.g., gestures pointing to multiple objects or vague verbal cues like"this"). We evaluate TransforMerger in simulated and real-world experiments, demonstrating its robustness to noise, misalignment, and missing information. Our results show that TransforMerger outperforms deterministic baselines, especially in scenarios requiring more contextual knowledge, enabling more robust and flexible human-robot communication. Code and datasets are available at: http://***. ***/publications/transformerger. © 2025, CC BY-NC-SA.

关键词： Gesture recognition

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Technology Approaches to Metering in Flexibility Aggregation 15

Technology Approaches to Metering in Flexibility Aggregation

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15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, ICUMT 2023

作者： Mamula, Ondrej Pitner, Tomas Strelec, Martin Hrycej, David Kasl, Frantisek Janecek, Petr Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Prague Czech Republic Masaryk University Faculty of Informatics Brno Czech Republic New Technologies for the Information Society University of West Bohemia Plzen Czech Republic

ISBN: (纸本)9798350393286

In this contribution, we identify and discuss three technical scenarios for access to data about metering at the point of consumption by the Aggregator for the purposes of flexibility aggregation. The analysis constitutes part of a broader research project aimed at development of analytical, computational and optimization tools for complex solution for safe use of aggregated power flexibility associated with the integration of new technologies and market players in the czech environment. © 2023 IEEE.

关键词： aggregation communication demand response flexibility measurement

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Automatic Workspace Calibration Using Homography for Pick and Place 19

Automatic Workspace Calibration Using Homography for Pick an...

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19th IEEE International Conference on Automation Science and Engineering, CASE 2023

作者： Burde, Varun Martinez Lema, David S. Zeman, Vit Kahlert, Lars Jochman, Tomas Burget, Pavel Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague Czech Republic School of Computation Information and Technology Technical University of Munich Munich Germany

ISBN: (纸本)9798350320695

For deploying any robotic solution, the most cumbersome yet essential task remains calibration. Almost every robotic system uses a camera to extract information to produce some output. In the case of the pick-and-place system, camera information is used to detect objects and estimate their position in real-world space. The accuracy of tasks like sorting and stacking the objects in the box depends on their estimated pose in the space, especially when they need to be arranged in a confined space. We propose the automatic calibration of the workspace using distinct markers. Our experimentation was carried out with loose packets of recycled paper, which consists of small parts inside. We evaluate our results on the basis of translation errors of the estimated centroid position of objects with respect to the position given by the calibrated 3D camera. In conclusion, we also assess the typical pick-and-place performance on the success rate of stacking the packets in a small box. © 2023 IEEE.

关键词： Cameras

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CoBOS: Constraint-Based Online Scheduler for Human-Robot Collaboration

CoBOS: Constraint-Based Online Scheduler for Human-Robot Col...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Marina Ionova Jan Kristof Behrens Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Prague

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Assembly processes involving humans and robots are challenging scenarios because the individual activities and access to shared workspace have to be coordinated. Fixed robot programs leave no room to diverge from a fixed protocol. Working on such a process can be stressful for the user and lead to ineffective behavior or failure. We propose a novel approach of online constraint-based scheduling in a reactive execution control framework facilitating behavior trees called CoBOS. This allows the robot to adapt to uncertain events such as delayed activity completions and activity selection (by the human). The user will experience less stress as the robotic coworkers adapt their behavior to best complement the human-selected activities to complete the common task. In addition to the improved working conditions, our algorithm leads to increased efficiency, even in highly uncertain scenarios. We evaluate our algorithm using a probabilistic simulation study with 56000 experiments. We outperform all other compared methods by a margin of 4−10%. Initial real robot experiments using a Franka Emika Panda robot and human tracking based on HTC Vive VR gloves look promising.

关键词： Job shop scheduling Uncertainty Systematics Robot kinematics Human-robot interaction Dynamic scheduling Probabilistic logic Resource management Robots Assembly

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Tell and show: Combining multiple modalities to communicate manipulation tasks to a robot

arXiv

引用

arXiv 2024年

作者： Vanc, Petr Skoviera, Radoslav Stepanova, Karla Czech Technical University in Prague Czech Institute of Informatics Robotics and Cybernetics Czech Republic

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. Current approaches to communication typically rely only on a single modality or are often very rigid and not robust to missing, misaligned, or noisy data. In this paper, we propose a novel method that takes inspiration from sensor fusion approaches to combine uncertain information from multiple modalities and enhance it with situational awareness (e.g., considering object properties or the scene setup). We first evaluate the proposed solution on simulated bimodal datasets (gestures and language) and show by several ablation experiments the importance of various components of the system and its robustness to noisy, missing, or misaligned observations. Then we implement and evaluate the model on the real setup. In human-robot interaction, we have to also consider if the selected action is probable enough to be executed or if we should better query humans for clarification. For these purposes, we enhance our model with adaptive entropy-based thresholding that detects the appropriate thresholds for different types of interaction showing similar performance as fine-tuned fixed thresholds. © 2024, CC BY-NC-SA.

关键词： Sensor data fusion

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