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

作者： Constantin Patsch Wael Torjmene Marsil Zakour Yuankai Wu Driton Salihu Eckehard Steinbach Department of Computer Engineering School of Computation Information and Technology Munich Institute of Robotics and Machine Intelligence (MIRMI) Chair of Media Technology Technical University of Munich Muenchen Germany

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Human reasoning comprises the ability to understand and reason about the current action solely based on past information. To provide effective assistance in an eldercare or household environment an assistive robot or intelligent assistive system has to assess human actions correctly. Based on this presumption, the task of online action detection determines the current action solely based on the past without access to future information. During inference, the performance of the model is largely impacted by the attributes of the underlying training dataset. However, as high costs and ethical concerns are associated with the real-world data collection process, synthetically created data provides a way to mitigate these problems while providing additional data for the training process of the underlying action detection model to improve performanceDue to the inherent domain shift between the synthetic and real data, we introduce a new egocentric dataset called Human Kitchen Interactions (HKI) to investigate the sim-to-real gap. Our dataset contains in total 100 synthetic and real videos in which 21 different actions are executed in a kitchen environment. The synthetic data is acquired in an egocentric virtual reality (VR) setup while capturing the virtual environment in a game engine. We evaluate state-of-the-art online action detection models on our dataset and provide insights into sim-to-real domain shift. Upon acceptance, we will release our dataset and the corresponding features at https://***/HKI/.

关键词： Training Solid modeling Visualization Data acquisition Video sequences Virtual environments Training data Data models Synthetic data Videos

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Generating Force Vectors from Projective Truncated Signed Distance Fields for Collision Avoidance and Haptic Feedback

Generating Force Vectors from Projective Truncated Signed Di...

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

作者： Seongjin Bien Abdeldjallil Naceri Luis Figueredo Sami Haddadin Munich Institute of Robotics and Machine Intelligence (MIRMI) Technische Universität München (TUM) Germany School of Computer Science University of Nottingham UK

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Signed Distance Fields are a common surface representation method widely used for both 3D mapping and obstacle avoidance. While the former traditionally uses projective Truncated Signed Distance Fields (TSDF), the latter often requires a complete Euclidean Signed Distance Field (ESDF) representation of the environment. In this paper, we propose a unified system by combining both methods to generate force vectors to nearby obstacles from a TSDF-based 3D reconstruction. We introduce a new merging scheme to better capture the geometry of the object, with no post-processing requirements, and a way to increase the effective range of the system. Validation experiments demonstrate the accuracy of the force vector calculation by comparing it against an ideal simulated environment. The flexibility of the system is demonstrated by implementing a haptic feedback teleoperation setup, which is validated through a user study in a teleoperation task. Through this, it is shown that the proposed method provides a statistically significant improvement to the task. Finally, a brief description on future improvements to the system is presented.

关键词： Three-dimensional displays Accuracy Statistical analysis Force Merging Robot vision systems Cameras Vectors Haptic interfaces Collision avoidance

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Towards Flexible Biolaboratory Automation: Container Taxonomy-Based, 3D-Printed Gripper Fingers

arXiv

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arXiv 2023年

作者： Zwirnmann, Henning Knobbe, Dennis Culha, Utku Haddadin, Sami School of Computation Information and Technology Technical University of Munich Germany The Munich Institute of Robotics and Machine Intelligence Technical University of Munich Munich80797 Germany

Automation in the life science research laboratory is a paradigm that has gained increasing relevance in recent years. Current robotic solutions often have a limited scope, which reduces their acceptance and prevents the realization of complex workflows. The transport and manipulation of laboratory supplies with a robot is a particular case where this limitation manifests. In this paper, we deduce a taxonomy of biolaboratory liquid containers that clarifies the need for a flexible grasping solution. Using the taxonomy as a guideline, we design fingers for a parallel robotic gripper which are developed with a monolithic dual-extrusion 3D print that integrates rigid and soft materials to optimize gripping properties. We design fine-tuned fingertips that provide stable grasps of the containers in question. A simple actuation system and a low weight are maintained by adopting a passive compliant mechanism. The ability to resist chemicals and high temperatures and the integration with a tool exchange system render the fingers usable for daily laboratory use and complex workflows. We present the task suitability of the fingers in experiments that show the wide range of vessels that can be handled as well as their tolerance against displacements and their grasp stability. Copyright © 2023, The Authors. All rights reserved.

关键词： Taxonomies

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From Human Hand to Grasp Surface Detection, Tracking & Analysis

From Human Hand to Grasp Surface Detection, Tracking & Analy...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Diego Hidalgo-Carvajal Abdeldjallil Naceri Sami Haddadin Technical University of Munich Germany Department of Computer Engineering TUM School of Computation Information and Technology Chair of Robotics and Systems Intelligence (RSI) Munich Institute of Robotics and Machine Intelligence (MIRMI) Centre for Tactile Internet With Human-in-the-Loop (CeTI)

Hands are paramount for dexterous interactions that humans exhibit in daily life. Understanding the intricacies of human hand-object interactions is therefore necessary. Unfortunately, the limitations of state-of-the-art technologies make capturing the full hand-object complexity unfeasible, giving rise to the need for new technological means to achieve this aim. In this work, we propose an end-to-end framework in which individualized hand models are derived and used to capture quantitative personalized hand-object interaction information, precisely, hand shape, kinematics, and contact surfaces. The results of this study serve as a proof of concept that such a framework can significantly deepen personalized hand-object interaction analyses, providing, in perspective, insights for medical diagnoses and rehabilitation, among *** relevance— Our work showcases the need to incorporate bespoke human hand models in individualized hand function assessment technologies, as hand-object interaction information is subject-dependent.

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Biomechanical Test Setup for the Investigation of Forehead Suture Techniques

Biomechanical Test Setup for the Investigation of Forehead S...

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作者： Micheler, Carina M. Lang, Jan J. Wilhelm, Nikolas J. Schaack, Victor G. Eisenhart-Rothe, Rüdiger Von Burgkart, Rainer H. H. Bäumlisberger, Anja Wachtel, Nikolaus Department of Orthopaedics and Sports Orthopaedics University Hospital Rechts der Isar School of Medicine Technical University of Munich Munich Germany Institute for Machine Tools and Industrial Management School of Engineering and Design Technical University of Munich Garching near Munich Germany Non-destructive Testing School of Engineering and Design Technical University of Munich Munich Germany Munich Institute of Robotics and Machine Intelligence Department of Electrical and Computer Engineering Technical University of Munich Munich Germany Division of Hand Plastic and Aesthetic Surgery University Hospital LMU Munich Munich Germany

Wound healing can be delayed if the biomechanical stability of the wound closure is inadequate. Therefore, it is necessary to investigate different suturing techniques for their biomechanical stability. In this study, suturing techniques suitable for the forehead area were investigated. For this application, a special test setup was developed to simulate the curvature of the forehead and the corresponding physiological configuration. The average forehead curvature is 62.24 ± 4.11 mm in radius. To simulate this curvature, the skin specimens are subjected to tensile stress over the spherical surface using a standard uniaxial testing machine. For the evaluation, an automated evaluation tool for MATLAB was also developed. Three different suturing techniques (Straight, Lazy-S, Zigzag) were investigated and tested for their biomechanical stability. Of the three suturing techniques, the Zigzag suture proved to be the most stable with the highest stiffness of 44.23 ± 8.18 % and the highest final failure of 32.60 ± 4.95 % (relative to the control sample without incision). The study has shown that the test setup can be used to investigate different forehead suture techniques. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： MATLAB

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Food: Facial Authentication And Out-Of-Distribution Detection With Short-Range FMCW Radar

Food: Facial Authentication And Out-Of-Distribution Detectio...

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IEEE International Conference on Image Processing

作者： Sabri Mustafa Kahya Boran Hamdi Sivrikaya Muhammet Sami Yavuz Eckehard Steinbach Department of Computer Engineering Chair of Media Technology Munich Institute of Robotics and Machine Intelligence (MIRMI) School of Computation Information and Technology Technical University of Munich Infineon Technologies AG

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

This paper proposes a short-range FMCW radar-based facial authentication and out-of-distribution (OOD) detection framework. Our pipeline jointly estimates the correct classes for the in-distribution (ID) samples and detects the OOD samples to prevent their inaccurate prediction. Our reconstruction-based architecture consists of a main convolutional block with one encoder and multi-decoder configuration, and intermediate linear encoder-decoder parts. Together, these elements form an accurate human face classifier and a robust OOD detector. For our dataset, gathered using a 60 GHz short-range FMCW radar, our network achieves an average classification accuracy of 98.07% in identifying in-distribution human faces. As an OOD detector, it achieves an average Area Under the Receiver Operating Characteristic (AUROC) curve of 98.50% and an average False Positive Rate at 95% True Positive Rate (FPR95) of 6.20%. Also, our extensive experiments show that the proposed approach outperforms previous OOD detectors in terms of common OOD detection metrics.

关键词： Accuracy Pipelines Neural networks Authentication Radar detection Detectors Radar

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HAROOD: Human Activity Classification and Out-Of-Distribution Detection with Short-Range FMCW Radar

HAROOD: Human Activity Classification and Out-Of-Distributio...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Sabri Mustafa Kahya Muhammet Sami Yavuz Eckehard Steinbach Department of Computer Engineering Chair of Media Technology Munich Institute of Robotics and Machine Intelligence (MIRMI) Technical University of Munich School of Computation Information and Technology Infineon Technologies AG

We propose HAROOD as a short-range FMCW radar-based human activity classifier and out-of-distribution (OOD) detector. It aims to classify human sitting, standing, and walking activities and to detect any other moving or stationary object as OOD. We introduce a two-stage network. The first stage is trained with a novel loss function that includes intermediate reconstruction loss, intermediate contrastive loss, and triplet loss. The second stage uses the first stage’s output as its input and is trained with cross-entropy loss. It creates a simple classifier that performs the activity classification. On our dataset collected by 60 GHz short-range FMCW radar, we achieve an average classification accuracy of 96.51%. Also, we achieve an average AUROC of 95.04% as an OOD detector. Additionally, our extensive evaluations demonstrate the superiority of HAROOD over the state-of-the-art OOD detection methods in terms of standard OOD detection metrics.

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SCTOMP: Spatially Constrained Time-Optimal Motion Planning

SCTOMP: Spatially Constrained Time-Optimal Motion Planning

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

作者： Jon Arrizabalaga Markus Ryll Autonomous Aerial Systems School of Engineering and Design Technical University of Munich Germany Munich Institute of Robotics and Machine Intelligence (MIRMI) Technical University of Munich

This work focuses on spatial time-optimal motion planning, a generalization of the exact time-optimal path following problem that allows a system to plan within a predefined space. In contrast to state-of-the-art methods, we drop the assumption of a given collision-free geometric reference. Instead, we present a three-stage motion planning method that solely relies on start and goal locations and a geometric representation of the environment to compute a time-optimal trajectory that is compliant with system dynamics and constraints. The proposed scheme first finds collision-free navigation corridors, second computes an obstacle-free Pythagorean Hodograph parametric spline along each corridor, and third, solves a spatially reformulated minimum-time optimization problem at each of these corridors. The spline obtained in the second stage is not a geometric reference, but an extension of the free space associated with its corridor, and thus, time-optimality of the solution is guaranteed. The validity of the proposed approach is demonstrated by a well-established planar example and benchmarked in a spatial system against state-of-the-art methodologies across a wide range of scenarios in highly congested environments. Video: https://***/zGExvnUEfOY

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Embedded Ethics and the “Soft Impacts” of Technology

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Bulletin of Science, Technology and Society 2024年第3-4期44卷 73-83页

作者： Tigard, Daniel W. Braun, Maximilian Breuer, Svenja Fiske, Amelia McLennan, Stuart Buyx, Alena University of San Diego San Diego CA United States Institute for Experiential AI Northeastern University MA Boston Thailand Department of Science Technology & Society School of Social Science and Technology and Department of Economics and Policy School of Management Technical University of Munich Germany Institute of History and Ethics in Medicine Department of Preclinical Medicine TUM School of Medicine and Health Technical University of Munich Munchen Germany Institute for Biomedical Ethics University of Basel Basel Switzerland Munich Institute of Robotics and Machine Intelligence Technical University of Munich Munchen Germany

Advanced technologies, such as artificial intelligence (AI) and robotics, are increasingly common, but often come with significant tradeoffs and effects which may elude initial observations. Among these, the term “soft impacts” has come to signify the qualitative implications of a technological device or intervention. How can these sorts of effects be addressed, and what role do they have in the development phases of emerging technologies? In this paper, we outline our interdisciplinary Responsible robotics project, which harnesses and builds upon an embedded ethics framework. We describe the embedded ethics approach, summarize some of its challenges, and highlight a key benefit. In short, by addressing the so-called “soft impacts” of technology, embedded ethics may stand to benefit not only the users of emerging systems, but also the developers. Although confirming this with a great degree of confidence will call for substantive longitudinal studies, we believe the aims and current roll-out of the embedded ethics approach provide grounds for optimism concerning the intended benefits described here. Accordingly, the mere prospect of increasing social and ethical sensitivity in development settings can serve to encourage a wider adoption of embedded ethics programs worldwide. © The Author(s) 2024.

关键词： AI ethics embedded ethics responsible robotics soft impacts technology ethics

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Pose-Following with Dual Quaternions

Pose-Following with Dual Quaternions

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IEEE Conference on Decision and Control

This work focuses on pose-following, a variant of path-following in which the goal is to steer the system's position and attitude along a path with a moving frame attached to it. Full body motion control, while accounting for the additional freedom to self-regulate the progress along the path is an appealing trade-off. Towards this end, we extend the well-established dual quaternion based pose-tracking method into a pose-following control law. Specifically, we derive the equations of motion for the full pose error between the geometric reference and the rigid body in the form of a dual quaternion and dual twist, and subsequently, formulate an almost globally asymptotically stable control law. The global attractivity of the presented approach is validated in a spatial example, while its benefits over pose-tracking are showcased through a planar case-study.

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