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检索条件"机构=Munich School of Robotics and Machine Intelligence and Robotics and System Intelligence"

共 225 条记录，以下是81-90 订阅

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Accurate Kinematic Modeling using Autoencoders on Differentiable Joints

Accurate Kinematic Modeling using Autoencoders on Differenti...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Nikolas Wilhelm Sami Haddadin Rainer Burgkart Patrick Van Der Smagt Maximilian Karl Munich Institute of Robotics and Machine Intelligence Technical University of Munich Munich Germany Department of Orthopedics and Sports Orthopedics Klinikum Rechts der Isar School of Medicine Munich Germany Volkswagen Group Machine Learning Research Lab Munich Germany

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In robotics and biomechanics, accurately determining joint parameters and computing the corresponding forward and inverse kinematics are critical yet often challenging tasks, especially when dealing with highly individualized and partly unknown systems. This paper unveils a cutting-edge kinematic optimizer, underpinned by an autoencoder-based architecture, to address these challenges. Utilizing a neural network, our approach simulates inverse kinematics, converting measurement data into joint-specific parameters during encoding, enabling a stable optimization process. These parameters are subsequently processed through a predefined, differentiable forward kinematics model, resulting in a decoded representation of the original data. Beyond offering a comprehensive solution to kinematics challenges, our method also unveils previously unidentified joint parameters. Real experimental data from knee and hand joints validate the optimizer’s efficacy. Additionally, our optimizer is multifunctional: it streamlines the modeling and automation of kinematics and enables a nuanced evaluation of diverse modeling techniques. By assessing the differences in reconstruction losses, we illuminate the merits of each approach. Collectively, this preliminary study signifies advancements in kinematic optimization, with potential applications spanning both biomechanics and robotics.

关键词： Biomechanics Automation Biological system modeling Neural networks Kinematics Computer architecture Encoding

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Accelerating Reliability Analysis for Aging and Self-Heating using machine Learning

Accelerating Reliability Analysis for Aging and Self-Heating...

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IEEE International Symposium on Quality Electronic Design

作者： Tarek Mohamed Hussam Amrouch Semiconductor Test and Reliability University of Stuttgart Stuttgart Germany Chair of AI Processor Design Technical University of Munich TUM School of Computation Information and Technology Munich Institute of Robotics and Machine Intelligence

ISBN: (数字)9798331509422

ISBN: (纸本)9798331509439

The relentless drive for advanced technologies, fueled by the demands of AI and safety-critical applications, has intensified the focus on transistor aginga pivotal concern that undermines both transistor reliability and overall circuit performance. This issue is further exacerbated by advancements in packaging and 3D integration, where elevated operating temperatures accelerate aging mechanisms. As technology nodes scales below 3 nm, transistor self-heating emerges as a fundamental challenge, driven by the thermal constraints of 3D confined structures. Traditional physics-based simulation tools, such as Technology CAD (TCAD), struggle to meet the growing computational demands of these intricate designs, with escalating simulation times that impede comprehensive design exploration and optimization. Here, we present a novel framework leveraging machine learning (ML) to accelerate transistor and circuit reliability analysis. These ML-driven methodologies achieve accurate predictions of self-heating and aging effects, enabling rapid identification of aging-prone transistors while drastically reducing computational overhead. Furthermore, by obviating the need to share proprietary, physics-based models from semiconductor foundries, these techniques preserve data confidentiality, addressing critical industry concerns. Such approach not only enhances the scalability of reliability assessments but also offers a transformative pathway for tackling the multifaceted challenges of next-generation semiconductor technologies.

关键词： Solid modeling Accuracy Accelerated aging machine learning Reliability engineering Foundries Transistors Integrated circuit reliability Integrated circuit modeling Three-dimensional integrated circuits

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Spherical Cubic Blends: $\mathcal{C}^{2}$-Continuous, Zero-Clamped, and Time-Optimized Interpolation of Quaternions

Spherical Cubic Blends: $\mathcal{C}^{2}$-Continuous, Zero-C...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jonas Wittmann Lukas Cha Marco Kappertz Philipp Seiwald Daniel J. Rixen Department of Mechanical Engineering Technical University of Munich TUM School of Engineering and Design Munich Institute of Robotics and Machine Intelligence (MIRMI) Garching Germany

Modern collaborative robotic applications require robot motions that are predictable for human coworkers. Therefore, trajectories often need to be planned in task space rather than configuration space ( $\mathcal{C}$ -space). While the interpolation of translations in Euclidean space is straightforward, the interpolation of rotations in $SO(3)$ is more complex. Most approaches originating from computer graphics do not exhibit the often desired $\mathcal{C}^{2}$ -continuity in robotics. Our main contribution is a $\mathcal{C}^{2}$ -continuous, zero-clamped interpolation scheme for quaternions that computes a fast synchronized motion given a set of waypoints. As a second contribution, we present modifications to two state-of-the-art quaternion interpolation schemes, Spherical Quadrangle Interpolation (SQUAD) and Spherical Parabolic Blends (SPB), to enable them to compute $\mathcal{C}^{2}$ -continuous, zero-clamped trajectories. In experiments, we demonstrate that for the time optimization of trajectories, our approach is computationally efficient and at the same time computes smooth trajectory profiles.

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Towards Unconstrained Collision Injury Protection Data Sets: Initial Surrogate Experiments for the Human Hand

Towards Unconstrained Collision Injury Protection Data Sets:...

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

作者： Robin Jeanne Kirschner Jinyu Yang Edonis Elshani Carina M. Micheler Tobias Leibbrand Dirk Müller Claudio Glowalla Nader Rajaei Rainer Burgkart Sami Haddadin Chair for Robotics and Systems Intelligence Munich Institute of Robotics and Machine Intelligence Technical University of Munich Munich Germany Department of Orthopaedics and Sports Orthopaedics Klinikum Rechts der Isar TUM School of Medicine Technical University of Munich Munich Germany Institute for Machine Tools and Industrial Management TUM School of Engineering and Design Technical University of Munich Garching Near Munich Germany Endoprothetikzentrum der Maximalversorgung BG Hospital Murnau Murnau Germany

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Safety for physical human-robot interaction (pHRI) is a major concern for all application domains. While current standardization for industrial robot applications provide safety constraints that address the onset of pain in blunt impacts, these impact thresholds are difficult to use on edged or pointed impactors. The most severe injuries occur in constrained contact scenarios, where crushing is possible. Nevertheless, situations potentially resulting in constrained contact only occur in certain areas of a workspace and design or organisational approaches can be used to avoid them. What remains are risks to the human physical integrity caused by unconstrained accidental contacts, which are difficult to avoid while maintaining robot motion efficiency. Nevertheless, the probability and severity of injuries occurring with edged or pointed impacting objects in unconstrained collisions is hardly researched. In this paper, we propose an experimental setup and procedure using two pendulums modeling human hands and arms and robots to understand the injury potential of unconstrained collisions of human hands with edged objects. Pig feet are used as ex vivo surrogate samples - as these closely resemble the physiological characteristics of human hands - to create an initial injury database on the severity of injuries caused by unconstrained edged or pointed impacts. For the effective mass range of typical lightweight robots, the data obtained show low probabilities of injuries such as skin cuts or bone/tendon injuries in unconstrained collisions when the velocity is reduced to < 0.5 m/s. Additionally, distinct differences between injury probability of the finger substitutes and the back of the hand substitutes are observed. The proposed experimental setups and procedures should be complemented by sufficient human modeling, e.g. the effective masses of human body parts, and will eventually lead to a complete understanding of the biomechanical injury potential in pHRI.

关键词： Hands Geometry Robot motion Human-robot interaction Standardization Skin Effective mass Collision avoidance Injuries Foot

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Offset-Aware Dual Quaternion Control for UAVs with Cable-Suspended Loads

Offset-Aware Dual Quaternion Control for UAVs with Cable-Sus...

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International Conference on Unmanned Aircraft systems (ICUAS)

作者： Yuxia Yuan Lukas Pries Markus Ryll Autonomous Aerial Systems School of Engineering and Design Technical University of Munich Ottobrunn Germany Munich Institute of Robotics and Machine Intelligence (MIRMI) and Autonomous Aerial Systems School of Engineering and Design Technical University of Munich Ottobrunn Germany

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Modeling the kinematics and dynamics of UAVs with cable-suspended loads using dual quaternions remains an area requiring further exploration, especially when considering the offset between the attachment point and the UAV's center of mass. This work introduces a novel control strategy based on dual quaternions for sling load cargo UAV (cUAV) systems with offset attachments. Leveraging the mathematical efficiency and compactness of dual quaternions, we establish a unified representation of the kinematics and dynamics of both the UAV and its suspended load. Extensive simulations and realworld experiments were conducted to evaluate the accuracy and robustness of the proposed strategy. The results demonstrate the controller's reliability and stability across various conditions in practical cUAV applications. This study makes a contribution to the presentation of this novel control strategy that harnesses the benefits of dual quaternions for cUAVs. Our work also holds promise for inspiring future innovations in under-actuated systems control using dual quaternions.

关键词： Technological innovation Accuracy Quaternions Transportation Kinematics Autonomous aerial vehicles Stability analysis Robustness Trajectory Load modeling

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RETOM: Leveraging Maneuverability for Reactive Tool Manipulation using Wrench-Fields

RETOM: Leveraging Maneuverability for Reactive Tool Manipula...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Felix Eberle Riddhiman Laha Haowen Yao Abdeldjallil Naceri Luis F.C. Figueredo Sami Haddadin Munich Institute of Robotics & Machine Intelligence Technische Universität München (TUM) Germany School of Computer Science University of Nottingham UK MIRMI Technical University of Munich (TUM)

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper investigates the problem of effective tool manipulation for motion planning in complex human-like scenarios. Vector-field-based real-time strategies, although widely used, usually do not account for unwieldy tools or incorporate systematic methods to handle these extra maneuvers needed. Instead, we formalize the problem and propose a novel field-based reactive planner that explicitly accounts for rotational forces for seamless maneuvers based on the tool’s geometry and featured points. Furthermore, we capture and encode robot performance through capability metrics and improve the same using an additional quality distribution method. This enables seamless integration of the robot’s embodiment with the reactive force-torque (wrench) field giving rise to flexible tool usage in non-stationary environments. Extensive simulation analysis on a 7 DoF collaborative robot manipulating a common tool in an unorganized table-top layout reinforces our claim of robustness in stationary and non-stationary scenarios.

关键词： Measurement Geometry systematics Layout Collaborative robots Robustness Real-time systems

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Notion on the Correct Use of the Robot Effective Mass in the Safety Context and Comments on ISO/TS 15066

Notion on the Correct Use of the Robot Effective Mass in the...

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IEEE International Conference on intelligence and Safety for robotics (ISR)

作者： Robin Jeanne Kirschner Nico Mansfeld Guillermo Gómez Peña Saeed Abdolshah Sami Haddadin Institute for Robotics and System Intelligence Munich School of Robotics and Machine Intelligence Technical University of Munich Munich Germany

Collision experiments in the human-robot interaction (HRI) context showed that the effective robot mass is one of the main parameters that influence human injury probability during a collision. Also the current standard ISO/TS 15066 highlights the importance of this parameter and provides a method to determine the maximum safe robot velocity based on the effective mass. To enable both safe and efficient robot applications, it is crucial to derive the robot's instantaneous effective mass sufficiently accurate based on either a), a kinematic and dynamic model or b), a suitable collision experiment. In this paper, we describe and quantitatively compare the well-established reflected mass model by Khatib and the simplified model provided in the ISO/TS 15066 for the KUKA LWR IV + and the Franka Emika Panda robot. Furthermore, we propose a method to practically determine the effective mass using a passive mechanical pendulum setup. Our results show that the simplified ISO/TS model can lead to a significant safety-relevant error. With our preliminary experimental setup, however, we can verify that the reflected mass obtained by the dynamics model only differs 1.1-7.8 P% from the measured value.

关键词： Limiting Kinematics Real-time systems Safety Effective mass Reliability Collision avoidance

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Design and Implementation of a Robotic Testbench for Analyzing Pincer Grip Execution in Human Specimen Hands

Design and Implementation of a Robotic Testbench for Analyzi...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Nikolas Wilhelm Claudio Glowalla Sami Haddadin Julian Schote Hannes Höppner Patrick van der Smagt Maximilian Karl Rainer Burgkart Department of Orthopedics and Sports Orthopedics Klinikum Rechts der Isar School of Medicine Munich Germany Munich Institute of Robotics and Machine Intelligence Technical University of Munich Munich Germany Humanoid Robotics Laboratory Berliner Hochschule für Technik Berlin Germany Machine Learning Research Lab Volkswagen Group Munich Germany

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This study presents an innovative test rig engineered to explore the kinematic and viscoelastic characteristics of human specimen hands. The rig features eight force-controlled motors linked to muscle tendons, enabling precise stimulation of hand specimens. Hand movements are monitored through an optical tracking system, while a force-torque sensor quantifies the resultant fingertip loads. Employing this setup, we successfully demonstrated a pincer grip using a cadaver hand and measured both muscle forces and grip strength. Our results reveal a nonlinear relationship between tendon forces and grip strength, which can be modeled by an exponential fit. This investigation serves as a nexus between biomechanical and robotics-focused research, providing critical insights for the advancement of robotic hand actuation and therapeutic interventions.

关键词： Biomechanics Technological innovation Tracking Stimulated emission Biological system modeling Muscles Motors

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OPENGRASP-LITE Version 1.0: A Tactile Artificial Hand with a Compliant Linkage Mechanism

OPENGRASP-LITE Version 1.0: A Tactile Artificial Hand with a...

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

作者： Sonja Groß Michael Ratzel Edgar Welte Diego Hidalgo-Carvajal Lingyun Chen Edmundo Pozo Fortunić Amartya Ganguly Abdalla Swikir Sami Haddadin Technical University of Munich Germany TUM School of Computation Information and Technology (CIT) Chair of Robotics and Systems Intelligence (RSI) Munich Institute of Robotics and Machine Intelligence (MIRMI) The Centre for Tactile Internet With Human-in-the-Loop (CeTI) Department of Electrical and Electronic Engineering Omar Al-Mukhtar University (OMU) Albaida Libya

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Recent advancements in artificial hand development have primarily concentrated on enhancing adaptive grasping, dexterity, as well as the integration of biomimetic skin. However, few designs have successfully combined lightweight, cost-effective solutions, and tactile sensing along with adaptive grasping in a human-sized prototype. We propose, an open-source, highly integrated artificial hand. It leverages a compliant linkage mechanism for versatile grasping capabilities, featuring six degrees of actuation and MEMS-based tactile sensors on every fingertip.

关键词： Hands Couplings Biomimetics Tactile sensors Prototypes Grasping Skin Sensors Intelligent robots

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A Safe Reinforcement Learning driven Weights-varying Model Predictive Control for Autonomous Vehicle Motion Control

A Safe Reinforcement Learning driven Weights-varying Model P...

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IEEE Symposium on Intelligent Vehicle

作者： Baha Zarrouki Marios Spanakakis Johannes Betz Chair of Automotive Technology TUM School of Engineering and Design Technical University of Munich Professorship of Autonomous Vehicle Systems TUM School of Engineering and Design Technical University of Munich Munich Institute of Robotics and Machine Intelligence (MIRMI)

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

Determining the optimal cost function parameters of Model Predictive Control (MPC) to optimize multiple control objectives is a challenging and time-consuming task. Multi-objective Bayesian Optimization (BO) techniques solve this problem by determining a Pareto optimal parameter set for an MPC with static weights. However, a single parameter set may not deliver the most optimal closed-loop control performance when the context of the MPC operating conditions changes during its operation, urging the need to adapt the cost function weights at runtime. Deep Reinforcement Learning (RL) algorithms can automatically learn context-dependent optimal parameter sets and dynamically adapt for a Weights-varying MPC (WMPC). However, learning cost function weights from scratch in a continuous action space may lead to unsafe operating states. To solve this, we propose a novel approach limiting the RL action space within a safe learning space that we represent by a catalog of pre-optimized feasible BO Pareto-optimal weight sets. We conceive an RL agent not to learn in a continuous space but to select the most optimal discrete actions, each corresponding to a single set of Pareto optimal weights, by proactively anticipating upcoming control tasks in a context-dependent manner. This approach introduces a two-step optimization: (1) safety-critical with BO and (2) performance-driven with RL. Hence, even an untrained RL agent guarantees a safe and optimal performance. Simulation results demonstrate that an untrained RL-WMPC shows Pareto-optimal closed-loop behavior and training the RL-WMPC helps exhibit a performance beyond the Pareto-front. The code used in this research is publicly accessible as open-source software: https://***/bzarr/TUM-CONTROL

关键词： Training Runtime Simulation Pareto optimization Aerospace electronics Cost function Task analysis

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