检索结果-内蒙古大学图书馆

Large spin accumulation signals in ultrafast magneto-optical experiments.

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Anadón, Alberto Singh, Harjinder Díaz, Eva Le-Guen, Yann Hohlfeld, Julius Wilson, Richard B. Malinowski, Gregory Hehn, Michel Gorchon, Jon Université de Lorraine CNRS IJL NancyF-54000 France Department of Mechanical Engineering and Materials Science and Engineering Program University of California RiversideCA United States

Magneto-optical techniques have become essential tools in spintronics, enabling the investigation of spin dynamics in the ultrafast regime. A key challenge in this field has been to accurately isolate the contributions to magneto-optical signals of spin transport phenomena from the local magnetization dynamics. The contribution of transported and accumulated spins was long believed to be orders of magnitude smaller than that of the magnetization and thus previous approaches to disentangle these signals have relied on specific experimental designs, usually including thick metal layers. Here, we present experimental evidence demonstrating that the magneto-optical signal from ultrafast spin accumulations can, under certain conditions, be comparable to or even exceed that of the magnetic layer in a standard ultrafast demagnetization experiment. Our findings provide a new framework for accessing and isolating these spin accumulations, allowing for time and depth dependent probing of transported spin and/or orbital angular momentum. © 2025, CC BY.

关键词： Spin dynamics

Meta-Learning-Based Optimal Control for Soft Robotic Manipulators to Interact with Unknown Environments

学校读者我要写书评

暂无评论

Meta-Learning-Based Optimal Control for Soft Robotic Manipul...

IEEE International Conference on robotics and Automation (ICRA)

作者： Zhiqiang Tang Peiyi Wang Wenci Xin Zhexin Xie Longxin Kan Muralidharan Mohanakrishnan Cecilia Laschi Department of Mechanical Engineering National University of Singapore Singapore Robotics Research Center Beijing Jiaotong University Beijing China

Safe and efficient robot-environment interaction is a critical but challenging problem as robots are being increasingly employed to operate in unstructured and unpredictable environments. Soft robots are inherently compliant to safely interact with environments but their high nonlinearity exacerbates control difficulties. Meta-learning provides a powerful tool for fast online model adaptation because it can learn an efficient model from data across different environments. Thus, this work applies the idea of meta-learning for the control of soft robotics. In particular, a target-oriented proactive search strategy is firstly performed to collect environment-specific data efficiently when a new interaction environment occurs. Then meta-learning exploits past experience to train a data-driven probabilistic model prior, and the model prior is online updated to be fast adapted to the new environment. Lastly, a model-based optimal control policy is utilized to drive the robot to desired performance. Our approach controls a soft robotic manipulator to achieve the desired position and contact force simultaneously when interacting with unknown changing environments. Overall, this work provides a viable control approach for soft robots to interact with unknown environments.

关键词：

Human-Humanoid Robots Cross-Embodiment Behavior-Skill Transfer Using Decomposed Adversarial Learning from Demonstration

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Liu, Junjia Li, Zhuo Yu, Minghao Dong, Zhipeng Calinon, Sylvain Caldwell, Darwin Chen, Fei Department of Mechanical and Automation Engineering T-Stone Robotics Institute The Chinese University of Hong Kong Hong Kong Idiap Research Institute Martigny Switzerland Department of Advanced Robotics Istituto Italiano di Tecnologia Genoa Italy

Humanoid robots are envisioned as embodied intelligent agents capable of performing a wide range of human-level loco-manipulation tasks, particularly in scenarios requiring strenuous and repetitive labor. However, learning these skills is challenging due to the high degrees of freedom of humanoid robots, and collecting sufficient training data for humanoid is a laborious process. Given the rapid introduction of new humanoid platforms, a cross-embodiment framework that allows generalizable skill transfer is becoming increasingly critical. To address this, we propose a transferable framework that reduces the data bottleneck by using a unified digital human model as a common prototype and bypassing the need for re-training on every new robot platform. The model learns behavior primitives from human demonstrations through adversarial imitation, and the complex robot structures are decomposed into functional components, each trained independently and dynamically coordinated. Task generalization is achieved through a human-object interaction graph, and skills are transferred to different robots via embodimentspecific kinematic motion retargeting and dynamic fine-tuning. Our framework is validated on five humanoid robots with diverse configurations, demonstrating stable loco-manipulation and highlighting its effectiveness in reducing data requirements and increasing the efficiency of skill transfer across platforms. Copyright © 2024, The Authors. All rights reserved.

关键词： Anthropomorphic robots

Uncovering Variability in Human Driving Behavior Through Automatic Extraction of Similar Traffic Scenes from Large Naturalistic Datasets

学校读者我要写书评

暂无评论

Uncovering Variability in Human Driving Behavior Through Aut...

IEEE International Conference on Systems, Man and Cybernetics

作者： Olger Siebinga Arkady Zgonnikov David Abbink Department of Cognitive Robotics Human-Robot Interaction Group Faculty of Mechanical Engineering Delft University of Technology Delft The Netherlands

Recently, multiple naturalistic traffic datasets of human-driven trajectories have been published (e.g., highD, NGSim, and pNEUMA). These datasets have been used in studies that investigate variability in human driving behavior, for example for scenario-based validation of autonomous vehicle (AV) behavior, modeling driver behavior, or validating driver models. Thus far, these studies focused on the variability on an operational level (e.g., velocity profiles during a lane change), not on a tactical level (i.e., to change lanes or not). Investigating the variability on both levels is necessary to develop driver models and AV s that include multiple tactical behaviors. To expose multi-level variability, the human responses to the same traffic scene could be investigated. However, no method exists to automatically extract similar scenes from datasets. Here, we present a four-step extraction method that uses the Hausdorff distance, a mathematical distance metric for sets. We performed a case study on the highD dataset that showed that the method is practically applicable. The human responses to the selected scenes exposed the variability on both the tactical and operational levels. With this new method, the variability in operational and tactical human behavior can be investigated, without the need for costly and time-consuming driving-simulator experiments.

关键词：

Exploring Modal Switch in Metamaterial-Based Robots

学校读者我要写书评

暂无评论

Exploring Modal Switch in Metamaterial-Based Robots

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

作者： Britton Jordan Daniel S. Esser Jeonghyeon Kim Brian Y. Cho Robert J. Webster Alan Kuntz Robotics Center and the Kahlert School of Computing University of Utah Salt Lake City UT USA Department of Mechanical Engineering Vanderbilt University Nashville TN

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

mechanical metamaterials are microscale patterned structures that are designed to have specific mechanical properties at a macro-scale that are atypical of natural materials. Robotic manipulators composed of these materials can exhibit deformation and motion capabilities that can be customized and easily fabricated. However, as of now, the motion capability of such manipulators are encoded in their physical composition and cannot be changed. This paper presents multimodal metamaterial-based robot prototypes which can switch between the behaviors found in two different metamaterials. Two such robots are explored, a bending/shearing robot and a bending/twisting robot. The robot design is described in detail, including how the robots toggle between behavior modes via mechanical actuation of a sliding rod insert. Multi-modal robots are compared to their single-mode equivalents to characterize their capabilities. The single-mode behaviors are largely preserved in the multi-modal innovations. The multi-modal prototypes also demonstrate variable rigidity. We discuss the feasibility of using robots of this design as part of a robotic surgical system.

关键词： Technological innovation Deformation Prototypes Switches Microsurgery Manipulators Metamaterials Rigidity Polymers Robots

Dataset and Benchmark: Novel Sensors for Autonomous Vehicle Perception

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Carmichael, Spencer Buchan, Austin Ramanagopal, Mani Ravi, Radhika Vasudevan, Ram Skinner, Katherine A. Robotics Department University of Michigan Ann ArborMI48109 United States Department of Mechanical Engineering University of Michigan Ann ArborMI48109 United States

Conventional cameras employed in autonomous vehicle (AV) systems support many perception tasks, but are challenged by low-light or high dynamic range scenes, adverse weather, and fast motion. Novel sensors, such as event and thermal cameras, offer capabilities with the potential to address these scenarios, but they remain to be fully exploited. This paper introduces the Novel Sensors for Autonomous Vehicle Perception (NSAVP) dataset to facilitate future research on this topic. The dataset was captured with a platform including stereo event, thermal, monochrome, and RGB cameras as well as a high precision navigation system providing ground truth poses. The data was collected by repeatedly driving two ∼8 km routes and includes varied lighting conditions and opposing viewpoint perspectives. We provide benchmarking experiments on the task of place recognition to demonstrate challenges and opportunities for novel sensors to enhance critical AV perception tasks. To our knowledge, the NSAVP dataset is the first to include stereo thermal cameras together with stereo event and monochrome cameras. The dataset and supporting software suite is available at: https://***/nsavp. © 2024, CC BY-NC-SA.

关键词： Computer vision

Deformable Object Manipulation With Constraints Using Path Set Planning and Tracking

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Huang, Jing Chu, Xiangyu Ma, Xin Au, Kwok Wai Samuel The Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong The Multi-Scale Medical Robotics Center Hong Kong Hong Kong

In robotic deformable object manipulation (DOM) applications, constraints arise commonly from environments and task-specific requirements. Enabling DOM with constraints is therefore crucial for its deployment in practice. However, dealing with constraints turns out to be challenging due to many inherent factors such as inaccessible deformation models of deformable objects (DOs) and varying environmental setups. This article presents a systematic manipulation framework for DOM subject to constraints by proposing a novel path set planning and tracking scheme. First, constrained DOM tasks are formulated into a versatile optimization formalism which enables dynamic constraint imposition. Because of the lack of the local optimization objective and high state dimensionality, the formulated problem is not analytically solvable. To address this, planning of the path set, which collects paths of DO feedback points, is proposed subsequently to offer feasible path and motion references for DO in constrained setups. Both theoretical analyses and computationally efficient algorithmic implementation of path set planning are discussed. Lastly, a control architecture combining path set tracking and constraint handling is designed for task execution. The effectiveness of our methods is validated in a variety of DOM tasks with constrained experimental settings. Copyright © 2024, The Authors. All rights reserved.

关键词： Constraint handling

In Situ Material Identification, Machining Monitoring, and Cloud Logging Integrated with AI and Machine Vision

学校读者我要写书评

暂无评论

In Situ Material Identification, Machining Monitoring, and C...

Innovative Trends in Information Technology (ICITIIT), International Conference on

作者： Penumuru Durga Prasad Deep Patel Sreekumar Muthuswamy Premkumar Karumbu Department of Mechanical Engineering Centre for AI IoT and Robotics Indian Institute of Information Technology Design and Manufacturing Kancheepuram Kancheepuram Chennai India Department of Electronics and Communications Engineering. Centre for AI IoT and Robotics Indian Institute of Information Technology Design and Manufacturing Kancheepuram Kancheepuram Chennai India

ISBN: (数字)9798350386813

ISBN: (纸本)9798350386820

Current process monitoring in machining hampers manufacturing efficiency due to manual data entry, fragmented systems, and lack of real-time data capture. This challenge is particularly tough for small to medium-sized enterprises (SMEs) without advanced tools. Our proposed methodology employs a collaborative robot (UR16e) with a machine vision system (InSight 7802C). The robot shifts the vision system to capture images of machining processes and workpieces. Enhanced with a fine-tuned Support Vector Machine (SVM) classifier, the vision system accurately identifies Aluminum, Copper, Mild Steel, and Medium-density fibreboard (MDF). Operational data, including material types and machine usage, is locally recorded and uploaded to Microsoft Azure cloud storage for data integrity and stakeholder transparency. This approach enhances process control and decision-making. Preliminary results validate its practicality and potential to boost manufacturing process monitoring. It sets a solid foundation for further exploration into smart manufacturing research, which is crucial for staying competitive in today’s rapidly evolving industrial landscape.

关键词： Support vector machines Process monitoring Cloud computing Service robots Machine vision Machining Drilling machines

BlueLink: A Bidirectional Optical Modem for High-Speed Underwater Communication

学校读者我要写书评

暂无评论

BlueLink: A Bidirectional Optical Modem for High-Speed Under...

IEEE International Workshop on Metrology for the Sea;Learning to Measure Sea Health Parameters (MetroSea)

作者： Ivar Bjørgo Saksvik Vahid Hassani Antonio Pascoal Alex Alcocer Department of Mechanical Electronic and Chemical Engineering Oslo Metropolitan University Oslo Norway Laboratory of Robotics and Systems in Engineering and Science (LARSyS) University of Lisbon Lisbon Portugal

Free space optical communication has emerged as a highly promising solution for enabling high-speed data transmission in underwater environments. The increasing demand for telemetry in unmanned underwater vehicles requires a significant increase in bandwidth capacity, surpassing the limitations of conventional acoustic technologies that currently dominate this domain. In this paper, we introduce a compact and energy-efficient optical modem for high-speed wireless underwater communication. The proposed modem offers bidirectional data transfer capabilities through the integration of transmitting LEDs and a photodiode receiver for light pulse detection, with data processing efficiently managed by an FPGA. The modem utilizes a software-defined architecture, enabling re-configurable modulation schemes and streamlining the implementation of signal filtering and processing through software, as opposed to traditional analog circuitry. Experiments conducted in a 3-meter seawater pool demonstrate a throughput of 2 Mbit/s.

关键词：