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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Su, Zhilong Wang, Can Wu, Xinyu Dong, Yao Ni, Jiangpeng He, Bailin Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Beijing100049 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9781665436786

This paper proposed a framework of cooperative UAV-UGV system. This system consists of three modules: UAV, UGV, and ground station console. It has the characteristics of high cohesion, low coupling, cross platform, and cross language. Compared with the prior methods which UAV-UGV cooperation system that only uses UAV to track UGV, our method is more effective and can give full play to the advantages of UAV and UGV. We use UAV visual tracking algorithm and coordinate transformation to get the target location, and use UGV to navigate to the target location to keep up with the target. The high mobility of UAV makes the target tracking range of the whole system larger, the robustness of UGV is good, and the tasks can be performed more precisely. © 2021 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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A one-step pseudolinear kalman filter for invasive target tracking in three-dimensional space

A one-step pseudolinear kalman filter for invasive target tr...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Zhang, Ying Liang, Rui Xu, Sheng Zhang, Liyuan Zhang, Ye Xiao, Dandan State Grid Tianjin Electric Power Company City West Power Supply Branch Tianjin300190 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9781665436786

This work studies the characteristics of the 3-dimensional (3D) pseudolinear Kalman filter (PLKF) proposed in the previous work [1] for angle-of-arrival (AOA) target tracking in the 3D space. The previous two-step 3D PLKF contains an xy-PLKF and a z-PLKF. This paper develops a one-step PLKF algorithm, which has low computational complexity. The estimation performance analysis of these two different PLKFs is provided. The one-step PLKF sacrifices the estimation accuracy to acquire a low computational complexity. In the distributed target tracking problem, the one-step PLKF can save a lot of communication costs compared with the two-step one. Furthermore, the stability of two PLKFs are also been simply proven. Simulation examples verify the effectiveness of the proposed one-step 3D PLKF to track an invasive target. Besides, the difference between the two PLKFs based on the theoretical analysis is also demonstrated by the simulation examples. © 2021 IEEE.

关键词： Target tracking

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Development of a magnetoelectric neural stimulator for in vitro experiments

Development of a magnetoelectric neural stimulator for in vi...

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IEEE Biomedical Circuits and systems (BIOCAS)

作者： Stratis Matsoukis Joana Covelo Maria V. Sanchez-Vives Andrea Veciana Donghoon Kim Xiang-Zhong Chen Salvador Pané Hidelberto Macedo-Zamudio Ulrike Wallrabe Ren Xu Guenter Edlinger Josef Scharinger G.tec Medical Engineering GmbH Austria Institute for Computational Perception Johannes Kepler University Linz Austria Institut D'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Barcelona Spain Institució Catalana de Recerca i Estudis Avançats (ICREA) Barcelona Spain Multi-Scale Robotics Lab (MSRL) Institute of Robotics and Intelligent Systems (IRIS) ETH Zurich Zurich Switzerland Laboratory for Microactuators IMTEK Albert-Ludwigs-Universität Freiburg Freiburg Germany

Magnetoelectric (ME) materials hold the potential for wireless and minimally invasive brain stimulation with high spatial precision. However, comprehensive integration of ME materials in neurophysiology experiments remains an open challenge. In this study, we present the development of a ME stimulator prototype for in vitro brain stimulation, specifically tested with BiFeO 3 -CoFe 2 O 4 (BFO-CFO) nanoparticles. Our approach entails the design and implementation of a ME stimulator, which seamlessly integrates with existing electrophysiology setups while supporting a wide range of frequencies. To optimize the stimulator's design and evaluate its performance, we conducted modeling and simulations, bench tests, and in vitro experiments using cortical slices. The proposed ME stimulator offers neuroscientists a reliable and versatile tool to advance their understanding of brain function and potentially enhance the treatment of neurological disorders.

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Efficient Haptic Rendering of Regolith

Efficient Haptic Rendering of Regolith

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IEEE International Conference on robotics and Automation (ICRA)

作者： Aaron Pereira Annika Schmidt Institute of Robotics and Mechatronics German Aerospace Center Oberpfaffenhofen Germany Human-Robot Interaction Lab European Space Agency Noordwijk Netherlands Sensor Based Robotic Systems and Intelligent Assistance Systems TU Munich Germany

Driven by the need for physically accurate and haptically convincing models of lunar and planetary regolith for model-mediated teleoperation in space, we present an approach to modelling regolith in an efficient yet realistic way. Model parameters are derived from physical characteristics of the regolith, to render regoliths with different density profiles, cohesion, internal friction and in different gravitational fields. Users could distinguish between changes in parameters– specifically friction and gravity field–and also gave qualitative feedback relevant to modelling regolith. We discuss the challenges in haptically rendering soils and the next steps.

关键词： Solid modeling Friction Conferences Moon Virtual reality Soil Rendering (computer graphics)

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252 - ON-DEMAND ENCRUSTATION-REPELLENT URETERAL STENT/CATHETER SURFACE: A NOVEL BIOINSPIRED ULTRASONIC APPROACH

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Continence 2024年 12卷 101594-101594页

作者： Dillinger, C Amado, P Obrist, D Burkhard, F Clavica, F Ahmed, D Acoustic Robotics Systems Lab Institute of Robotics and Intelligent Systems Department of Mechanical and Process Engineering ETH Zurich Zurich Switzerland ARTORG Center for Biomedical Engineering Research University of Bern Bern Switzerland Department of Urology Inselspital Bern University Hospital University of Bern Bern Switzerland

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Preliminary study of online real-time control system for lower extremity exoskeletons based on EEG and sEMG fusion

Preliminary study of online real-time control system for low...

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IEEE International Conference on robotics and Biomimetics

作者： Wenju Li Keyong Shao Chi Zhu Yue Ma Wujing Cao Meng Yin Lijun Yang Mingxiang Luo Xinyu Wu School of Electrical Engineering Information Northeast Petroleum University Daqing China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong China Department of Systems Life Engineering Maebashi Institute of Technology Meabashi Japan

ISBN: (纸本)9781665481106

Motion imaging (MI) is widely used in exoskele-ton robot control direction. However, online real-time con-trol of exoskeletons based on biological signals is difficult to achieve. Because the anti-interference of biological signals in real life is poor and affected by individual differences, the control of auxiliary equipment by the realization of human-machine interface is still facing great challenges. In this paper, a human-machine interface (HMI) based on hybrid biological signals is designed and online real-time control of lower extremity exoskeletons is realized. Based on a comprehensive analysis of human walking, the HMI uses the electromyography signals (upper extremities) and EEG signals generated during real exercise as input signals. Different analysis methods are designed for different modal signals. We extracted four features of sEMG signals to distinguish between different movement processes in the human body. For EEG signals, the use of Independent Component Analysis (ICA) increases the robustness of the system. Event-related desynchronization/synchronization (ERS/ERD) and power spectral densities are reused for analysis from the perspective of the interaction of multiple information in the channel, time and frequency domains. The human-machine interface integrates EEG and EMG multimodal biological signals, and the average recognition accuracy of different subjects has reached 93.7%. In order to increase the recognition accuracy of practical applications and reduce the differences between different individuals, a window voting mechanism is designed. Healthy subjects were tested, and the recognition accuracy of the lower limb exoskeleton online real-time assistance system reached 99%, with high accuracy and reliability.

关键词： Legged locomotion Exoskeletons Feature extraction Real-time systems Electroencephalography Biology Robustness

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Soft Robot Control With a Learned Differentiable Model

Soft Robot Control With a Learned Differentiable Model

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IEEE International Conference on Soft robotics (RoboSoft)

作者： James M. Bern Yannick Schnider Pol Banzet Nitish Kumar Stelian Coros Computational Robotics Lab in the Institute for Intelligent Interactive Systems (IIIS) ETH Zurich Switzerland

ISBN: (数字)9781728165707

ISBN: (纸本)9781728165714

Soft robots are inherently safe and comply readily to their environment. They are therefore exciting for applications like search and rescue or medicine, which involve a high degree of uncertainty, and require interacting with humans. However, the best way to model and control soft robots largely remains an open question. One promising approach is to leverage physically-based modeling techniques such as the finite element method. However, such techniques are inherently limited by their physical assumptions. Indeed, real-world soft robots are often made from unpredictable materials, using imprecise techniques. Data-driven approaches provide an exciting alternative, as they can learn real-world fabrication defects and asymmetries. In this paper we present our first investigation into using machine learning to do soft robot control. We learn a differentiable model of a soft robot's quasi-static physics, and then perform gradient-based optimization to find optimal open-loop control inputs. We find that our learned model captures phenomena that would be absent from an idealized physically-based simulation. We also present practical techniques for acquiring high-quality motion capture data, and observations the effect of network complexity on model accuracy.

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On-Command Disassembly of Microrobotic Superstructures for Transport and Delivery of Magnetic Micromachines

arXiv

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arXiv 2023年

作者： Landers, Fabian C. Gantenbein, Valentin Hertle, Lukas Veciana, Andrea Llacer-Wintle, Joaquin Chen, Xiang-Zhong Ye, Hao Franco, Carlos Puigmartí-Luis, Josep Kim, Minsoo Nelson, Bradley J. Pané, Salvador Multi-Scale Robotics Lab Institute of Robotics and Intelligent Systems ETH Zurich Tannenstrasse 3 Zurich8092 Switzerland Institute of Optoelectronics Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception Fudan University Shanghai200438 China Yiwu Research Institute of Fudan University Zhejiang Yiwu322000 China Departament de Ciència dels Materials i Química Física Institut de Química Teòrica i Computacional University of Barcelona Martí i Franquès 1 Barcelona08028 Spain Pg. Lluís Companys 23 Barcelona08010 Spain

Magnetic microrobots have been developed for navigating microscale environments by means of remote magnetic fields. However, limited propulsion speeds at small scales remain an issue in the maneuverability of these devices as magnetic force and torque are proportional to their magnetic volume. Here, we propose a microrobotic superstructure, which, as analogous to a supramolecular system, consists of two or more microrobotic units that are interconnected and organized through a physical (transient) component (a polymeric frame or a thread). Our superstructures consist of microfabricated magnetic helical micromachines interlocked by a magnetic gelatin nanocomposite containing iron oxide nanoparticles (IONPs). While the microhelices enable the motion of the superstructure, the IONPs serve as heating transducers for dissolving the gelatin chassis via magnetic hyperthermia. In a practical demonstration, we showcase the superstructure’s motion with a gradient magnetic field in a large channel, the disassembly of the superstructure and release of the helical micromachines by a high-frequency alternating magnetic field, and the corkscrew locomotion of the released helices through a small channel via a rotating magnetic field. This adaptable microrobotic superstructure reacts to different magnetic inputs, which could be used to perform complex delivery procedures within intricate regions of the human body. © 2023, CC BY-NC-ND.

关键词： Iron oxides

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Trajectory optimization for a class of robots belonging to Constrained Collaborative Mobile Agents (CCMA) family

Trajectory optimization for a class of robots belonging to C...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Nitish Kumar Stelian Coros Computational Robotics Lab Institute for Intelligent Interactive Systems (IIIS) ETH Zurich Switzerland

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

We present a novel class of robots belonging to Constrained Collaborative Mobile Agents (CCMA) family which consists of ground mobile bases with non-holonomic constraints. Moreover, these mobile robots are constrained by closed-loop kinematic chains consisting of revolute joints which can be either passive or actuated. We also describe a novel trajectory optimization method which is general with respect to number of mobile robots, topology of the closed- loop kinematic chains and placement of the actuators at the revolute joints. We also extend the standalone trajectory optimization method to optimize concurrently the design parameters and the control policy. We describe various CCMA system examples, in simulation, differing in design, topology, number of mobile robots and actuation space. The simulation results for standalone trajectory optimization with fixed design parameters is presented for CCMA system examples. We also show how this method can be used for tasks other than end-effector positioning such as internal collision avoidance and external obstacle avoidance. The concurrent design and control policy optimization is demonstrated, in simulations, to increase the CCMA system workspace and manipulation capabilities. Finally, the trajectory optimization method is validated in experiments through two 4-DOF prototypes consisting of 3 tracked mobile bases.

关键词： Kinematics Mobile robots Trajectory optimization Mobile agents Task analysis

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Hierarchical human-motion prediction and logic-geometric programming for minimal interference human-robot tasks

arXiv

引用

arXiv 2021年

作者： Le, An T. Kratzer, Philipp Hagenmayer, Simon Toussaint, Marc Mainprice, Jim Machine Learning and Robotics Lab University of Stuttgart Germany Max Planck Institute for Intelligent Systems IS-MPI Tübingen/Stuttgart Germany Technische Universität Berlin TUB Germany

In this paper, we tackle the problem of human-robot coordination in sequences of manipulation tasks. Our approach integrates hierarchical human motion prediction with Task and Motion Planning (TAMP). We first devise a hierarchical motion prediction approach by combining Inverse Reinforcement Learning and short-term motion prediction using a Recurrent Neural Network. In a second step, we propose a dynamic version of the TAMP algorithm Logic-Geometric Programming (LGP) [1]. Our version of Dynamic LGP, replans periodically to handle the mismatch between the human motion prediction and the actual human behavior. We assess the efficacy of the approach by training the prediction algorithms and testing the framework on the publicly available MoGaze dataset [2]. © 2021, CC BY-NC-ND.

关键词： Computer circuits

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