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2024 International Conference on machine Learning, Pattern Recognition and Automation engineering, MLPRAE 2024

作者： Rao, Jinjun Wang, Cong Liu, Mei Lei, Jingtao Giernacki, Wojciech Department of Precision Mechanical Engineering School of Mechatronic Engineering and Automation Shanghai University China Institute of Robotics and Machine Intelligence Faculty of Automatic Control Robotics and Electrical Engineering Poznan University of Technology Poland

ISBN: (纸本)9798400709876

Aiming at the problem that the combination of self-play (SP) and deep reinforcement learning (DRL) only involves two-party games and the policy learning of each party is limited, a multi-party asymmetric self-play algorithm (MASP) is proposed. Firstly, by improving the ELO scoring system, the ELO scoring takes into account each party of the unmanned surface vehicle (USV) clusters, and the imbalance of the number of USV clusters, so that the frequency of exchanging strategies of all USV clusters in the confrontation process is equal. Secondly, it ensures that USV clusters have a balanced combat ability, and at the same time ensures that the combat ability of all parties is strong and weak and the gap is not too wide. In addition, the parameters are dynamically set to reduce the update frequency of the policy of the stronger party. The experimental results show that the MASP can make the USV clusters learn more effective policies, have a shorter game time, and obtain higher rewards and ELO scores in the simple 2v2 adversarial game scenario and the three-party game scenario of a warship escort mission. © 2024 ACM.

关键词： Deep reinforcement learning

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Development and Evaluation of a Cost-effective IMU System for Gait Analysis: Comparison with Vicon and VideoPose3D Algorithms

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Current Directions in Biomedical engineering 2023年第1期9卷 254-257页

作者： Wilhelm, Nikolas Haddadin, Sami Micheler, Carina M. Lang, Jan J. Hinterwimmer, Florian Schaack, Victor Smits, Ricardo Burgkart, Rainer Department of Orthopedics and Sports Orthopedics Klinikum Rechts der Isar School of Medicine and Munich Institute of Robotics and Machine Intelligence Department of Electrical and Computer Engineering 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 Department of Orthopedics and Sports Orthopedics Klinikum Rechts der Isar School of Medicine Munich Germany

This study aimed to develop and evaluate a costeffective Inertial Measurement Unit (IMU) system for gait analysis, comparing its performance with the Vicon system and the VideoPose3D algorithm. The system comprises five calibrated sensors and a mobile app to measure lower body orientation during gait and stair climbing. Eight healthy participants were involved in the experiment, each performing ten repetitions to analyze hip and knee flexion angles. The IMU system demonstrated significantly lower mean square error than deep learning-based approaches and comparable results to the Vicon system, indicating its potential for clinical and research applications. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Gait analysis

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Invited Paper: Ultra-Efficient Edge AI Using FeFET-based Monolithic 3D Integration 42

Invited Paper: Ultra-Efficient Edge AI Using FeFET-based Mon...

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42nd IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2023

作者： Kumar, Shubham Chauhan, Yogesh Singh Amrouch, Hussam Stuttgart Germany Indian Institute of Technology Kanpur Department of Electrical Engineering India Ai Processor Design Germany Munich Institute of Robotics and Machine Intelligence Tum Germany

ISBN: (纸本)9798350315592

Monolithic three-dimensional (M3D) integration signifies a notable technological leap by providing solutions of high density and energy efficiency, particularly for ultra-efficient edge AI solutions. Among emerging technologies, ferroelectric thin-film transistors (FeTFTs) have attracted substantial interest due to their potential in neuromorphic computing and their compatibility with back-end-of-the-line (BEOL) fabrication processes. Nevertheless, the challenge of M3D integrated circuits lies in elevated temperatures resulting from limited heat dissipation across various stacked tiers, subsequently exerting adverse effects on system reliability. In this work, we explore how compute-in-memory (CIM) architectures can be realized using BEOL FeTFT to accelerate deep learning applications. We demonstrate how generated temperature impacts the reliability and ultimately degrade the inference accuracy. To achieve that, we have modified the open-source '3D+NeuroSim' framework to introduce FeTFT and then employed it to estimate the key figures of merit, such as throughput, power density, area, etc. Then, we perform a comprehensive thermal analysis for the simulated M3D architecture to explore how the DNN accuracy will be impacted due to the generated heat. We also demonstrate how FeTFT devices can be accurately modeled using TCAD simulations and how run-time variability (due to temperature effects) and design-time variability (due to process variation) impact the reliability of FeTFT transistors. © 2023 IEEE.

关键词： Thermoanalysis

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Development and Evaluation of a Cost-effective IMU System for Gait Analysis: Comparison with Vicon and VideoPose3D Algorithms

Development and Evaluation of a Cost-effective IMU System fo...

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关键词： Gait analysis

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Analysis and Characterization of Defects in FeFETs

Analysis and Characterization of Defects in FeFETs

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2023 IEEE International Test Conference, ITC 2023

作者： Thapar, Dhruv Thomann, Simon Chaudhuri, Arjun Amrouch, Hussam Chakrabarty, Krishnendu Duke University Department of Electrical and Computer Engineering North Carolina United States Ai Processor Design Germany Munich Institute of Robotics and Machine Intelligence Technical University of Munich Germany Arizona United States

ISBN: (纸本)9798350343250

Emerging devices are susceptible to manufacturing defects due to immature fabrication processes. Ferroelectric field-effect transistors, referred to as FeFETs, are promising emerging devices, but the impact of manufacturing imperfections on these devices has yet to be studied. Thus, we combine a technology CAD (TCAD) model with a fault-injection technique to represent fabrication defects in a FeFET. The TCAD model is calibrated against a fabricated metal-ferroelectric-metal capacitor and uses a multi-domain ferroelectric-layer structure. We address two classes of defects in the ferroelectric layer and map them to stuck-at-fault models referred to as neutral faults (SAP°) and stuck-at-plus and stuck-at-minus (SAP+ and SAP-) faults. We also develop a machine-learning (ML) framework to characterize these fault-injected FeFET devices. The ML framework provides a significant speedup in predicting the health of the FE layer as compared to computationally heavy TCAD simulations. Our study of defects in ferroelectric FET (FeFET), which is done for the first time, and the insights gained thereof can provide valuable feedback for the fabrication and yield learning of FeFET-based circuits. © 2023 IEEE.

关键词： Defects

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On Rapid Parallel Tuning of Controllers of a Swarm of MAVs – Distribution Strategies of the Updated Gains

On Rapid Parallel Tuning of Controllers of a Swarm of MAVs ...

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International Conference on Control, Automation, robotics and Vision (ICARCV)

作者： Dariusz HorIa Wojciech Giernacki Vít Krátký Petr Štibinger Tomáš Báča Martin Saska Faculty of Automation Robotics and Electrical Engineering Institute of Robotics and Machine Intelligence Poznan University of Technology Poznan Poland Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague Prague Czechia

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

In this paper, we present a reliable, scalable, time deterministic, model-free procedure to tune swarms of Micro Aerial Vehicles (MAVs) using basic sensory data. Two approaches to taking advantage of parallel tuning are presented. First, the tuning with averaging of the results on the basis of performance indices reported from the swarm with identical gains to decrease the negative effect of the noise in the measurements. Second, the tuning with parallel testing of varying set of gains across the swarm to reduce the tuning time. The presented methods were evaluated both in simulation and real-world experiments. The achieved results show the ability of the proposed approach to improve the results of the tuning while decreasing the tuning time, ensuring at the same time a reliable tuning mechanism.

关键词： Automation Distribution strategy Noise Gain measurement Robot sensing systems Data models Reliability Noise measurement Tuning Testing

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Optimal Control for Clutched-Elastic Robots: A Contact-Implicit Approach

Optimal Control for Clutched-Elastic Robots: A Contact-Impli...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Dennis Ossadnik Vasilije Rakčević Mehmet C. Yildirim Edmundo Pozo Fortunić Hugo T. M. Kussaba Abdalla Swikir Sami Haddadin Chair of Robotics and Systems Intelligence and the Munich Institute of Robotics and Machine Intelligence (MIRMI) Technical University of Munich Germany Department of Electrical and Electronic Engineering Omar Al-Mukhtar University (OMU) Albaida Libya

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Intrinsically elastic robots surpass their rigid counterparts in a range of different characteristics. By temporarily storing potential energy and subsequently converting it to kinetic energy, elastic robots are capable of highly dynamic motions even with limited motor power. However, the time-dependency of this energy storage and release mechanism remains one of the major challenges in controlling elastic robots. A possible remedy is the introduction of locking elements (i.e. clutches and brakes) in the drive train. This gives rise to a new class of robots, so-called clutched-elastic robots (CER), with which it is possible to precisely control the energy-transfer timing. A prevalent challenge in the realm of CERs is the automatic discovery of clutch sequences. Due to complexity, many methods still rely on pre-defined modes. In this paper, we introduce a novel contact-implicit scheme designed to optimize both control input and clutch sequence simultaneously. A penalty in the objective function ensures the prevention of unnecessary clutch transitions. We empirically demonstrate the effectiveness of our proposed method on a double pendulum equipped with two of our newly proposed clutch-based Bi-Stiffness Actuators (BSA).

关键词： Potential energy Prevention and mitigation Optimal control Switches Motors Linear programming Timing

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Biomechanical Test Setup for the Investigation of Forehead Suture Techniques

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Current Directions in Biomedical engineering 2023年第1期9卷 532-535页

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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Generating Realistic VRU-AV Scenarios via Social Force-Based Gradient Optimization 27

Generating Realistic VRU-AV Scenarios via Social Force-Based...

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27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024

作者： Long, Tingting Zong, Mengru Zhang, Chi Liu, Yuehu Ma, Shuangxun Li, Li National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence Shaanxi Xi'an China School of Electrical Engineering Xi' An Jiaotong University Shaanxi Xi'an China School of Future Transportation Changan University Xi'an710064 China BNRist Tsinghua University Department of Automation Beijing100084 China

ISBN: (纸本)9798331505929

Validating safe and reliable interaction with vulnerable road users (VRUs) is imperative for autonomous vehicles, especially in simulation testing procedures before on-road applications. However, existing VRU agents are either with predefined routes or with collision-oriented behaviors, which limits the fidelity and diversity of scenarios. Bridging the gap between the simulated world and reality requires realistic VRU behaviors. In this paper, we apply social force to capture natural human behavior, considering how individuals are influenced by their surroundings and adhere to real-world rules. To this end, we propose HybridSFM, an improved social force model designed for characterizing human-vehicle interacting behavior. Specifically, the steering and acceleration of the VRUs are parameterized and integrated with social norms to forecast trajectories. Based on this, we further implement a gradient optimization framework for generating VRU-AV safety-critical scenarios. Firstly, VRUs are positioned randomly around the ego-agent. Differentiable simulation updates states and unrolls trajectories while backpropagation optimizes the actions of VRUs. The modified scenario is further optimized in the subsequent time step until a collision happens. The experiments demonstrate that our approach can enhance realistic safety-critical scenarios at intersection scenarios, facilitating the testing of interaction capabilities for autonomous vehicles. © 2024 IEEE.

关键词： Autonomous vehicles

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TReCiM: Lower Power and Temperature-Resilient Multibit 2FeFET-1T Compute-in-Memory Design 24

TReCiM: Lower Power and Temperature-Resilient Multibit 2FeFE...

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43rd International Conference on Computer-Aided Design, ICCAD 2024

作者： Zhou, Yifei Kämpfe, Thomas Ni, Kai Amrouch, Hussam Zhuo, Cheng Yin, Xunzhao Zhejiang University Hangzhou China Fraunhofer IPMS Dresden Germany Department of Electrical Engineering University of Notre Dame Notre Dame United States Technical University of Munich TUM School of Computation Information and Technology Munich Institute of Robotics and Machine Intelligence Munich Germany Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province China

ISBN: (纸本)9798400710773

Compute-in-memory (CiM) emerges as a promising solution to solve hardware challenges in artificial intelligence (AI) and the Internet of Things (IoT), particularly addressing the"memory wall" issue. By utilizing nonvolatile memory (NVM) devices in a crossbar structure, CiM efficiently accelerates multiply-accumulate (MAC) computations, the crucial operations in neural networks and other AI models. Among various NVM devices, Ferroelectric FET (FeFET) is particularly appealing for ultra-low-power CiM arrays due to its CMOS compatibility, voltage-driven write/read mechanisms and high ION/IOFF ratio. Moreover, subthreshold-operated FeFETs, which operate at scaling voltages in the subthreshold region, can further minimize the power consumption of CiM array. However, subthreshold-FeFETs are susceptible to temperature drift, resulting in computation accuracy degradation. Existing solutions exhibit weak temperature resilience at larger array size and only support 1-bit. In this paper, we propose TReCiM, an ultra-low-power temperature-resilient multibit 2FeFET-1T CiM design that reliably performs MAC operations in the subthreshold-FeFET region with temperature ranging from 0°C to 85°C at scale. We benchmark our design using NeuroSim framework in the context of VGG-8 neural network architecture running the CIFAR-10 dataset. Benchmarking results suggest that when considering temperature drift impact, our proposed TReCiM array achieves 91.31% accuracy, with 1.86% accuracy improvement compared to existing 1-bit 2T-1FeFET CiM array. Furthermore, our proposed design achieves 48.03 TOPS/W energy efficiency at system level, comparable to existing designs with smaller technology feature sizes. © 2024 Copyright is held by the owner/author(s).

关键词： MISFET devices

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