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Workshop on Sensor Data Fusion: Trends, Solutions, Applications (SDF)

作者： Markus Walker Philipp S. Bien Uwe D. Hanebeck Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology (KIT) Germany

ISBN: (数字)9798331527440

ISBN: (纸本)9798331527457

The assessment of prediction quality in machine learning models is crucial, particularly within specific regions of the input space, as black-box models do not perform equally well in every region. Common methods, such as mean squared error and calibration measures, are unable to assess local quality. To address this issue, we propose a novel approach based on Voronoi tessellation, which provides a visual and intuitive method for analyzing two-dimensional input spaces. Our method identifies regions in the input space, assesses the calibration of predictions within these regions, and is implemented for regression tasks in multi-input systems. The effectiveness of our approach is exemplified using Bayesian neural networks (BNNs) and shows that our proposed method provides a clearer understanding of the quality of predictions in different input space regions.

关键词： Visualization Neural networks Closed box Machine learning Predictive models Data models Calibration Bayes methods State estimation Testing

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Influence of Reporting Rate on Epidemic Control Based on SIXAR Model 41

Influence of Reporting Rate on Epidemic Control Based on SIX...

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第41届中国控制会议

作者： Lingyu Wu Qiandong Sun Cong Li Xiang Li Adaptive Networks and Control Lab Department of Electronic EngineeringSchool of Information Science and TechnologyFudan University The Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous SystemsTongji University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

How to balance the control efficiency of the epidemic and the economy is extremely *** paper proposes a Susceptible-Infected-Isolated-Asymptomatic-Recovered(SIXAR,X represents isolated people) model,considering the asymptomatic and the *** conduct an in-depth research on the reporting rate in the epidemic,and find the critical reporting rate to prevent the spread of the *** result proves that maintaining the reporting rate near a critical value can both ensure epidemic prevention and control and reduce economic *** will provide a new idea for the government to formulate rational measures.

关键词： Epidemic models SIR model Complex Network COVID-19

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Closed-Form information-Theoretic Roughness Measures for Mixture Densities

Closed-Form Information-Theoretic Roughness Measures for Mix...

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American Control Conference (ACC)

作者： Uwe D. Hanebeck Daniel Frisch Dominik Prossel Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology (KIT) Germany

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

In estimation, control, and machine learning under uncertainties, latent variables are usually described by a probability density function (pdf). The optimal reconstruction of a continuous pdf from given samples or moments is an important and ubiquitous task. Unfortunately, it typically results in an underdetermined optimization problem, as the pdf is not fully constrained by the given samples or moments. For regularization, we use Fisher information (FI) that acts as a roughness measure, i.e., selects the smoothest pdf fulfilling the constraints, in an information-theoretic sense. For the important class of mixture densities, FI can only be computed numerically. In this paper, we derive a closed-form solution for FI for mixtures by transforming the problem to the space $\mathcal{R}$ of root mixtures (RMs). This results in a tandem processing scheme simultaneously working in the original mixture space $\mathcal{M}$ and the corresponding RM space: The density parameters are optimized in root mixture space based on the closed-form FI. The desired constraints are evaluated in the original mixture space $\mathcal{M}$ .

关键词： Closed-form solutions Uncertainty Nonlinear equations Shape Machine learning Probability density function Minimization

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Design of a Mesh Crawling Robot with Beetle-Inspired Variable Stiffness Tarsus

Design of a Mesh Crawling Robot with Beetle-Inspired Variabl...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Chen, Hao Hu, Kai Hu, Longlong Zhou, Ziqi Li, Yao Li, Bing Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen518055 China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China

ISBN: (纸本)9781665481090

Compared with large robots, micro-robots have the advantages of small size, low power consumption, and high concealment. For complex terrain, the crawling performance of micro-robots will be significantly reduced. In this study, the mesh surface was used as the crawling base of the robot, and a variable stiffness tarsus was designed with the beetle as a reference. This tarsus composed of multiple bending parts achieves a large range of stiffness changes, 0.070.495 N/mm. We have achieved stiffness control of the tarsus in a single actuation by trajectory planning of the claw ends. The proposed robot can achieve a big stiffness of the tarsus to resist the deformation of the tarsus due to external forces, which means that the robot can increase the adhesion ability when crawling at the stance phase. Therefore, even when the load was increased from 10g to 40g, the average crawling speed of the robot was not significantly reduced. This new tarsus can improve the crawling performance of the micro-robot on the mesh. © 2024 IEEE.

关键词： Microrobots

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A glance over the past decade: road scene parsing towards safe and comfortable autonomous driving

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Autonomous intelligent systems 2025年第1期5卷 1-15页

作者： Fan, Rui Li, Jiahang Li, Jiaqi Wang, Jiale Long, Ziwei Jia, Ning Liu, Yanan Wang, Wenshuo Bocus, Mohammud J. Vityazev, Sergey Chen, Xieyuanli Xiao, Junhao Andreev, Stepan Lu, Huimin Dvorkovich, Alexander College of Electronics & Information Engineering Shanghai Institute of Intelligent Science and Technology Shanghai Research Institute for Intelligent Autonomous Systems the State Key Laboratory of Intelligent Autonomous Systems and the Frontiers Science Center for Intelligent Autonomous Systems Tongji University 4800 Caoan Rd Shanghai201804 China College of Electronics & Information Engineering Tongji University 4800 Caoan Rd Shanghai201804 China School of Microelectronics Shanghai University 20 Chengzhong Rd Shanghai201800 China School of Mechanical Engineering Beijing Institute of Technology 5 Zhongguancun South Street Beijing100081 China Department of Electrical and Electronic Engineering University of Bristol Woodland Road England BristolBS8 1UB United Kingdom Faculty of Radio Engineering and Telecommunications Ryazan State Radio Engineering University Ulitsa Gagarina 59/1 Ryazan Oblast Ryazan390005 Russia College of Intelligence Science and Technology National University of Defense Technology 109 Deya Road Changsha410073 China Microwave Photonics Department Telecommunications Center Moscow Institute of Physics and Technology Institutsky Lane 9 Moscow Region Dolgoprudny141701 Russia Multimedia Technology and Telecom Department Telecommunications Center Moscow Institute of Physics and Technology Institutsky Lane 9 Moscow Region Dolgoprudny141701 Russia

Road scene parsing is a crucial capability for self-driving vehicles and intelligent road inspection systems. Recent research has increasingly focused on enhancing driving safety and comfort by improving the detection of both drivable areas and road defects. This article reviews state-of-the-art networks developed over the past decade for both general-purpose semantic segmentation and specialized road scene parsing tasks. It also includes extensive experimental comparisons of these networks across five public datasets. Additionally, we explore the key challenges and emerging trends in the field, aiming to guide researchers toward developing next-generation models for more effective and reliable road scene parsing. © The Author(s) 2025.

关键词： Semantics

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Inverse Gaussian Process Interpolation for High-Quality Assumed Gaussian Filtering

Inverse Gaussian Process Interpolation for High-Quality Assu...

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International Conference on Multisensor Fusion and Integration for intelligent systems (MFI)

作者： Jiachen Zhou Daniel Frisch Uwe D. Hanebeck Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology (KIT) Germany

ISBN: (数字)9798350368031

ISBN: (纸本)9798350368048

In this paper, we propose a novel Gaussian Assumed Density Filter (GADF) for high-quality state estimation of nonlinear dynamic systems. Our approach focuses on the measurement update, utilizing a non-Gaussian local approximation of the true joint measurement/prior state density. This is achieved through the sequential use of two Inverse Gaussian Processes (IGPs): the first IGP interpolates the means, and based on these results, the second IGP is trained to interpolate the covariances. Together, they fully characterize the conditional Gaussian densities of the hidden state on concrete measurements. Consequently, our method does not require the second Gaussian assumption for the joint density anymore, thereby enhancing filter performance. Moreover, our approach eliminates the need for an explicit likelihood function within the filter step, making it a higher-quality plug-in replacement for the commonly used Linear Regression Kalman Filter (LRKF).

关键词： Interpolation Maximum likelihood detection Density measurement Noise Linear regression Gaussian processes Nonlinear filters Nonlinear dynamical systems Noise measurement State estimation

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New Software Bionic Haptic Actuator Design Based on Barometric Array

New Software Bionic Haptic Actuator Design Based on Baromet...

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International Conference on Applied Nonlinear Dynamics, Vibration, and Control, ICANDVC 2023

作者： Yu, Zige Li, Sai Lin, Mengying Hu, Hang Li, Yingying Lei, Qian Huang, Zixin School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Wuhan430200 China Institute of Robotics and Automatic Information Systems College of Artificial Intelligence Nankai University Tianjin300350 China

ISBN: (纸本)9789819705535

To address the limitations of single-point tactile perception in soft biomimetic actuators, such as fixed positioning, limited coverage area, low resolution at long distances from the geometric center, and challenges in maintaining high sensitivity and stability over a broad range, a novel soft biomimetic tactile actuator based on a pneumatic array is designed and manufactured. Using liquid silicone rubber and BMP280 pressure sensor, the actuator was crafted by an injection molding process. Silicone gel was injected into the pressure sensor array, and vacuum extraction created a sealed space within the sensor cavity. The pressure excitation applied on the surface of the actuator could be converted into electrical signals, enabling tactile pressure detection. An STM32 microprocessor is utilized for building haptic information acquisition and processing system, with sensitivity assessed using the Kalman filter algorithm. Experimental results show that the soft biomimetic tactile actuator has high sensitivity and minimal repetition error, which can effectively detects changes in tactile force output, mitigates noise interference, and enhances the precision and stability of physiological pressure data feedback in physiotherapy applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Bionics

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Gaussian Mixture Particle Filter Step based on Method of Moments

Gaussian Mixture Particle Filter Step based on Method of Mom...

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International Conference on information Fusion

作者： Daniel Frisch Uwe D. Hanebeck Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology (KIT) Germany

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

We propose a novel update step of a Gaussian mixture particle filter for nonlinear state estimation. The update procedure works as follows: First, unweighted samples are drawn in an optimal deterministic sense from a prior Gaussian mixture. These samples are then assigned weights from the likelihood function, and we compute higher-order moments from this samplebased posterior. These moment approximations converge with $L^{-1}$ instead of $L^{-1 / 2}$ as our samples are optimal deterministic. Finally, the continuous posterior approximation is determined as the Gaussian mixture that has minimal Fisher information under the constraint of having the aforementioned moments. To achieve this, we employ a closed-form solution of the Fisher information that involves Gaussian root mixture densities.

关键词： Codes Closed-form solutions Monte Carlo methods Oceans information filters Particle filters Bayes methods State estimation Optimization Method of moments

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Walking Control for a Self-Balancing Exoskeleton on Flat Ground

Walking Control for a Self-Balancing Exoskeleton on Flat Gro...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Li, Jinke Tian, Dingkui Li, Feng Sun, Jianquan Yin, Meng Wu, Xinyu University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen518055 China Siat Cuhk Joint Laboratory of Robotics and Intelligent Systems China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9798350327182

Designed to provide rehabilitation or the assistance of walking for individuals who are with lower limb muscle injuries or spinal during their activities, self-balancing lower limb exoskeletons have been developed. This paper introduces an innovative controller for a fully actuated exoskeleton that ensures stable walking for wearers without the need for external devices. The exoskeleton robot is represented as a center of mass model, and based on this representation, the trajectory generation and controller are discussed, aiming to improve locomotion stability. To assess the stability and dynamic performance, a stable walking experiment with the exoskeleton was conducted, involving a male subject. © 2023 IEEE.

关键词： Exoskeleton (robotics)

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A calculation method of spatial similarity based on quantitative detail direction relation expression model 4

A calculation method of spatial similarity based on quantita...

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4th International Conference on Geoscience and Remote Sensing Mapping, GRSM 2022

作者： Zong, Qin Chen, Hui Deng, Xinjie School of Intelligent Construction Chong Qing Jian Zhu College Chongqing400072 China Sino-german Robotics School Shenzhen Institute of Information Technology Shenzhen518172 China

ISBN: (数字)9781510662179

ISBN: (纸本)9781510662162

In view of the fact that the source and target parts are contained in the reference target, the existing model expression is inconsistent with the actual cognition. A quantitative detail direction relationship expression model is proposed to establish a two-layer grid direction relationship matrix for spatial objects. The expression ability of the two-layer grid direction relation matrix is tested and analysed. Through the comparison and analysis with the calculation results of the direction relation binary in literature [7] and the grid direction relation matrix in literature [8], the recognition ability of the two-layer grid direction relation matrix to displacement and rotation is verified. Finally, it is proved that the method in this paper is effective in the calculation of spatial direction similarity, extended cartographic comprehensive evaluation, data matching and fusion Applicability of work tasks such as change detection and update. © 2023 SPIE.

关键词： Optical engineering

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