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arXiv 2025年

作者： Hielscher, Till Bulling, Andreas Arras, Kai O. Socially Intelligent Robotics Lab Institute for Artificial Intelligence University of Stuttgart Germany Collaborative Artificial Intelligence Group Institute for Visualization and Interactive Systems University of Stuttgart Germany

Our goal is to enable social robots to interact autonomously with humans in a realistic, engaging, and expressive manner. The 12 Principles of Animation [1] are a well-established framework animators use to create movements that make characters appear convincing, dynamic, and emotionally expressive. This paper proposes a novel approach that leverages Dynamic Movement Primitives (DMPs) to implement key animation principles, providing a learnable, explainable, modulable, online adaptable and composable model for automatic expressive motion generation. DMPs, originally developed for general imitation learning in robotics and grounded in a spring-damper system design, offer mathematical properties that make them particularly suitable for this task. Specifically, they enable modulation of the intensities of individual principles and facilitate the decomposition of complex, expressive motion sequences into learnable and parametrizable primitives. We present the mathematical formulation of the parameterized animation principles and demonstrate the effectiveness of our framework through experiments and application on three robotic platforms with different kinematic configurations, in simulation, on actual robots and in a user study. Our results show that the approach allows for creating diverse and nuanced expressions using a single base model. © 2025, CC BY-NC-ND.

关键词： Animation

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Towards Fast Face Image Quality Assessment via Latent Diffusion Model 18th

Towards Fast Face Image Quality Assessment via Latent Diffu...

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18th Chinese Conference on Biometric Recognition, CCBR 2024

作者： Yan, Zheyu Zhao, Weisong Zhu, Xiangyu Gao, Li Zhang, Xiao-Yu Lei, Zhen State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China China Mobile Financial Technology Co. Ltd. Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science and Innovation Chinese Academy of Sciences Hong Kong Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9789819610679

Face recognition technology has gradually come into wide application in real life. However, in real-life unconstrained scenarios, low-quality images could be matched to unpredictable individuals, thereby affecting the stability of recognition and even causing security problems. Conducting quality assessment on face images before facial recognition can help alleviate these problems by rejecting low-quality samples. In this paper, we propose a Fast Diffusion-model-based Face Image Quality Assessment method (FDif-FIQA). It uses a diffusion model to perturb face images and measures image quality based on the similarity of features before and after the perturbation. The denoising process is transferred from the pixel space to the latent space, thereby reducing the computational cost. We evaluated the performance of this method with multiple mainstream face recognition models on various public datasets. Compared to state-of-the-art methods, our approach demonstrates highly competitive performance and significant improvements in computational efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Face recognition

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Introspective Perception for Long-Term Aerial Telemanipulation With Virtual Reality

Field Robotics

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Field robotics 2025年 3卷 323-367页

作者： Jongseok Lee Ribin Balachandran Konstantin Kondak Andre Coelho Marco De Stefano Matthias Humt Jianxiang Feng Tamim Asfour Rudolph Triebel Institute of Robotics and Mechatronics German Aerospace Center (DLR) Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology (KIT) Robotics and Mechatronics Laboratory University of Twente (UT) Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology (KIT) Chair of Computer Vision and Artificial Intelligence Technical University of Munich (TUM)

This paper presents a novel telepresence system for advancing aerial manipulation in dynamic and unstructured environments. The proposed system not only features a haptic device, but also a virtual reality (VR) interface that provides real-time 3D displays of the robot's workspace as well as a haptic guidance to its remotely located operator. To realize this, multiple sensors, namely, a LiDAR, cameras, and IMUs are utilized. For processing of the acquired sensory data, pose estimation pipelines are devised for industrial objects of both known and unknown geometries. We further propose an active learning pipeline in order to increase the sample efficiency of a pipeline component that relies on a Deep Neural Network (DNN) based object detector. All these algorithms jointly address various challenges encountered during the execution of perception tasks in industrial scenarios. In the experiments, exhaustive ablation studies are provided to validate the proposed pipelines. Methodologically, these results commonly suggest how an awareness of the algorithms' own failures and uncertainty (“introspection”) can be used to tackle the encountered problems. Moreover, outdoor experiments are conducted to evaluate the effectiveness of the overall system in enhancing aerial manipulation capabilities. In particular, with flight campaigns over days and nights, from spring to winter, and with different users and locations, we demonstrate over 70 robust executions of pick-and-place, force application and peg-in-hole tasks with the DLR cable-Suspended Aerial Manipulator (SAM). As a result, we show the viability of the proposed system in future industrial applications. 1

关键词： Robots Service robots Sensors Pipelines Active learning Pose estimation Haptic interfaces Telepresence Visualization Virtual reality

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Machine Learning for Multimodal Stress Detection – A Case-Study 1

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International Workshop on Advanced in Information Security Management and Applications, AISMA 2024

作者： Kazi, Awaiz Jagtap, Jayant Jayaswal, Ruchi Kolhar, Shrikrishna Choudhury, Tanupriya Kotecha, Ketan Symbiosis Institute of Technology Maharashtra Pune Lavale412115 India Artificial Intelligence Robotics and Cybernetics Marik Institute of Computing NIMS University Rajasthan Jaipur India Uttarakhand Dehradun248007 India Symbiosis Institute of Technology Pune412115 India

ISBN: (数字)9783031721717

ISBN: (纸本)9783031721700

In contemporary educational and professional settings, the escalating issue of stress significantly impacts the health and productivity of individuals. This comprehensive survey article analyzes and contrasts the stress levels reported by students and employees, employing a machine learning approach. By harnessing the capabilities of ML techniques, this study delves into the multifaceted factors influencing stress within these distinct cohorts. Through a meticulous examination of recent research and authentic data, as well as a quest for potential commonalities, the aim is to elucidate specific stressors encountered by students and employees. The work focuses on the difficulties these individuals confront psychologically and reveals the capability of machine learning to solve stress-related problems within society. The results of this research can be used to create targeted interventions and support systems that help students and employees deal with stress, thus improving their quality of life and working conditions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adversarial machine learning

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Inter-Intra Hypergraph Computation for Survival Prediction on Whole Slide Images

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IEEE Transactions on Pattern Analysis and Machine intelligence 2025年第07期PP卷 PP页

作者： Han, Xiangmin Zhou, Huijian Tian, Zhiqiang Du, Shaoyi Gao, Yue Tsinghua University School of Software BNRist THUIBCS BLBCI Beijing100084 China Xi'an Jiaotong University Institute of Artificial Intelligence and Robotics College of Artificial Intelligence Xi'an710049 China

Survival prediction on histopathology whole slide images (WSIs) involves the analysis of multi-level complex correlations, such as inter-correlations among patients and intra-correlations within gigapixel histopathology images. However, the current graph-based methods for WSI analysis mainly focus on the exploration of pairwise correlations, resulting in the loss of high-order correlations. Hypergraph-based methods can handle such high-order correlations, while existing hypergraph-based methods fail to integrate multi-level high-order correlations into a unified framework, which limits the representation capability of WSIs. In this work, we propose an inter-intra hypergraph computation (I2HGC) framework to address this issue. The I2HGC framework implements multi-level hypergraph computation for survival prediction on WSIs, namely intra-hypergraph computation and inter-hypergraph computation. Specifically, the intra-hypergraph computation considers each patch sampled from the histopathology WSI as a vertex of the intra-hypergraph and models the high-order correlations among all patches of an individual WSI in both topology and semantic feature spaces using a hypergraph structure. Then, the intra-hypergraph module generates the intra-embedding and intra-risk for each patient. Subsequently, the inter-hypergraph computation employs these intra-embeddings as features for each patient to form the population-level high-order correlations using data- and knowledge-driven hypergraph modeling strategies. Finally, the intra-risks and the inter-risks are fused for the final survival prediction of each patient. Extensive experimental results on four widely used TCGA carcinoma datasets are presented. We demonstrate that the hypergraph structure captures significantly richer correlations than the graph structure, encompassing all pairwise correlations as well as higher-order interactions through hyperedges. For WSIs with a vast number of pixels and complex correlations, hypergraph

关键词： Medical imaging

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Anti-Swing Trajectory Planning for Quadrotor Transportation Systems with Double-Pendulum Swing Effects

Anti-Swing Trajectory Planning for Quadrotor Transportation ...

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International Conference on Applied Nonlinear Dynamics, Vibration and Control, ICANDVC 2021

作者： Liang, Xiao Cai, Kexin Han, Jianda Institute of Robotics and Automatic Information System College of Artificial Intelligence Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300350 China

ISBN: (纸本)9789811659119

The quadrotor transportation system has attracted numerous attention on different occasions due to its broad adaptability. Nevertheless, the "double" underactuated property of the system brings various challenges in practical control, which is caused by the underactuation of the quadrotor and that the suspended payload cannot be controller directly. In addition, most existing methods are designed based on the hypothesis of neglecting the hook’s motion. In fact, the quadrotors translation will also cause the hook’s relative motion with respect to the payload. In this paper, a trajectory generation method for the precise positioning of the quadrotor and the suppression of the double-pendulum swing motion is proposed. By injecting the artificially constructed swing elimination term into the basic positioning reference trajectory, a novel anti-swing trajectory is designed. Lyapunov based stability analysis is provided to prove the performance of the trajectory. Simulation results are concluded to validate the effectiveness of the planning scheme. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Trajectories

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StableMoFusion: Towards Robust and Efficient Diffusion-based Motion Generation Framework 24

StableMoFusion: Towards Robust and Efficient Diffusion-based...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Huang, Yiheng Yang, Hui Luo, Chuanchen Wang, Yuxi Xu, Shibiao Zhang, Zhaoxiang Zhang, Man Peng, Junran Beijing University of Posts and Telecommunications Beijing China Centre for Artificial Intelligence and Robotics HKISI-CAS Hong Kong Shandong University Jinan China Institute of Automation Chinese Academy of Science Beijing China

ISBN: (纸本)9798400706868

Thanks to the powerful generative capacity of diffusion models, recent years have witnessed rapid progress in human motion generation. Existing diffusion-based methods employ disparate network architectures and training strategies. The effect of the design of each component is still unclear. In addition, the iterative denoising process consumes considerable computational overhead, which is prohibitive for real-time scenarios such as virtual characters and humanoid robots. For this reason, we first conduct a comprehensive investigation into network architectures, training strategies, and inference process. Based on the profound analysis, we tailor each component for efficient high-quality human motion generation. Despite the promising performance, the tailored model still suffers from foot skating which is an ubiquitous issue in diffusion-based solutions. To eliminate footskate, we identify foot-ground contact and correct foot motions along the denoising process. By organically combining these well-designed components together, we present StableMoFusion, a robust and efficient framework for human motion generation. Extensive experimental results show that our StableMoFusion performs favorably against current state-of-the-art methods. © 2024 ACM.

关键词： Network architecture

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A Control Method for a Hung-Up Snake Robot Based on Proximal Policy Optimization and the Time-Reversed Method 42

A Control Method for a Hung-Up Snake Robot Based on Proximal...

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42nd Chinese Control Conference, CCC 2023

作者： Sheng, Fengwei Guo, Xian Tang, Chaoquan Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin300350 China China University of Mining and Technology Xuzhou221116 China

ISBN: (纸本)9789887581543

Due to the presence of multi-joint synergistic movement, the control of the tail-swing locomotion of a snake robot is a very challenging problem. In this paper, a control method based on proximal policy optimization and the time-reversed method is proposed to solve this problem. Specifically, this method first simplifies the snake robot model to the two-link model;then, the trajectory planning is carried out by using the time-reversed method to obtain the reference trajectory;then, the trajectory tracking method based on proximal policy optimization is used to track the reference trajectory and control the tail of the snake robot to reach the target state;then two traditional nonlinear controllers are designed as a contrast. Finally, some experiments results are collected and analyzed, which shows the superior performance of the proposed method. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Reinforcement learning

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Incorporating Bounded Rationality into Electric Vehicle Highway Charging Decisions: A Bayesian Game Analysis

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IEEE Internet of Things Journal 2025年第11期12卷 15249-15260页

作者： Yan, Huanyu Tang, Xiaoying The Chinese University of Hon g Kong School of Science and Engineering Guangdong Shenzhen518172 China The Chinese University of Hon g Kong Shenzhen Institute of Artificial Intelligence and Robotics for Society Guangdong Shenzhen518172 China The Chinese University of Hon g Kong Shenzhen Key Laboratory of Crowd Intelligence Empowered Low-Carbon Energy Network School of Science and Engineering Guangdong Shenzhen518172 China

Electric vehicles (EVs) represent a critical intelligent terminal within the Internet of Things (IoT). Despite the year-on-year growth in EV penetration, the highway driving experience still requires improvement. Accurate prediction of EV highway charging behavior is crucial to addressing this issue. This paper introduces a novel bounded rationality framework to analyze highway charging decisions. Specifically, we utilize prospect theory to capture the tendency of drivers to reserve more electricity than theoretically necessary. We then propose a Bayesian game in which EV drivers, unaware of others' decisions, aim to minimize costs, including range anxiety, charging fees, and queuing time. To gain insights into the game, we prove the existence and uniqueness of the Bayesian Nash Equilibrium in two practical scenarios. Our numerical experiments, based on real-life data, demonstrate that drivers' risk aversion tendency significantly influence EV charging decisions, charging demand, queuing lengths at charging stations, and the departure rate on the highway network. Furthermore, our strategy reduces cumulative EV cost and CSs' charging costs compared to other benchmarks. © 2014 IEEE.

关键词： Markov processes

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Fully 3D Printed Soft Electrostatic Loudspeaker

Fully 3D Printed Soft Electrostatic Loudspeaker

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Jisen Li Fei Xiao Anjing Cheng Zhen Luo Jian Zhu Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of Hong Kong Shenzhen China Shenzhen Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of Hong Kong Shenzhen China

ISBN: (数字)9798350391916

ISBN: (纸本)9798350391923

Loudspeakers are essential components in human-machine interaction, enabling auditory communication between devices and users. However, most conventional loudspeakers are constructed from rigid materials, resulting in poor compliance and limiting their application in wearable technologies. In this paper, we introduce a novel soft loudspeaker fabricated using a customized 3D printer. This loudspeaker is made entirely of silicone rubber, which provides excellent compliance and biocompatibility, making it suitable for integration into wearable devices. The fabrication process involves the use of advanced multi-material 3D printing techniques to create a structure that can operate without the need for prestretch, enhancing its flexibility and ease of use. Experimental results demonstrate that the soft loudspeaker can produce satisfactory audio output when tested with real music input. The acoustic performance, including sound quality and volume, shows a close resemblance to traditional loudspeakers, while offering the added benefits of flexibility and comfort for the user.

关键词： Loudspeakers Fabrication Technological innovation Mechatronics Voltage Three-dimensional printing Rubber Printers Wearable devices Spectrogram

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