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6th Social Robots with AI: Prospects, Risks, and Responsible Methods Robophilosophy, RP 2024

作者： Zawieska, Karolina Kollakidou, Avgi Bodenhagen, Leon Krüger, Norbert Martin, Clionah Bendt, Mads Andersen, Casper School of Culture and Society Aarhus University Denmark Faculty of Engineering University of Southern Denmark Denmark The Danish Institute for Advanced Study Denmark Coalescent Mobile Robotics ApS Denmark Capra Robotics ApS Denmark RGC Management A/S Denmark

ISBN: (纸本)9781643685670

robotics and AI technologies often have been perceived as radically innovative technologies that likely will cause problematic disruptions of society. In particular, ethical concerns about the simulation of high-level human capacities in social robots have engendered calls for various forms of 'top-down' regulation, guided by pre-set values and standards. Working from insights of a case study with mobile robots, we suggest in this discussion paper that we might do better in pursuing responsible innovation bottom-up: Moving among robots with minimal social interaction skills, citizens may practically acquire the technological knowledge that can protect them against anthropomorphizing overinterpretations and inappropriate attachments. We unfold this suggestion in three steps: First, reporting on our case study, we describe the limited role of value considerations among the design goals that currently guide developers and early adopters of mobile robots in the retail industry. Second, based on an observation from an ethnographic pilot study and related HRI research on mobile robots, we derive a proposal for responsible innovation bottom-up, as supervised social experiment and cultural learning. Third, we discuss the proposal, pro and contra. © 2025 IOS Press. All rights reserved.

关键词： Mobile robots

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Neural Dynamics for Cooperative Motion Control of Omnidirectional Mobile Manipulators in the Presence of Noises: A Distributed Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1605-1620页

作者： Yufeng Lian Xingtian Xiao Jiliang Zhang Long Jin Junzhi Yu Zhongbo Sun the Department of Control Engineering Changchun University of TechnologyChangchun 130012China IEEE the College of Information Science and Engineering Northeastern UniversityShenyang 110819 the National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China the School of Information Science and Engineering Lanzhou UniversityLanzhou 730000China the State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China

This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning(CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming(QP) and solved online utilizing a noise-tolerant zeroing neural network(NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.

关键词： Cooperative motion control noise-tolerant zeroing neural network(NTZNN) omnidirectional mobile manipulator(OMM) repetitive motion planning

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Construction of laser-induced graphene/silver nanowire composite structures for low-strain,high-sensitivity flexible wearable strain sensors

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Science China(Technological Sciences) 2024年第11期67卷 3524-3534页

作者： YANG PingAn ZHAO JingYuan LI Rui ZHOU ZhiHao GUI YinGang SUN RuiXue WU DeCheng WANG XiaoJie School of Automation Chongqing University of Posts and TelecommunicationsChongqing 400065China College of Engineering and Technology Southwest UniversityChongqing 400715China Bio-inspired Robotics and Intelligent Material Laboratory Institute of Advanced Manufacturing TechnologyHefei Institutes of Physical ScienceChinese Academy of SciencesChangzhou 213164China

Sandwich-structured flexible sensors based on graphene have high sensitivity and *** graphene is combined with a flexible substrate in a sandwich structure,the weak bonding between them compromises the sensor's stability and sensitivity at low *** presents challenges in monitoring subtle physiological activities,such as hand bending and pulse *** this purpose,laser-induced graphene(LIG)is proposed to be used to prepare flexible sensors in order to improve the sensitivity and stability of the sensors at low ***(PDMS)with low modulus and polyimide(PI)with rich carbon content are selected as precursor materials for LIG,and graphene is formed through laser ***,silver nanowires(Ag NWs)solution is added to LIG to give the sensor low strain and high sensitivity *** the PI/PDMS ratio is 1:3,the Ag NWs/LIG flexible strain sensor exhibits excellent sensitivity(GF=778.468)over a small strain range(8.76%-11.25%).Meanwhile,the sensor still shows excellent stability after 2000 cycle *** Ag NWs/LIG flexible strain sensor shows good performance when placed on the back of the hand,around the eyes,*** is demonstrated that Ag NWs/LIG flexible strain sensors have good application potential in human physiological activity monitoring,health management and medical fields,and provide a low-strain,high-sensitivity sensor design strategy for flexible wearable devices.

关键词： flexible strain sensors high sensitivity strain range Ag NWs laser-induced graphene

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Instability-Induced Origami Design by Topology Optimization

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Acta Mechanica Solida Sinica 2023年第4期36卷 506-513页

作者： Weiwei Wang Ke Liu Meiqi Wu Hongyuan Li Pengyu Lv Huiling Duan State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceBIC-ESATCollege of EngineeringPeking UniversityBeijing 100871China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China CAPT HEDPS and IFSACollaborative Innovation Center of MoEPeking UniversityBeijing 100871China

Instability-induced wrinkle patterns of thin sheets are ubiquitous in nature,which often result in origami-like patterns that provide inspiration for the engineering of origami *** by instability-induced origami patterns,we propose a computational origami design method based on the nonlinear analysis of loaded thin sheets and topology *** bar-and-hinge model is employed for the nonlinear structural analysis,added with a displacement perturbation strategy to initiate out-of-plane *** ideas from topology optimization,a continuous crease indicator is introduced as the design variable to indicate the state of a crease,which is penalized by power functions to establish the mapping relationships between the crease indicator and hinge *** the structural strain energy with a crease length constraint,we are able to evolve a thin sheet into an origami structure with an optimized crease *** examples with different initial setups are illustrated,demonstrating the effectiveness and feasibility of the method.

关键词： Origami structure Instability Topology optimization Bar-and-hinge model

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16-Layer 3D Stacking Based on Self-Assembly Technology for HBM Application

16-Layer 3D Stacking Based on Self-Assembly Technology for H...

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2024 International 3D Systems Integration Conference, 3DIC 2024

作者： Zehua, Du Kikuchi, Hiroshi Hishinuma, Hayato Tanaka, Tetsu Fukushima, Takafumi Graduate School of Engineering Tohoku University Sendai Japan Advanced Technology Development Center Yamaha Robotics Holdings Co. Ltd. Tokyo Japan

ISBN: (纸本)9798331516505

We address a trade-off issue between chip assembly time and positioning accuracy in a traditional pick- and-place method using self-assembly technology driven by liquid surface tension. This method allows 16-layer stacking of 50-µm-thin chips fabricated via Plasma Dicing Before Grinding (PDBG). The surface tension of liquid droplets enables sub-50 nm alignment accuracy even with manual chip placement. By identifying key parameters such as pre-alignment position and liquid volume/distribution, we optimize the self-assembly process for High Bandwidth Memory (HBM) applications. Additionally, we discuss the effects of liquid bridges and wetting contrast between the chip surface and sidewall on multi-layer stacking. © 2024 IEEE.

关键词： Wetting

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Nonconvex Noise-Tolerant Neural Model for Repetitive Motion of Omnidirectional Mobile Manipulators

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1766-1768页

作者： Zhongbo Sun Shijun Tang Jiliang Zhang Junzhi Yu the Department of Control Engineering Changchun University of TechnologyChangchun 130012China IEEE College of Information Science and Engineering Northeastern UniversityShenyang 110819China the State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China

Dear Editor,Quadratic programming problems(QPs)receive a lot of attention in various fields of science computing and engineering applications,such as manipulator control[1].Recursive neural network(RNN)is considered t... 详细信息

关键词： directional programming hardware

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OPTIMIZING GENETIC PROCESS MINING WITH HEURISTIC AND HONEY BEE APPROACHES FOR ENHANCED INITIAL POPULATION DESIGN AND NEIGHBORHOOD SEARCH

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International Journal of Innovative Computing, Information and Control 2025年第3期21卷 781-790页

作者： Effendi, Yutika Amelia Kim, Minsoo Robotics and Artificial Intelligence Engineering Faculty of Advanced Technology and Multidiscipline Airlangga University Kampus C UNAIR Jl. Dr. Ir. H. Soekarno Mulyorejo Jawa Timur Surabaya60115 Indonesia Department of Industrial and Data Engineering College of Engineering Pukyong National University 45 Yongso-ro Namgu Busan48513 Korea Republic of

Genetic process mining is a method used to identify, monitor, and improve processes by extracting insights from event logs within modern information systems. While traditional Genetic Algorithms (GAs) can mine models with all structural constructs, except for duplicate tasks, and are resilient to noise, their significant computational time remains a major drawback. This study enhances the Honey Bee Genetic Algorithm (HBGA) by incorporating the Heuristic Miner (HM)’s dependency measure, addressing challenges related to random population generation and excessive parameter tuning while accelerating the initial stages of evolution. By leveraging HM for initial population design and HBGA for neighborhood search, the proposed approach reduces the number of fitness function evaluations and computational time without compromising the accuracy of the final process model. Experimental results demonstrate that the proposed method outperforms traditional genetic process mining in terms of execution time and fitness function evaluations, while achieving superior fitness. Consequently, this process mining algorithm offers a more efficient and effective solution for discovering workflow models. © 2025, ICIC International. All rights reserved.

关键词： Dependency relation Genetic process mining Heuristic miner Honey bee algorithm Process discovery Process enhancement Process mining

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Robust Practical Stabilization for Complex Dynamical Networks With DoS Attacks and Actuator Saturation

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3108-3118页

作者： Shi, Xueya Peng, Zhinan Yu, Junzhi Li, Hongfei Southwest University College of Electronic and Information Engineering Chongqing400715 China Sichuan Artificial Intelligence Research Institute Yibin644000 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China

This article addresses the problem of designing an attack-resilient adaptive event-triggered (AET) controller for complex dynamical networks (CDNs) under DoS attacks and actuator saturation, with a focus on robust practical stability (RPS). First, considering the impact of DoS attacks on closed-loop systems, an AET controller against DoS attacks is designed. Unlike other event-triggered controllers, the complete timeline is divided, and the AET controller is built with two switching modes based on the intervals of dormant and active periods of DoS attacks in which the system is located. Second, to reconcile AET controller with actuator saturation, a switched system modeling approach is established that explicitly incorporates saturation constraints into the coupled network dynamics. Third, a switched Lyapunov-Krasovskii functional (LKF) is proposed, with which sufficient conditions are provided to ensured the RPS, and a joint design strategy is developed for the desired triggered matrix and feedback gain using linear matrix inequalities (LMIs). Moreover, the results are generalized to the case of actuator faults, indicating that the system is able to achieve RPS with actuator faults. Finally, the proposed method is verified through an example. © 2013 IEEE.

关键词： Lyapunov functions

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Learning to Model Diverse Driving Behaviors in Highly Interactive Autonomous Driving Scenarios With Multiagent Reinforcement Learning

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IEEE Systems Journal 2025年第1期19卷 317-326页

作者： Liu, Weiwei Hu, Wenxuan Jing, Wei Lei, Lanxin Gao, Lingping Liu, Yong Zhejiang University The Advanced Perception on Robotics and Intelligent Learning Lab College of Control Science and Engineering Hangzhou310027 China Huzhou Institute of Zhejiang University Zhejiang 310027 China Alibaba DAMO Academy Autonomous Driving Lab Zhejiang 311121 China Huzhou University College of Information Engineering Zhejiang 313000 China

Autonomous vehicles trained through multiagent reinforcement learning (MARL) have shown impressive results in many driving scenarios. However, the performance of these trained policies can be impacted when faced with diverse driving styles and personalities, particularly in highly interactive situations. This is because conventional MARL algorithms usually operate under the assumption of fully cooperative behavior among all agents and focus on maximizing team rewards during training. To address this issue, we introduce the personality modeling network (PeMN), which includes a cooperation value function and personality parameters to model the varied interactions in high-interactive scenarios. The PeMN also enables the training of a background traffic flow with diverse behaviors, thereby improving the performance and generalization of the ego vehicle. Our extensive experimental studies, which incorporate different personality parameters in high-interactive driving scenarios, demonstrate that the personality parameters effectively model diverse driving styles and that policies trained with PeMN demonstrate better generalization than traditional MARL methods. © 2007-2012 IEEE.

关键词： Reinforcement learning

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Impact of nano fillers on the mechanical and rheological behaviour of polydimethylsiloxane based nanocomposite elastomer

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Ceramics International 2025年第14期51卷 18852-18864页

作者： Mandal, Swaroop Kumar Kumar, Rahul Pradhan, Asisha Ranjan Kumar, Deepak Kumar, Satish Department of Automation and Robotics Dr. DY Patil Institute of Technology Pimpri Pune411018 India Advanced Composite and Smart Material Laboratory Department of Mechanical Engineering National Institute of Technology Jamshedpur 831014 India Department of Mechanical Engineering Parala Maharaja Engineering College Odisha 761003 India Rheology Lab Department of Mechanical Engineering National Institute of Technology Jamshedpur 831014 India

In this work, an advanced elastomer which is reinforced with nanocomposite of reduced graphene oxide and calcium carbonate (rGO/CaCO3) is fabricated. Its mechanical and rheological properties are investigated experimentally. The effect of rGO/CaCO3 nanocomposite was experimentally investigated using Dynamical Mechanical Analysis (DMA), Tensile test and Rheological test. The results indicate improved adhesion and physical strengthening effect between rGO/CaCO3 nanocomposite and the PDMS, that leads towards the decrement of extensional loss factor and hence increment in the extensional storage modulus. Also, the ultimate tensile stress and percentage elongation of the elastomers was found to be increased with increasing wt. % of rGO in CaCO3. It has been observed that 5 % rGO/CaCO3 nanocomposite in PDMS exhibits a higher tensile stress of 0.81 ± 0.040 MPa in comparison to pure PDMS (0.48 ± 0.024 MPa). The bare PDMS material has a maximum force of 12.94 ± 0.647 N, but the 5 % rGO/CaCO3/PDMS nanocomposite can tolerate a maximum force of 22.1 ± 1.105 N. Furthermore, the rheological properties of the material were altered, resulting in an increase in the viscosity of PDMS as the percentage (%) of rGO concentration in the rGO/CaCO3 nanocomposite increased. The presence of CaCO3 increases viscosity, however when 4 % (wt. %) rGO is added to CaCO3, the viscosity decreases compared to other filler concentrations in the elastomers. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Polydimethylsiloxane

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