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1

Xu, Ming-Yang, Yi-Fan Hua, Yun-Fan Li, et al. "Development of an Ankle Assistive Robot with Instantly Gait-Adaptive Method." Journal of Robotics and Mechatronics 35, no. 3 (2023): 669–83. http://dx.doi.org/10.20965/jrm.2023.p0669.

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As the population ages, the number of elderly people suffering from systemic diseases such as stroke increases. To address this problem, various wearable walking assistive robots have been developed to promote physical exercise for stroke prevention. Wearable assistive robots have shown the ability to improve human mobility. However, most of these robots are heavy, bulky, and impractical. In this study, we developed a compact ankle assistive robot for elderly users to promote walking exercise. By informing the user of correct motion and timing, the robot can guide the user to achieve a healthy
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Cantucci, Filippo, Rino Falcone, and Marco Marini. "Redefining User Expectations: The Impact of Adjustable Social Autonomy in Human–Robot Interaction." Electronics 13, no. 1 (2023): 127. http://dx.doi.org/10.3390/electronics13010127.

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To promote the acceptance of robots in society, it is crucial to design systems exhibiting adaptive behavior. This is particularly needed in various social domains (e.g., cultural heritage, healthcare, education). Despite significant advancements in adaptability within Human-Robot Interaction and Social Robotics, research in these fields has overlooked the essential task of analyzing the robot’s cognitive processes and their implications for intelligent interaction (e.g., adaptive behavior, personalization). This study investigates human users’ satisfaction when interacting with a robot whose
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Maroto-Gómez, Marcos, María Malfaz, Álvaro Castro-González, Sara Carrasco-Martínez, and Miguel Ángel Salichs. "Adaptive Circadian Rhythms for Autonomous and Biologically Inspired Robot Behavior." Biomimetics 8, no. 5 (2023): 413. http://dx.doi.org/10.3390/biomimetics8050413.

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Biological rhythms are periodic internal variations of living organisms that act as adaptive responses to environmental changes. The human pacemaker is the suprachiasmatic nucleus, a brain region involved in biological functions like homeostasis or emotion. Biological rhythms are ultradian (<24 h), circadian (∼24 h), or infradian (>24 h) depending on their period. Circadian rhythms are the most studied since they regulate daily sleep, emotion, and activity. Ambient and internal stimuli, such as light or activity, influence the timing and the period of biological rhythms, making our bodie
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de Jong, Chiara, Jochen Peter, Rinaldo Kühne, and Alex Barco. "Children’s acceptance of social robots." Interaction Studies 20, no. 3 (2019): 393–425. http://dx.doi.org/10.1075/is.18071.jon.

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Abstract Social robots progressively enter children’s lives, but little is known about children’s acceptance of social robots and its antecedents. To fill this research gap, this narrative review surveyed 34 articles on child-robot interaction published between 2000 and 2017. We focused on robot, user, and interaction characteristics as potential antecedents of children’s intentional and behavioral social robot acceptance. In general, children readily accept robots. However, we found that social, adaptive robot behavior, children’s sex and age, as well as frequency of the interaction seem to a
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Liu, Ruisen, Manisha Natarajan, and Matthew C. Gombolay. "Coordinating Human-Robot Teams with Dynamic and Stochastic Task Proficiencies." ACM Transactions on Human-Robot Interaction 11, no. 1 (2022): 1–42. http://dx.doi.org/10.1145/3477391.

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As robots become ubiquitous in the workforce, it is essential that human-robot collaboration be both intuitive and adaptive. A robot’s ability to coordinate team activities improves based on its ability to infer and reason about the dynamic (i.e., the “learning curve”) and stochastic task performance of its human counterparts. We introduce a novel resource coordination algorithm that enables robots to schedule team activities by (1) actively characterizing the task performance of their human teammates and (2) ensuring the schedule is robust to temporal constraints given this characterization.
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Rincon Arango, Jaime Andres, Cedric Marco-Detchart, and Vicente Javier Julian Inglada. "Personalized Cognitive Support via Social Robots." Sensors 25, no. 3 (2025): 888. https://doi.org/10.3390/s25030888.

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This paper explores the use of personalized cognitive support through social robots to assist the elderly in maintaining cognitive health and emotional well-being. As aging populations grow, the demand for innovative solutions to address issues like loneliness, cognitive decline, and physical limitations increases. The studied social robots utilize machine learning and advanced sensor technology to deliver real-time adaptive interactions, including cognitive exercises, daily task assistance, and emotional support. Through responsive and personalized features, the robot enhances user autonomy a
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Sirithunge, Chapa, A. G. Buddhika P. Jayasekara, and D. P. Chandima. "Experience-based Learning and Adaptive Behavior for Improved Situation-Awareness of a Social Robot." IOP Conference Series: Materials Science and Engineering 1321, no. 1 (2024): 012016. https://doi.org/10.1088/1757-899x/1321/1/012016.

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Abstract When robots work in close contact with their human counterparts, they have to perceive their surroundings adequately. Hence have adequate situation-awareness. In such cases, an encounter will include the robot itself, the surrounding and the humans. Existing frameworks to interpret such situations, considered a limited number of observable human cues and inputs from the surrounding so far. Therefore only a few aspects of a situation were effectively perceived by these mechanisms. In our work, we trained a Deep Q-Network (DQN) which takes a number of attributes in a situation as input
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Almeida, Luis, Paulo Menezes, and Jorge Dias. "Telepresence Social Robotics towards Co-Presence: A Review." Applied Sciences 12, no. 11 (2022): 5557. http://dx.doi.org/10.3390/app12115557.

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Telepresence robots are becoming popular in social interactions involving health care, elderly assistance, guidance, or office meetings. There are two types of human psychological experiences to consider in robot-mediated interactions: (1) telepresence, in which a user develops a sense of being present near the remote interlocutor, and (2) co-presence, in which a user perceives the other person as being present locally with him or her. This work presents a literature review on developments supporting robotic social interactions, contributing to improving the sense of presence and co-presence v
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Matúšová, Miriam, Marcela Bučányová, and Erika Hrušková. "The future of industry with collaborative robots." MATEC Web of Conferences 299 (2019): 02008. http://dx.doi.org/10.1051/matecconf/201929902008.

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Rapidly changing user requirements, improving of quality of life or increased safety at work are allarguments for introducing flexible automation that replaces strenuous or dangerous work. Industrial robots with adaptive directing are now deployed to most industries due to their large range of uses. Theirmain addition for manufacturing is to eliminate downtime of complete operating and manipulating production process, to make easier all particular operation in accordance with ergonomics. The paper describescomparing between conventional industrial robot and collaborative robot.
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Phan, Thieu Long, and Akansel Cosgun. "Placing Objects on Table Is Preferred over Direct Handovers When Users Are Occupied." Sensors 25, no. 7 (2025): 2140. https://doi.org/10.3390/s25072140.

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Service robots commonly deliver objects through direct handovers, assuming users are fully attentive. However, in real-world scenarios, users are often occupied with other tasks. This paper investigates how user attentiveness affects preferences between direct handovers and placing objects on a table. A user study was conducted (n = 25) to evaluate these strategies in scenarios where participants were either occupied (simulated via a typing task) or unoccupied. Results show that placing objects on the table significantly enhances user experience when users were occupied, with higher ratings fo
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Lu, Fei, Min Huang, Xiaolei Li, Guohui Tian, Hao Wu, and Wenjia Si. "Learning and Development of Home Service Robots’ Service Cognition Based on a Learning Mechanism." Applied Sciences 10, no. 2 (2020): 464. http://dx.doi.org/10.3390/app10020464.

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In order to improve the intelligence of home service robots and resolve their inability to develop service cognition skills in an autonomous, human-like manner, we propose a method for home service robots to learn and develop skills that allow them to perform their services appropriately in a dynamic and uncertain home environment. In a context model built with the support of intelligent sensors and Internet of Things (IoT) technology in a smart home, common-sense information about environmental comfort is recorded into the logical judgment of the robot as a reward provided by the environment.
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Yuan, Fengpei, Amir Sadovnik, Ran Zhang, Devin Casenhiser, Eun Jin Paek, and Xiaopeng Zhao. "A simulated experiment to explore robotic dialogue strategies for people with dementia." Journal of Rehabilitation and Assistive Technologies Engineering 9 (January 2022): 205566832211057. http://dx.doi.org/10.1177/20556683221105768.

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Introduction Persons with dementia (PwDs) often show symptoms of repetitive questioning, which brings great burdens on caregivers. Conversational robots hold promise of helping cope with PwDs’ repetitive behavior. This paper develops an adaptive conversation strategy to answer PwDs’ repetitive questions, follow up with new questions to distract PwDs from repetitive behavior, and stimulate their conversation and cognition. Methods We propose a general reinforcement learning model to interact with PwDs with repetitive questioning. Q-learning is exploited to learn adaptive conversation strategy (
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Yuan, Fengpei, Amir Sadovnik, Ran Zhang, Devin Casenhiser, Eun Jin Paek, and Xiaopeng Zhao. "A simulated experiment to explore robotic dialogue strategies for people with dementia." Journal of Rehabilitation and Assistive Technologies Engineering 9 (January 2022): 205566832211057. http://dx.doi.org/10.1177/20556683221105768.

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Introduction Persons with dementia (PwDs) often show symptoms of repetitive questioning, which brings great burdens on caregivers. Conversational robots hold promise of helping cope with PwDs’ repetitive behavior. This paper develops an adaptive conversation strategy to answer PwDs’ repetitive questions, follow up with new questions to distract PwDs from repetitive behavior, and stimulate their conversation and cognition. Methods We propose a general reinforcement learning model to interact with PwDs with repetitive questioning. Q-learning is exploited to learn adaptive conversation strategy (
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Martins, Gonçalo S., Hend Al Tair, Luís Santos та Jorge Dias. "αPOMDP: POMDP-based user-adaptive decision-making for social robots". Pattern Recognition Letters 118 (лютий 2019): 94–103. http://dx.doi.org/10.1016/j.patrec.2018.03.011.

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15

Asada, Harichiko, Clifford C. Federspiel, and Sheng Liu. "Human Centered Control in Robotics and Consumer Product Design." Journal of Dynamic Systems, Measurement, and Control 115, no. 2B (1993): 271–80. http://dx.doi.org/10.1115/1.2899067.

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Human factors in the control and programming of robots and electric appliances are addressed in this paper. Systems and control techniques for the enhancement of human-machine communication as well as learning and adaptation to human needs are described with exemplary case studies. First, fundamental issues and methodologies, as well as historical perspective of relevant fields, are summarized, and two case studies are then discussed. One is user-adaptable control of air conditioners, a new type of adaptive control that allows an air conditioner to learn the thermal preference of the user. The
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Abut, Tayfun, and Servet Soyguder. "Real-time control of bilateral teleoperation system with adaptive computed torque method." Industrial Robot: An International Journal 44, no. 3 (2017): 299–311. http://dx.doi.org/10.1108/ir-09-2016-0245.

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Purpose This paper aims to use the adaptive computed torque control (ACTC) method to eliminate the kinematic and dynamic uncertainties of master and slave robots and for the control of the system in the presence of forces originating from human and environment interaction. Design/methodology/approach In case of uncertainties in the robot parameters that are utilized in teleoperation studies and when the environment where interactions take place is not known and when there is a time delay, very serious problems take place in system performance. An adaptation rule was created to update uncertain
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Cantucci, Filippo, and Rino Falcone. "Collaborative Autonomy: Human–Robot Interaction to the Test of Intelligent Help." Electronics 11, no. 19 (2022): 3065. http://dx.doi.org/10.3390/electronics11193065.

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A big challenge in human–robot interaction (HRI) is the design of autonomous robots that collaborate effectively with humans, exposing behaviors similar to those exhibited by humans when they interact with each other. Indeed, robots are part of daily life in multiple environments (i.e., cultural heritage sites, hospitals, offices, touristic scenarios and so on). In these contexts, robots have to coexist and interact with a wide spectrum of users not necessarily able or willing to adapt their interaction level to the kind requested by a machine: the users need to deal with artificial systems wh
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18

Iqbal, M., and G. Abbas. "RISK ANALYSIS IN HUMAN-ROBOT INTERACTIVE ENVIRONMENTS." Pakistan Journal of Scientific Research 4, no. 1 (2024): 105–18. https://doi.org/10.57041/pjosr.v4i1.1216.

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As robotic systems gradually integrate into environments shared with humans, effective risk analysis in human-robot interactive settings has become necessary to guarantee optimized collaboration, and safety, and boost user acceptance. This review discovers methodologies for risk assessment in human-robot interactive (HRI), examining factors like physical proximity, dynamic unpredictability, and cognitive inconsistency amongst human users. This paper explores how sensor technologies, real-time data, and predictive algorithms can be influenced to alleviate risks related to robot faults, unpredic
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Petrov, A. A., and S. A. Kuz'min. "A Flexible and User-Friendly Vision System for Adaptive Industrial Robots." IFAC Proceedings Volumes 19, no. 2 (1986): 255–60. http://dx.doi.org/10.1016/s1474-6670(17)64131-4.

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20

Lund, Henrik Hautop, and Luigi Pagliarini. "Distributed Robotics Education." Journal of Robotics and Mechatronics 23, no. 5 (2011): 859–70. http://dx.doi.org/10.20965/jrm.2011.p0859.

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Distributed robotics takes many forms, for instance, multirobots, modular robots, and self-reconfigurable robots. The understanding and development of such advanced robotic systems demand extensive knowledge in engineering and computer science. In this paper, we describe the concept of a distributed educational system as a valuable tool for introducing students to interactive parallel and distributed processing programming as the foundation for distributed robotics and human-robot interaction development. This is done by providing an educational tool that enables problem representation to be c
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Pham, Thanh-Nam, and Duc-Tho Mai. "A Mobile Robot Design for Home Security Systems." Engineering, Technology & Applied Science Research 14, no. 4 (2024): 14882–87. http://dx.doi.org/10.48084/etasr.7336.

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Home Security Systems (HSSs) have received much attention and have been widely adopted for practical deployment. However, detection and warning accuracy still need to be improved, along with the range of the realm, making it challenging to satisfy the user demands. This study proposes a security monitoring system based on mobile robots and the Internet of Things (IoT), allowing users to monitor and control devices remotely. The mobile robot integrated sensor systems and surveillance cameras are utilized for unauthorized early intrusion detection and to give users instant warnings. The data col
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Santhanaraj, Karthik, Dinakaran Devaraj, Ramya MM, Joshuva Dhanraj, and Kuppan Ramanathan. "Biologically Inspired Self-Organizing Computational Model to Mimic Infant Learning." Machine Learning and Knowledge Extraction 5, no. 2 (2023): 491–511. http://dx.doi.org/10.3390/make5020030.

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Recent technological advancements have fostered human–robot coexistence in work and residential environments. The assistive robot must exhibit humane behavior and consistent care to become an integral part of the human habitat. Furthermore, the robot requires an adaptive unsupervised learning model to explore unfamiliar conditions and collaborate seamlessly. This paper introduces variants of the growing hierarchical self-organizing map (GHSOM)-based computational models for assistive robots, which constructs knowledge from unsupervised exploration-based learning. Traditional self-organizing ma
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Jarosz, Mateusz, and Bartlomiej Sniezynski. "Personalization of Robot Behavior Using Approach Based on Model Predictive Control." Applied Sciences 14, no. 24 (2024): 11805. https://doi.org/10.3390/app142411805.

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This paper proposes a novel approach to personalizing robot behavior using Model Predictive Control (MPC). Social humanoid robots, equipped with advanced sensors and human-like capabilities, are increasingly integrated into human environments, necessitating adaptable and intuitive communication interfaces. Our approach enables the design of adaptive interfaces that support fluid, personalized human–robot interactions. In the proposed framework, a user model is applied to predict responses to potential robot actions. Initially, this model represents an average user; however, it is updated as th
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Mashud, Gazi, SK Hasan, and Nafizul Alam. "Advances in Control Techniques for Rehabilitation Exoskeleton Robots: A Systematic Review." Actuators 14, no. 3 (2025): 108. https://doi.org/10.3390/act14030108.

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This systematic review explores recent advancements in control methods for rehabilitation exoskeleton robots, which assist individuals with motor impairments through guided movement. As robotics technology progresses, precise, adaptable, and safe control techniques have become accessible for effective human–robot interaction in rehabilitation settings. Key control methods, including computed torque and adaptive control, excel in managing complex movements and adapting to diverse patient needs. Robust and sliding mode controls address stability under unpredictable conditions. Traditional approa
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Pinto-Bernal, Maria, Matthijs Biondina, and Tony Belpaeme. "Designing Social Robots with LLMs for Engaging Human Interaction." Applied Sciences 15, no. 11 (2025): 6377. https://doi.org/10.3390/app15116377.

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Large Language Models (LLMs), particularly those enhanced through Reinforcement Learning from Human Feedback, such as ChatGPT, have opened up new possibilities for natural and open-ended spoken interaction in social robotics. However, these models are not inherently designed for embodied, multimodal contexts. This paper presents a user-centred approach to integrating an LLM into a humanoid robot, designed to engage in fluid, context-aware conversation with socially isolated older adults. We describe our system architecture, which combines real-time speech processing, layered memory summarisati
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Nocentini, Olivia, Laura Fiorini, Giorgia Acerbi, Alessandra Sorrentino, Gianmaria Mancioppi, and Filippo Cavallo. "A Survey of Behavioral Models for Social Robots." Robotics 8, no. 3 (2019): 54. http://dx.doi.org/10.3390/robotics8030054.

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The cooperation between humans and robots is becoming increasingly important in our society. Consequently, there is a growing interest in the development of models that can enhance and enrich the interaction between humans and robots. A key challenge in the Human-Robot Interaction (HRI) field is to provide robots with cognitive and affective capabilities, by developing architectures that let them establish empathetic relationships with users. Over the last several years, multiple models were proposed to face this open-challenge. This work provides a survey of the most relevant attempts/works.
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Wu, Tong, Dongyue Liu, and Xiyun Li. "Designing Hybrid Mobility for Agricultural Robots: Performance Analysis of Wheeled and Tracked Systems in Variable Terrain." Machines 13, no. 7 (2025): 572. https://doi.org/10.3390/machines13070572.

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This study investigates the operational performance of fruit-picking robots under varying terrain slopes and soil moisture conditions, with a focus on comparing wheeled and tracked locomotion systems. A modular robot platform was designed and tested in both controlled environments and actual mountainous orchards in Shandong, China. The experiments assessed key performance metrics—average speed, slip rate, and path deviation—under combinations of four slope levels (0°, 8°, 18°, 28°) and three soil moisture levels (dry 10%, moderate 20%, wet 35%). Results reveal that wheeled robots perform optim
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Martins, Gonçalo S., Luís Santos, and Jorge Dias. "User-Adaptive Interaction in Social Robots: A Survey Focusing on Non-physical Interaction." International Journal of Social Robotics 11, no. 1 (2018): 185–205. http://dx.doi.org/10.1007/s12369-018-0485-4.

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Mary Catherine, V. G., Binu Paul, Antony Sharon, Aldrin Antony, and Daleesha M. Viswanathan. "Fabrication of PDMS based flexible capacitive tactile sensor array with inkjet printed silver electrodes for robotic object grasp control." Engineering Research Express 6, no. 4 (2024): 045356. https://doi.org/10.1088/2631-8695/ad9986.

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Abstract Human interactive robots deployed for advanced services such as nursing and elderly assistance systems, operate in close proximity to humans in a home environment, unlike the conventional industrial robots. For the adaptive and safe interaction with humans, it is important to endow the sense of touch to such robots. Tactile sensors are embedded on the robotic body to perceive touch. The existing rigid tactile sensors have limited flexibility and conformability to robot surfaces. This paper presents the development of tactile sensors for robots to detect human touch, biomimicking the f
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Bassetti, Chiara, Enrico Blanzieri, Stefano Borgo, and Sofia Marangon. "Towards socially-competent and culturally-adaptive artificial agents." Interaction Studies 23, no. 3 (2022): 469–512. http://dx.doi.org/10.1075/is.22021.bas.

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Abstract The development of artificial agents for social interaction pushes to enrich robots with social skills and knowledge about (local) social norms. One possibility is to distinguish the expressive and the functional orders during a human-robot interaction. The overarching aim of this work is to set a framework to make the artificial agent socially-competent beyond dyadic interaction – interaction in varying multi-party social situations – and beyond individual-based user personalization, thereby enlarging the current conception of “culturally-adaptive”. The core idea is to provide the ar
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Stankevich, Lev, and Anzhelika Zhuravskaya. "Mobile robots control with neuromorphic classifires of environment states." Robotics and Technical Cybernetics 12, no. 3 (2024): 212–21. http://dx.doi.org/10.31776/rtcj.12306.

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The article proposes to implement mobile robots control systems using neuromorphic classifiers, in which biosimi-lar neurons are built on an original neuro-fuzzy model, trained to display the function of the Izhikevich neuron. Us-ing this approach, neuromorphic classifiers of spatial and spatiotemporal patterns were developed. Such a classi-fiers were used in non-contact supervisory control system for mobile robot based on static and dynamic states of the environment. The experiments performed demonstrated the effectiveness of using the neuromorphic classifi-ers, both in a neural interface whe
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Perovic, Gojko, Francesco Iori, Angela Mazzeo, Marco Controzzi, and Egidio Falotico. "Adaptive Robot-Human Handovers With Preference Learning." Robotics and Automation Letters 8, no. 10 (2023): 6331–38. https://doi.org/10.1109/LRA.2023.3306280.

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This letter proposes an adaptive method for robot-to-human handovers under different scenarios. The method combines Dynamic Movement Primitives (DMP) with Preference Learning (PL) to generate online trajectories that are reactive to human motion, modulating the speed of the robot. The PL allows for tuning the coupling parameters of the DMP, tailoring the interaction to each participant personally, and allowing for qualitative analysis of user preferences. Simulation of an interaction-constrained learning task with different optimization techniques is performed to determine an appropriate learn
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Li, Huanzhou, Hongxia Xu, and Minghui Zhan. "Design and implementation of a multifunctional desktop robot for computer peripherals." Journal of Physics: Conference Series 2858, no. 1 (2024): 012015. http://dx.doi.org/10.1088/1742-6596/2858/1/012015.

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Abstract As an important component of the intelligent machinery field, desktop robots not only enrich people’s entertainment lives but are also gradually expanding into applications in education, healthcare, and other fields. However, existing products often struggle to meet the increasingly diverse needs due to short battery life and limited computing resources. In response to this challenge, this study designs a multifunctional desktop robot that can be used as a computer peripheral, which significantly improves power supply and computing capabilities. The design uses the STM32F4 series micr
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Karia, Rushang, Jayesh Nagpal, Daksh Dobhal, et al. "Using Explainable AI and Hierarchical Planning for Outreach with Robots." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 28 (2025): 29019–27. https://doi.org/10.1609/aaai.v39i28.35172.

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Understanding how robots plan and execute tasks is crucial in today's world, where they are becoming more prevalent in our daily lives. However, teaching non-experts, such as K-12 students, the complexities of robot planning can be challenging. This work presents an open-source platform, JEDAI.Ed, that simplifies the process using a visual interface that abstracts the details of various planning processes that robots use for performing complex mobile manipulation tasks. Using principles developed in the field of explainable AI, this intuitive platform enables students to use a high-level intui
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Tozadore, Daniel Carnieto, and Roseli Aparecida Francelin Romero. "Graphical User Interface for educational content programming with social robots activities and how teachers may perceive it." Revista Brasileira de Informática na Educação 28 (February 16, 2020): 191–207. http://dx.doi.org/10.5753/rbie.2020.28.0.191.

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Interactive devices have been successfully applied in education in the last decades. The most used devices for such tasks are personal computers and tablets, due to its financial trade-off and popularization. Social robots are less used, mainly because of its cost and the complexity of being programmed. In this paper, a solution to work around the complexity of programming social robots is presented as a Graphical User Interface (GUI). The GUI system controls an interactive robot which plays with the students and adapts its behavior autonomously. During the activity execution, the adaptive alg
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Trakas, Panagiotis S., Spyridon I. Anogiatis, and Charalampos P. Bechlioulis. "Trajectory Tracking with Obstacle Avoidance for Nonholonomic Mobile Robots with Diamond-Shaped Velocity Constraints and Output Performance Specifications." Sensors 24, no. 14 (2024): 4636. http://dx.doi.org/10.3390/s24144636.

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In this paper, we address the trajectory-/target-tracking and obstacle-avoidance problem for nonholonomic mobile robots subjected to diamond-shaped velocity constraints and predefined output performance specifications. The proposed scheme leverages the adaptive performance control to dynamically adjust the user-defined output performance specifications, ensuring compliance with input and safety constraints. A key feature of this approach is the integration of multiple constraints into a single adaptive performance function, governed by a simple adaptive law. Additionally, we introduce a robust
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Zhao, Zhirui, Xinyu Hou, Dexing Shan, Hongjun Liu, Hongshuai Liu, and Lina Hao. "Application of Fuzzy Adaptive Impedance Control Based on Backstepping Method for PAM Elbow Exoskeleton in Rehabilitation." Polymers 16, no. 24 (2024): 3533. https://doi.org/10.3390/polym16243533.

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In this study, a fuzzy adaptive impedance control method integrating the backstepping control for the PAM elbow exoskeleton was developed to facilitate robot-assisted rehabilitation tasks. The proposed method uses fuzzy logic to adjust impedance parameters, thereby optimizing user adaptability and reducing interactive torque, which are major limitations of traditional impedance control methods. Furthermore, a repetitive learning algorithm and an adaptive control strategy were incorporated to improve the performance of position accuracy, addressing the time-varying uncertainties and nonlinear d
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Ruiz-Ruiz, Francisco J., Cristina Urdiales, and Jesús M. Gómez-de-Gabriel. "Estimation of the Interaction Forces in a Compliant pHRI Gripper." Machines 10, no. 12 (2022): 1128. http://dx.doi.org/10.3390/machines10121128.

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Physical human–robot interaction (pHRI) is an essential skill for robots expected to work with humans, such as assistive or rescue robots. However, due to hard safety and compliance constraints, pHRI is still underdeveloped in practice. Tactile sensing is vital for pHRI, as constant occlusions while grasping make it hard to rely on vision or range sensors alone. More specifically, measuring interaction forces in the gripper is crucial to avoid injuries, predict user intention and perform successful collaborative movements. This work exploits the inherent compliance of a gripper with four under
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Qu, ShuHao. "A Review of Bioinspired Tactile Sensing Systems for Intelligent Robotic Interaction." Applied and Computational Engineering 169, no. 1 (2025): 155–61. https://doi.org/10.54254/2755-2721/2025.ch24536.

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Bioinspired tactile sensing systems, which take cues from the human somatosensory system, are vital for improving how intelligent robots perceive and interact. These technologies enable safe and efficient humanrobot interaction by mimicking human touch flexibility. They are crucial for applications like collaborative automation, assistive technologies, and prosthetics that need physical human-robot interaction (pHRI). This review explores recent developments in flexible sensor materials, microstructural innovation, and transduction methods. The focus is on integrating multimodal strategies tha
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Zhang, Pengfei, Xueshan Gao, Mingda Miao, and Peng Zhao. "Design and Control of a Lower Limb Rehabilitation Robot Based on Human Motion Intention Recognition with Multi-Source Sensor Information." Machines 10, no. 12 (2022): 1125. http://dx.doi.org/10.3390/machines10121125.

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The research on rehabilitation robots is gradually moving toward combining human intention recognition with control strategies to stimulate user involvement. In order to enhance the interactive performance between the robot and the human body, we propose a machine-learning-based human motion intention recognition algorithm using sensor information such as force, displacement and wheel speed. The proposed system uses the bi-directional long short-term memory (BILSTM) algorithm to recognize actions such as falling, walking, and turning, of which the accuracy rate has reached 99.61%. In addition,
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Chien, Jong-Chih, Zih-Yang Dang, and Jiann-Der Lee. "Navigating a Service Robot for Indoor Complex Environments." Applied Sciences 9, no. 3 (2019): 491. http://dx.doi.org/10.3390/app9030491.

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This paper investigates the use of an autonomous service robot in an indoor complex environment, such as a hospital ward or a retirement home. This type of service robot not only needs to plan and find paths around obstacles, but must also interact with caregivers or patients. This study presents a type of service robot that combines the image from a 3D depth camera with infrared sensors, and the inputs from multiple sonar sensors in an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based approach in path planning. In personal contacts, facial features are used to perform person recognition in
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Nadiri, Farzad, and Ahmad B. Rad. "Swarm Intelligence for Collaborative Play in Humanoid Soccer Teams." Sensors 25, no. 11 (2025): 3496. https://doi.org/10.3390/s25113496.

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Humanoid soccer robots operate in dynamic, unpredictable, and often partially observable settings. Effective teamwork, sound decision-making, and real-time collaboration are critical to competitive performance. In this paper, a biologically inspired swarm-intelligence framework for humanoid soccer is proposed, comprising (1) a low-overhead communication User Datagram Protocol (UDP) optimized for minimal bandwidth and graceful degradation under packet loss; (2) an Ant Colony Optimization (ACO)-based decentralized role allocation mechanism that dynamically assigns attackers, midfielders, and def
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S, Mrs Vasanthi,. "VOICE-CONTROLLED ROBOT USING RASPBERRY PI AND BLUETOOTH." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31122.

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In this digital technology era for all the risky and dangerous tasks we prefer Robots rather than people. In the early stage of this Robotics the Robes are manually controlled but due advancement in wireless technology now Robes can be controlled via voice This project employs voice commands to control through an Android app linked to a microcontroller via Bluetooth .Users can control the robot either by tapping buttons on the app or by speaking commands. Movement is powered by two DC servo motors connected to the receiver microcontroller. The voice commands are converted in to digital signals
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Maeda, Yoichiro, and Daisuke Katagami. "Special Issue on Human Symbiotic System." Journal of Advanced Computational Intelligence and Intelligent Informatics 14, no. 7 (2010): 757. http://dx.doi.org/10.20965/jaciii.2010.p0757.

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With opportunities for human beings to coexist with artificial agents and autonomous robots are increasing, high-level interactive communication between them is increasingly needed. These human symbiotic systems are used for research on basic intelligent interaction design principles and methods and bidirectional communication based on effective collaboration and symbiosis between human beings and robots, agents, and computers, also known as artifacts. The research society on gHuman Symbiotic System (HSS)h was implemented by the Japan Society for Fuzzy Theory and Intelligent Informatics (SOF
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Sinha, Anurag, Ashish Bagwari, Pooja Joshi, Ramish, Sudhani Verma, and Jyotshana Kanti. "A∗WRBAS: Space Mobile Robotics Control Conceptual Model Using IoRT Reinforcement Learning and Tracking with Noise Estimation Using EKF." Mobile Information Systems 2022 (September 29, 2022): 1–17. http://dx.doi.org/10.1155/2022/9224025.

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With more than one billion connected devices, the notion of the Internet of Things (IoT) is now gaining momentum. The mobile robot must be able to find itself in space, which is a necessary ability for autonomous navigation. Every high-level navigation operation starts with the fundamental assumption that the user is aware of both their position and the locations of other points of interest throughout the world. A robot without a sense of position can only function in a localized, reactive manner and cannot plan actions that take place outside of the immediate area of its sensory capabilities.
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Anupama A, Ramya S Yamikar, and Renuka K M. "AI-driven gesture control for industrial robots: A vision-based approach for enhancing human-robot collaboration." World Journal of Advanced Research and Reviews 20, no. 2 (2023): 1498–506. https://doi.org/10.30574/wjarr.2023.20.2.2254.

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The integration of artificial intelligence (AI) with vision-based gesture control systems has significantly transformed human-robot interaction in industrial environments. This paper explores recent advancements in AI-driven gesture recognition for industrial robots, focusing on its role in improving human-robot collaboration, efficiency, and safety. AI-powered gesture control enables intuitive and contactless operation, reducing the need for physical controllers and enhancing ergonomics in industrial workflows. The study examines key components of AI-driven gesture recognition, including deep
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Tabandeh, Saleh, William W. Melek, and Christopher M. Clark. "An adaptive niching genetic algorithm approach for generating multiple solutions of serial manipulator inverse kinematics with applications to modular robots." Robotica 28, no. 4 (2009): 493–507. http://dx.doi.org/10.1017/s0263574709005803.

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SUMMARYInverse kinematics (IK) is a nonlinear problem that may have multiple solutions. A modified genetic algorithm (GA) for solving the IK of a serial robotic manipulator is presented. The algorithm is capable of finding multiple solutions of the IK through niching methods. Despite the fact that the number and position of solutions in the search space depends on the position and orientation of the end-effector as well as the kinematic configuration (KC) of the robot, the number of GA parameters that must be set by a user are limited to a minimum through the use of an adaptive niching method.
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Chanel, Caroline P. C., Raphaëlle N. Roy, Frédéric Dehais, and Nicolas Drougard. "Towards Mixed-Initiative Human–Robot Interaction: Assessment of Discriminative Physiological and Behavioral Features for Performance Prediction." Sensors 20, no. 1 (2020): 296. http://dx.doi.org/10.3390/s20010296.

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The design of human–robot interactions is a key challenge to optimize operational performance. A promising approach is to consider mixed-initiative interactions in which the tasks and authority of each human and artificial agents are dynamically defined according to their current abilities. An important issue for the implementation of mixed-initiative systems is to monitor human performance to dynamically drive task allocation between human and artificial agents (i.e., robots). We, therefore, designed an experimental scenario involving missions whereby participants had to cooperate with a robo
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Jeevani Singireddy, Botlagunta Preethish Nandan, Phanish Lakkarasu, Venkata Narasareddy Annapareddy, and Jai Kiran Reddy Burugulla. "Emotional Intelligence in Artificial Agents: Leveraging Deep Multimodal Big Data for Contextual Social Interaction and Adaptive Behavioral Modelling." Metallurgical and Materials Engineering 31, no. 4 (2025): 599–615. https://doi.org/10.63278/1489.

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As artificial agents develop beyond mere tools and begin to perform roles traditionally associated with humans, expectations of their performance are equally evolving. Not only must agents be able to accomplish their tasks; but they must also be able to do so in a manner that observers would consider socially or contextually appropriate. For social interaction where the agent and human are co-performers, adherence to social cues that signal emergent aspects of a relationship such as intimacy or status is paramount to the experience of the interacting humans. For autonomous agents who function
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Mineo, Carmelo, Donatella Cerniglia, Vito Ricotta, and Bernhard Reitinger. "Autonomous 3D geometry reconstruction through robot-manipulated optical sensors." International Journal of Advanced Manufacturing Technology 116, no. 5-6 (2021): 1895–911. http://dx.doi.org/10.1007/s00170-021-07432-5.

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AbstractMany industrial sectors face increasing production demands and the need to reduce costs, without compromising the quality. The use of robotics and automation has grown significantly in recent years, but versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs for specific manufacturing tasks still relies on programming trajectory waypoints by hand. The
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