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Between the Social and the Technical: Negotiation of human-centered robotics Design in a Middle School Classroom

INTERNATIONAL JOURNAL OF SOCIAL robotics 2018年第3期10卷 309-324页

作者： Gomoll, Andrea Sabanovic, Selma Tolar, Erin Hmelo-Silver, Cindy E. Francisco, Matthew Lawlor, Orion Indiana Univ Sch Informat & Comp 901 E 10th St Bloomington IN 47408 USA Indiana Univ Sch Educ 201 N Rose Ave Bloomington IN 47405 USA Univ Alaska Fairbanks Coll Engn & Mines POB 756660 Fairbanks AK 99775 USA

This paper presents a middle school human-centered robotics (HCR) learning experience and the ways in which it supported students' orientation to technical and social aspects of Science, Technology, Engineering, and Mathematics (STEM). The interdisciplinary project associated with this analysis aims to engage diverse students in authentic STEM practices by creating robotic technologies that can assist people in their school, and connect with remote peers. The goal of this project is to increase student interest in and knowledge of STEM topics, and to help students recognize STEM as relevant to their daily lives and broader societal issues. The human-centered focus of the curriculum encouraged thinking from multiple perspectives (e.g. design, social science, programming) and allowed for diverse STEM exploration. We present samples from student work and classroom interactions. These samples show challenges and successes in engaging students with STEM as a combination of social and technical questions and skills. We trace the trajectory of one group's work to highlight moments in which students navigated an engineering design cycle, analyzed and designed social environments, and crossed disciplinary domains through HCR design-using a phenomena, mechanisms, components framework (PMC) to explore systems thinking. Phenomena refers to attention to the function of the robotic technology in the classroom environment. Components included a focus on single parts of the robot, while mechanism addressed how parts of the robot worked together. This qualitative case study demonstrates the capacity social robotics and inquiry-based learning experiences hold for broadening notions of STEM as a social and multidisciplinary learning domain.

关键词： human-centered robotics STEM education Problem-based learning Sociotechnical systems Engineering design cycle Qualitative case study

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Dragons, Ladybugs, and Softballs: Girls' STEM Engagement with human-centered robotics (vol 25, pg 915, 2016)

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JOURNAL OF SCIENCE EDUCATION AND TECHNOLOGY 2016年第6期25卷 915-915页

作者： Gomoll, Andrea Hmelo-Silver, Cindy E. Sabanovic, Selma Francisco, Matthew Indiana Univ 1900 E 10th St Bloomington IN 47401 USA

Early experiences in science, technology, engineering, and math (STEM) are important for getting youth interested in STEM fields, particularly for girls. Here, we explore how an after-school robotics club can provide informal STEM experiences that inspire students to engage with STEM in the future. human-centered robotics, with its emphasis on the social aspects of science and technology, may be especially important for bringing girls into the STEM pipeline. Using a problem-based approach, we designed two robotics challenges. We focus here on the more extended second challenge, in which participants were asked to imagine and build a telepresence robot that would allow others to explore their space from a distance. This research follows four girls as they engage with human-centered telepresence robotics design. We constructed case studies of these target participants to explore their different forms of engagement and phases of interest development—considering facets of behavioral, social, cognitive, and conceptual-to-consequential engagement as well as stages of interest ranging from triggered interest to well-developed individual interest. The results demonstrated that opportunities to personalize their robots and feedback from peers and facilitators were important motivators. We found both explicit and vicarious engagement and varied interest phases in our group of four focus participants. This first iteration of our project demonstrated that human-centered robotics is a promising approach to getting girls interested and engaged in STEM practices. As we design future iterations of our robotics club environment, we must consider how to harness multiple forms of leadership and engagement without marginalizing students with different working preferences.

关键词： Engagement human-centered robotics Interest development Problem-based learning Telepresence robotics

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human-Robot Collaborative Cable-Suspended Manipulation With Contact Distinction

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IEEE robotics AND AUTOMATION LETTERS 2025年第1期10卷 740-747页

作者： Cortigiani, Giovanni Malvezzi, Monica Prattichizzo, Domenico Pozzi, Maria Univ Siena Dept Informat Engn & Math I-53100 Siena Italy Ist Italiano Tecnol Humanoids & Human Ctr Mechatron Res Line I-16163 Genoa Italy

The collaborative transportation of objects between humans and robots is a fundamental task in physical human-robot interaction. Most of the literature considers the rigid co-grasping of non-deformable items in which both the human and the robot directly hold the transported object with their hands. In this letter, we implement a control strategy for the collaborative manipulation of a cable-suspended platform. The latter is an articulated and partially deformable object that can be used as a base where to place the transported object. In this way, the human and the robot are not rigidly coupled, ensuring a greater flexibility in the partners' motions and a safer interaction. However, the uncertain dynamics of the platform introduces a greater possibility of unintended collisions with external objects, which must be distinguished from contacts arising when a load is placed on or removed from the platform. This letter proposes a contact detection and distinction strategy to address this challenge. The proposed cable-suspended manipulation framework is based only on force sensing at the robot end-effector, and was tested with ten users.

关键词： Robots Collision avoidance Robot sensing systems Collaboration Force Cables End effectors Admittance control Transportation Sensors human-centered robotics human-robot collaboration physical human-robot interaction

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Autonomous Synthesis of Self-Aligning Knee Joint Exoskeleton Mechanisms

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IEEE TRANSACTIONS ON robotics 2025年 41卷 2358-2373页

作者： Yu, Jeonghan Kang, Seok Won Kim, Yoon Young Seoul Natl Univ Dept Mech Engn Seoul 08826 South Korea Columbia Univ Dept Mech Engn New York NY 10027 USA Johns Hopkins Univ Dept Civil & Syst Engn Baltimore MD 21218 USA Sookmyung Womens Univ Dept Mech Syst Seoul 04310 South Korea

Self-aligning mechanisms are essential components in facilitating adaptability in wearable robots, but their synthesis from scratch is very challenging. To overcome this hurdle, we propose a so-far-unprecedented autonomous method to synthesize self-aligning knee joint mechanisms, requiring neither a baseline design nor human intervention during synthesis. Our method transforms the synthesis problem into an optimization problem amenable to an efficient gradient-based algorithm using a discretized ground mechanism model. The main challenge in the conversion lies in how to define the objective and constraint functions in order to ensure the fundamental self-aligning capability and also to impose a desired force transmittance profile. Several design cases were considered to show the effectiveness of the newly proposed functions for the optimization-based synthesis formulation, notably in addressing degree-of-freedom requirements. Although this study focuses primarily on knee joint mechanisms assisting gait motion and aligning with the flexion axis, the developed method can be applied to other self-aligning robot mechanisms.

关键词： Knee Topology Exoskeletons Optimization Springs Robots Shape Electronic mail Bars Actuators human-centered robotics mechanism design prosthetics and exoskeletons topology optimization

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Garment Diffusion Models for Robot-Assisted Dressing

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IEEE robotics AND AUTOMATION LETTERS 2025年第2期10卷 1217-1224页

作者： Kotsovolis, Stelios Demiris, Yiannis Imperial Coll London Dept Elect & Elect Engn Personal Robot Lab London SW7 2BT England

Robots have the potential to assist people with disabilities and the elderly. One of the most common and burdensome tasks for caregivers is dressing. Two challenges of robot-assisted dressing are modeling the dynamics of garments and handling visual occlusions that obstruct the perception of the full state of the garment due to the proximity between the garment, the robot, and the human. In this letter, we propose a diffusion-based dynamics model for garments during robot-assisted dressing that can deal with partial point cloud observations. The diffusion model, conditioned on the observation and the robot's action, is used to predict a full point cloud of the garment's opening of the future state. The model is utilized in a model predictive controller, that is trained iteratively with model-based reinforcement learning. In our experiments, we examine a common problem of dressing: the insertion of a garment's sleeve on an arm. As demonstrated by the performed experiments, the proposed diffusion-based model predictive controller can be effectively used for robot-assisted dressing and handle visual occlusions. Moreover, our approach is highly sample-efficient. Specifically, the controller achieved 91.2% success rate in the examined dressing task with less than 100 sampled trajectories. Real-wold experiments demonstrate that the proposed method can adapt to the sim-to-real gap and generalize well to novel garments and configurations of the body.

关键词： Clothing Robots Point cloud compression Predictive models Diffusion models Visualization Force Dynamics Vectors Three-dimensional displays human-centered robotics model learning for control physical human-robot interaction robot-assisted dressing

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Robots Have Been Seen and Not Heard: Effects of Consequential Sounds on human-Perception of Robots

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IEEE robotics AND AUTOMATION LETTERS 2025年第4期10卷 3980-3987页

作者： Allen, Aimee Drummond, Tom Kulic, Dana Monash Univ Fac Engn Melbourne Vic 3800 Australia Univ Melbourne Sch Comp & Informat Syst Melbourne Vic 3010 Australia

Robots make compulsory machine sounds, known as "consequential sounds," as they move and operate. As robots become more prevalent in workplaces, homes and public spaces, understanding how sounds produced by robots affect human-perceptions of these robots is becoming increasingly important to creating positive human robot interactions (HRI). This letter presents the results from 182 participants (858 trials) investigating how human-perception of robots is changed by consequential sounds. In a between-participants study, participants in the sound condition were shown 5 videos of different robots and asked their opinions on the robots and the sounds they made. This was compared to participants in the control condition who viewed silent videos. Consequential sounds correlated with significantly more negative perceptions of robots, including increased negative "associated affects," feeling more distracted, and being less willing to colocate in a shared environment with robots.

关键词： Robots Robot sensing systems human-robot interaction Videos Sensitivity Employment Training Manipulators Protocols Productivity Robot audition human-centered robotics social HRI consequential sounds

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PRO-MIND: Proximity and Reactivity Optimization of Robot Motion to Tune Safety Limits, human Stress, and Productivity in Industrial Settings

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IEEE TRANSACTIONS ON robotics 2025年 41卷 2067-2085页

作者： Lagomarsino, Marta Lorenzini, Marta De Momi, Elena Ajoudani, Arash Ist Italiano Tecnol Human Robot Interfaces & Interact Lab I-16163 Genoa Italy Politecn Milan Dept Elect Informat & Bioengn I-20133 Milan Italy

Despite impressive advancements of industrial collaborative robots, their potential remains largely untapped due to the difficulty in balancing human safety and comfort with fast production constraints. To help address this challenge, we present PRO-MIND, a novel human-in-the-loop framework that exploits valuable data about the human coworker to optimize robot trajectories. By estimating human attention and mental effort, our method dynamically adjusts safety zones and enables on-the-fly alterations of the robot path to enhance human comfort and optimal stopping conditions. Moreover, we formulate a multiobjective optimization to adapt the robot's trajectory execution time and smoothness based on the current human psychophysical stress, estimated from heart rate variability and frantic movements. These adaptations exploit the properties of B-spline curves to preserve continuity and smoothness, which are crucial factors in improving motion predictability and comfort. Evaluation in two realistic case studies showcases the framework's ability to restrain the operators' workload and stress and to ensure their safety while enhancing human-robot productivity. Further strengths of PRO-MIND include its adaptability to each individual's specific needs and sensitivity to variations in attention, mental effort, and stress during task execution.

关键词： Robots Safety Collaborative robots human factors Trajectory Service robots Productivity Collaboration Robot motion Planning Cognitive human-robot interaction human factors and human-in-the-loop human-centered robotics motion and path planning

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Remote Robotic Palpation With Depth-Vision-Driven Autonomous-Dimensionality-Reduction Shared Control

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IEEE TRANSACTIONS ON robotics 2025年 41卷 1882-1897页

作者： Zhao, Jingwen Costi, Leone Scimeca, Luca Iida, Fumiya Univ Cambridge Dept Engn Cambridge CB2 1TN England Imperial Coll London Dept Bioengn London SW7 2AZ England MILA Inst Montreal PQ H2S 3H1 Canada

Teleoperated medical robots have the potential to revolutionize healthcare. However, when developing systems for tasks like remote palpation, state-of-the-art literature still uses test phantoms of oversimplified geometries, due to the complexity of the required mechanical robot-patient interaction. In reality, human bodies have complex 3-D shapes and require fine-tuning of all six manipulator's degrees of freedom, controlled by the user. In this article, we argue that the implementation of depth-vision-driven autonomous dimensionality-reduction (DVD ADR) shared control can greatly improve the users' performance. The proposed control method keeps the user in control of the end-effector's position, while automatically adjusting its orientation in order to maintain the tactile sensor normal to the phantom's surface. A depth camera and a computer vision algorithm are used to infer the phantom's shape and achieve DVD ADR shared control. Experimental results showcase how this leads to statistically significant performance improvement. Not only were the participants able to achieve more precise palpations, with up to 29.5% and 22.4% more accuracy in position and orientation, respectively, but the DVD ADR shared control allowed them to achieve a 8.8% better detection accuracy while needing 13.8% less time. The abovementioned results are all tested for statistical significance and achieved a p-value lower than 0.05.

关键词： Robots Medical services DVD Phantoms Tactile sensors Robot kinematics Input devices Hands Geometry Vectors Computer vision for medical robotics human-centered robotics shared control telerobotics and teleoperation soft robotics

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Robust Side Following Robotic Wheelchair by Using Homotopy Class of human Intention

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IEEE robotics AND AUTOMATION LETTERS 2025年第5期10卷 5018-5025页

作者： Tan, Kuan Yuee Garg, Neha P. Ramanathan, Manoj Ang, Wei Tech Nanyang Technol Univ NTU Agcy Sci Technol & Res A Rehabil Res Inst Singapore Singapore 138685 Singapore

A side-by-side following robot can alleviate the need for wheelchair pushing, thereby reducing the burden on caregivers and porters. Existing works on side-by-side following cannot be easily adapted to different environments as they either need prior knowledge about the human's path or the robot may take a different path than the human when moving around obstacles. In this work, we propose a side-by-side following system that ensures that the wheelchair takes the same path as the human around obstacles while avoiding them by leveraging the homotopy class of the human's intended path within a shared control framework. Our system can also be easily deployed in various real-world environments as it only needs prior knowledge of the human's final goal. Through quantitative experiments in simulation, we show that our method can perform significantly better compared to a baseline approach that does not leverage the knowledge of the human's intended path. We further validate our method through testing with human subjects using real robotic wheelchair. Our results show higher preference for our method as compared to the baseline method.

关键词： human-aware motion planning human-centered robotics physically assistive devices physically assistive devices rehabilitation robotics rehabilitation robotics rehabilitation robotics

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Robot Behavior Personalization From Sparse User Feedback

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IEEE robotics AND AUTOMATION LETTERS 2025年第5期10卷 4580-4587页

作者： Patel, Maithili Chernova, Sonia Georgia Inst Technol Sch Interact Comp Atlanta GA 30332 USA

As service robots become more general-purpose, they will need to adapt to their users' preferences over a large set of all possible tasks that they can perform. This includes preferences regarding which actions the users prefer to delegate to robots as opposed to doing themselves. Existing personalization approaches require task-specific data for each user. To handle diversity across all household tasks and users, and nuances in user preferences across tasks, we propose to learn a task adaptation function independently, which can be used in tandem with any universal robot policy to personalize robot behavior. We create Task Adaptation using Abstract Concepts (TAACo) framework. TAACo can learn to predict the user's preferred manner of assistance with any given task, by mediating reasoning through a representation composed of abstract concepts built based on user feedback. TAACo can generalize to an open set of household tasks from small amount of user feedback and explain its inferences through intuitive concepts. We evaluate our model on a dataset we collected of 5 people's preferences, and show that TAACo outperforms GPT-4 by 16% and a rule-based system by 54%, on prediction accuracy, with 40 samples of user feedback

关键词： Robots Resource management Robot sensing systems Data mining Accuracy Training Service robots Semantics Older adults Oils human-centered robotics Domestic robotics

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