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Iranian Conference on Electrical Engineering (ICEE)

作者： Arash Akbari Arman Akbari Mehdi Tale Masouleh Department of Computer Science University of Tehran Tehran Iran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran

Robot grasping is of paramount importance in industrial and service robotics. In recent years, various data-driven algorithms have been proposed to solve the problem of grasp detection and a part of them are based on reinforcement learning (RL) approaches. In a variety of proposed algorithms, random key points are being employed which will make the learning process inefficient and time-consuming. In this paper, a geometry-based algorithm is presented which can find grasp poses based on the geometry of the unknown object and propose the ones which may lead to successful grasping. For the grasp contacts computation part, the presented algorithm produces a finite number of key points based on the 2D shape of the object from a specific point of view. Afterward, it will narrow down the candidate points and output a finite number of successful grasp poses based on three grasp quality metrics for various unknown objects. Three approaches are proposed in order to achieve center points which can describe different parts of a 2D shape. Then, the obtained points are used as the center of circles which are tangent to the 2D shape contour. Also, a new grasp quality metric is proposed. The time of the grasp and the amount of object disorientation after grasping are considered as a metric to evaluate the successfulness of the grasp. Simulation results demonstrate that the proposed algorithm for unknown object grasping can find a finite number of successful grasp poses for different seen or unseen objects without using any random point,

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Elevating AI Research at Cognitive Agents and interaction lab: A Technical Report on High-Performance Computing Infrastructure

TechRxiv

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TechRxiv 2023年

作者： Khan, Md Mosaddek Cognitive Agents and Interaction Lab Department of Computer Science and Engineering University of Dhaka Bangladesh

The Cognitive Agents and interaction lab (CAIL) at the University of Dhaka has strategically developed a focused High-Performance Computing (HPC) facility, underpinning its niche in artificial intelligence (AI) research, with a special emphasis — but not limited to — deep and reinforcement learning within the context of multi-agent systems. This technical report outlines the HPC resources at CAIL, highlighting a number of advanced GPUs that drive our research forward. The facility, supported by multiple grants, exemplifies a model for small-scale, high-impact computational research environments. We detail how these resources empower our team to achieve significant strides in AI, despite the challenges of scale, and set a precedent for innovation in the field. © 2023, CC BY.

关键词： Multi agent systems

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TouchPose: Hand Pose Prediction, Depth Estimation, and Touch Classification from Capacitive Images 21

TouchPose: Hand Pose Prediction, Depth Estimation, and Touch...

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34th Annual ACM Symposium on User Interface Software and Technology, UIST 2021

作者： Ahuja, Karan Streli, Paul Holz, Christian Human-Computer Interaction Institute Carnegie Mellon University United States Department of Computer Science ETH Zürich Switzerland

ISBN: (纸本)9781450386357

Today's touchscreen devices commonly detect the coordinates of user input through capacitive sensing. Yet, these coordinates are the mere 2D manifestations of the more complex 3D configuration of the whole hand - a sensation that touchscreen devices so far remain oblivious to. In this work, we introduce the problem of reconstructing a 3D hand skeleton from capacitive images, which encode the sparse observations captured by touch sensors. These low-resolution images represent intensity mappings that are proportional to the distance to the user's fingers and hands. We present the first dataset of capacitive images with corresponding depth maps and 3D hand pose coordinates, comprising 65,374 aligned records from 10 participants. We introduce our supervised method TouchPose, which learns a 3D hand model and a corresponding depth map using a cross-modal trained embedding from capacitive images in our dataset. We quantitatively evaluate TouchPose's accuracy in touch classification, depth estimation, and 3D joint reconstruction, showing that our model generalizes to hand poses it has never seen during training and can infer joints that lie outside the touch sensor's volume. Enabled by TouchPose, we demonstrate a series of interactive apps and novel interactions on multitouch devices. These applications show TouchPose's versatile capability to serve as a general-purpose model, operating independent of use-case, and establishing 3D hand pose as an integral part of the input dictionary for application designers and developers. We also release our dataset, code, and model to enable future work in this domain. © 2021 Owner/Author.

关键词： Tactile sensors

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Developable metamaterials: Mass-fabricable metamaterials by laser-cutting elastic structures 21

Developable metamaterials: Mass-fabricable metamaterials by ...

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2021 CHI Conference on human Factors in Computing Systems: Making Waves, Combining Strengths, CHI 2021

作者： Signer, Madlaina Signer, Alexandra Sorkine-Hornung, Olga Department of Computer Science Eth Zurich Switzerland Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh United States

ISBN: (纸本)9781450380966

We propose a novel design of engineered, structured materials that leverages fast fabrication technologies, pushing them towards mass-fabrication. Specifically, our metamaterial is designed to be laser cut, to approximate the volumetric shape and allow for locally varying compliance. Traditional mechanical metamaterials consist of intricate cells arranged on a 3-dimensional grid, limiting them to 3D printing-which is slow. Our metamaterial is designed for laser cutting, which is drastically faster. Our structures are best described as ruffled strips of thin sheet material, such as paper, plastics, metals, etc. Users can interactively define the ruffles' anisotropic stiffness directions and local density. Our computational design tool assists users by automatically optimizing the ruffle to fill the shape's volume, and exporting the flat ruffle design ready for cutting. We demonstrate how such ruffled metamaterials can be utilized for, e.g., custom toys with locally varying compliance, custom packaging material, or lightweight formwork for architectural shells. © 2021 ACM.

关键词： Fabrication

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An Interactive Augmented Reality Interface for Personalized Proxemics Modeling

arXiv

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arXiv 2024年

作者： Nigro, Massimiliano O’Connell, Amy Groechel, Thomas Velentza, Anna-Maria Matarić, Maja The Interaction Lab. Department of Computer Science University of Southern California Los AngelesCA90089 United States

Understanding and respecting personal space preferences is essential for socially assistive robots designed for older adult users. This work introduces and evaluates a novel personalized context-aware method for modeling users’ proxemics preferences during human-robot interactions. Using an interactive augmented reality interface, we collected a set of user-preferred distances from the robot and employed an active transfer learning approach to fine-tune a specialized deep learning model. We evaluated this approach through two user studies: 1) a convenience population study (N = 24) to validate the efficacy of the active transfer learning approach;and 2) a user study involving older adults (N = 15) to assess the system’s usability. We compared the data collected with the augmented reality interface and with the physical robot to examine the relationship between proxemics preferences for a virtual robot versus a physically embodied robot. We found that fine-tuning significantly improved model performance: on average, the error in testing decreased by 26.97% after fine-tuning. The system was well-received by older adult participants, who provided valuable feedback and suggestions for future work. Copyright © 2024, The Authors. All rights reserved.

关键词： Active learning

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A DV-Hop dynamic weight positioning model with genetic algorithm

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International Journal of Wireless and Mobile Computing 2021年第2期20卷 139-145页

作者： Wang, Penghong Fan, Tian Cai, Xingjuan Li, Wuchao School of Computer Science and Technology Taiyuan University of Science and Technology Taiyuan Shanxi003024 China Research Centre of Intelligent Interface and Human Computer Interaction Department of Computer Science and Technology Harbin Institute of Technology Harbin Heilongjiang150006 China Jiaxing Vocational Technical College Jiaxing Zhejiang China

Wireless Sensor Networks (WSNs), as an important part of the Internet of Things (IoT), are widely deployed to the location estimation in WSNs. However, at present, the study of DV-Hop algorithm is still limited to the improvement of the sensor nodes in the ordinary region. In this paper, aiming at the complex areas under different application backgrounds, based on the analysis of the localisation principle of the traditional DV-Hop model based on optimisation algorithm, a dynamic weight positioning model based on genetic algorithm (DWMGA-DV-Hop) is proposed. The algorithm performs simulation experiments on three different types of test by adopting dynamic weight calculation model. And experimental results demonstrate that, under different test sets, compared with the standard DV-Hop algorithm, TW-PSODV-Hop and OCS-DV-Hop algorithm, this algorithm has the highest positioning accuracy and stability. Copyright © 2021 Inderscience Enterprises Ltd.

关键词： Genetic algorithms

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Relectrode: A reconfigurable electrode for multi-purpose sensing based on microfluidics 21

Relectrode: A reconfigurable electrode for multi-purpose sen...

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2021 CHI Conference on human Factors in Computing Systems: Making Waves, Combining Strengths, CHI 2021

作者： Sun, Wei Chen, Yanjun Zhan, Simon Han, Teng State Key Laboratory of Computer Science Beijing Key Lab of Human-Computer Interaction Institute of SoftwareChinese Academy of Sciences Beijing China

ISBN: (纸本)9781450380966

In this paper, we propose a reconfgurable electrode, RElectrode, using a microfuidic technique that can change the geometry and material properties of the electrode to satisfy the needs for sensing a variety of diferent types of user input through touch/touchless gestures, pressure, temperature, and distinguish between diferent types of objects or liquids. Unlike the existing approaches, which depend on the specifc-shaped electrode for particular sensing (e.g., coil for inductive sensing), RElectrode enables capacity, inductance, resistance/pressure, temperature, pH sensings all in a single package. We demonstrate the design and fabrication of the microfuidic structure of our RElectrode, evaluate its sensing performance through several studies, and provide some unique applications. RElectrode demonstrates technical feasibility and application values of integrating physical and biochemical properties of microfuidics into novel sensing interfaces. © 2021 ACM.

关键词： Electrodes

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MoveToCode: An Embodied Augmented Reality Visual Programming Language with an Autonomous Robot Tutor for Promoting Student Programming Curiosity

MoveToCode: An Embodied Augmented Reality Visual Programming...

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IEEE International Workshop on Robot and human Communication (ROMAN)

作者： Thomas R Groechel Ipek Goktan Karen Ly Anna-Maria Velentza Maja J Matarić Department of Computer Science Interaction Lab University of Southern California Los Angeles CA USA

Virtual, augmented, and mixed reality for human-robot interaction (VAM-HRI) is a new and rapidly growing field of research. The field of socially assistive robot (SAR) has made impactful advances in educational settings, but has not yet benefited from VAM-HRI advances. We developed MoveToCode - an open-source, embodied (i.e., kinesthetic) learning visual programming language that aims to increase student (ages 8-12) curiosity during programming. MoveToCode uses an augmented reality (AR) autonomous robot tutor named Kuri that models the students’ kinesthetic curiosity and acts to promote their curiosity in programming. MoveToCode design was informed by pilot studies and tested in Los Angeles elementary classrooms $(n =21)$. Results from main study validated our design decisions compared to the pilot study which was conducted in a real elementary school classroom environment $(n =15)$, showing an improvement in perceived robot helpfulness (median $+ \Delta1.25$ out of 5) and number of completed exercises (median $+ \Delta1$, maximum of 11). While no significant changes were found in pre/post student curiosity or intention to program later in life, students wrote more open-ended questions post-study on topics related to robots, programming, research, and if they would like to do the activity again. This work demonstrates the potential of using VAM-HRI in a kinesthetic context for SAR tutors, and highlights the existing conventions and new design considerations for creating AR applications for SAR.

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AI Literacy: Finding Common Threads between Education, Design, Policy, and Explainability

AI Literacy: Finding Common Threads between Education, Desig...

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Extended Abstracts of the 2023 CHI Conference on human Factors in Computing Systems, CHI EA 2023

作者： Long, Duri Roberts, Jessica Magerko, Brian Holstein, Kenneth Dipaola, Daniella Martin, Fred Department of Communication Studies Northwestern University United States School of Interactive Computing Georgia Tech United States School of Literature Media and Communication Georgia Tech United States Human-Computer Interaction Institute Carnegie Mellon University United States Personal Robots Group Mit Media Lab United States Computer Science University of Massachusetts Lowell United States

ISBN: (纸本)9781450394222

Fostering public AI literacy has been a growing area of interest at CHI for several years, and a substantial community is forming around issues such as teaching children how to build and program AI systems, designing learning experiences to broaden public understanding of AI, developing explainable AI systems, understanding how novices make sense of AI, and exploring the relationship between public policy, ethics, and AI literacy. Previous workshops related to AI literacy have been held at other conferences (e.g., SIGCSE, AAAI) that have been mostly focused on bringing together researchers and educators interested in AI education in K-12 classroom environments, an important subfield of this area. Our workshop seeks to cast a wider net that encompasses both HCI research related to introducing AI in K-12 education and also HCI research that is concerned with issues of AI literacy more broadly, including adult education, interactions with AI in the workplace, understanding how users make sense of and learn about AI systems, research on developing explainable AI (XAI) for non-expert users, and public policy issues related to AI literacy. © 2023 Owner/Author.

关键词： Public policy

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Development and Initial Evaluation of a Digital Phenotype Collection System for Adolescents: Proof-of-Concept Study

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JMIR Formative Research 2024年 8卷 e59623页

作者： Cho, Minseo Park, Doeun Choo, Myounglee Kim, Jinwoo Han, Doug Hyun Human Computer Interaction Lab Department of Cognitive Science Yonsei University Seoul South Korea Human Computer Interaction Lab School of Business Yonsei University Seoul South Korea HAII Corp Seoul South Korea College of Medicine Chung-Ang University Seoul South Korea

Background: The growing concern on adolescent mental health calls for proactive early detection and intervention strategies. There is a recognition of the link between digital phenotypes and mental health, drawing attention to their potential use. However, the process of collecting digital phenotype data presents challenges despite its promising prospects. Objective: This study aims to develop and validate system concepts for collecting adolescent digital phenotypes that effectively manage inherent challenges in the process. Methods: In a formative investigation (N=34), we observed adolescent self-recording behaviors and conducted interviews to develop design goals. These goals were then translated into system concepts, which included planners resembling interfaces, simplified data input with tags, visual reports on behaviors and moods, and supportive ecological momentary assessment (EMA) prompts. A proof-of-concept study was conducted over 2 weeks (n=16), using tools that simulated the concepts to record daily activities and complete EMA surveys. The effectiveness of the system was evaluated through semistructured interviews, supplemented by an analysis of the frequency of records and responses. Results: The interview findings revealed overall satisfaction with the system concepts, emphasizing strong support for self-recording. Participants consistently maintained daily records throughout the study period, with no missing data. They particularly valued the recording procedures that aligned well with their self-recording goal of time management, facilitated by the interface design and simplified recording procedures. Visualizations during recording and subsequent report viewing further enhanced engagement by identifying missing data and encouraging deeper self-reflection. The average EMA compliance reached 72%, attributed to a design that faithfully reflected adolescents’ lives, with surveys scheduled at convenient times and supportive messages tailored to their dai

关键词： adolescent mental health adolescents digital phenotyping ecological momentary assessment phenotype data phenotypes proof of concept qualitative research self-monitoring smartphone apps

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