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Autonomous Unmanned Aerial Vehicle Indoor Navigation Based on Deep Learning Approaches

Autonomous Unmanned Aerial Vehicle Indoor Navigation Based o...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Hamed Ghasemi Elnaz Balazadeh Shayan Malekpour Ahmad Kalhor Mehdi Tale Masouleh Human and Robot Interaction Laboratory School of Electrical and Computer engineering University of Tehran Tehran Iran Human and Robot Interaction Laboratory University of Tehran Tehran Iran Department of electrical and computer engineering School of Electrical and Computer engineering University of Tehran Tehran Iran

This article presents two approaches based on deep learning for achieving autonomous navigation and subsequently, conducts an in-depth comparative analysis to elaborate their respective performance. Both methods leverage neural networks to facilitate navigation. The first approach employs a deep convolutional neural network to identify suitable areas for forward movement, while the second method utilizes the drone’s front camera to capture images, which are then processed by a generative network to generate corresponding depth images. Importantly, both approaches rely solely on an RGB camera, resulting in cost savings for the robot and reduced energy consumption. The training data used for classifying collision-free and appropriate paths were gathered from simulated environments closely resembling real indoor settings. The proposed model calculates the probability associated with each segment of the input image, enabling the selection of the most viable area for drone flight. Incorporating generative networks as a depth estimation module enhances flight accuracy, making navigation in uncharted environments more straightforward. The accuracy of depth estimation was evaluated using standard criteria, achieving an accuracy rate of $84 \%$. This result underscores the effectiveness of the proposed method.

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Post-Training Quantization in Brain-computer Interfaces Based on Event-Related Potential Detection

Post-Training Quantization in Brain-Computer Interfaces Base...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Hubert Cecotti Dalvir Dhaliwal Hardip Singh Yohesh Kumar Meena Department of Computer Science California State University Fresno USA Human-AI Interaction (HAIx) Lab IIT Gandhinagar India

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Post-training quantization (PTQ) is a technique used to optimize and reduce the memory footprint and computational requirements of machine learning models. It has been used primarily for neural networks. For Brain-computer Interfaces (BCI) that are fully portable and usable in various situations, it is necessary to provide approaches that are lightweight for storage and computation. In this paper, we propose the evaluation of post-training quantization on state-of-the-art approaches in brain-computer interfaces and assess their impact on accuracy. We evaluate the performance of the single-trial detection of event-related potentials representing one major BCI paradigm. The area under the receiver operating characteristic curve drops from 0.861 to 0.825 with PTQ when applied on both spatial filters and the classifier, while reducing the size of the model by about x 15. The results support the conclusion that PTQ can substantially reduce the memory footprint of the models while keeping roughly the same level of accuracy.

关键词： Quantization (signal) Accuracy Memory management Deep architecture Receivers Machine learning Brain modeling Spatial filters Brain-computer interfaces Hardware

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"I am a Technology Creator": Black Girls as Technosocial Change Agents in a Culturally-Responsive Robotics Camp 25

"I am a Technology Creator": Black Girls as Technosocial Cha...

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2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Li, Chun Solyst, Jaemarie Scott, Safiyyah Howse, Gabriella Nkrumah, Tara Walker, Erin Ogan, Amy Stewart, Angela E.B. Department of Informatics and Networked System University of Pittsburgh PittsburghPA United States Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States School of Computer Science Carnegie Mellon University PittsburghPA United States Center for Gender Equity in Science and Technology Arizona State University TempeAZ United States Department of Computer Science University of Pittsburgh PittsburghPA United States

ISBN: (纸本)9798400713941

Black girls and women have long been creators in computing spaces. However, much computing education positions Black girls as workers who execute tasks for others' purposes. Our work takes a different approach by positioning Black girls as technosocial change agents who challenge dominant narratives and construct more liberating identities and social relations as they create new technologies. We draw on data from seven Black girls, ages 9-12, who participated in a 20-hour culturally responsive computing (CRC) camp focused on robotics. Using a thematic analysis approach, we explore how these Black girls demonstrate and enhance their technosocial change agency (TSCA) throughout the camp. We identify themes related to how creating technology helps Black girls refine and fulfill their definitions of technical creators and develop agency through technology creation. We discuss computing education and technology design recommendations within the TSCA framework to support learners' emerging TSCA in future CRC programs. © 2025 Copyright held by the owner/author(s).

关键词： Educational robots

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Quantifying Spatial Domain Explanations in BCI using Earth Mover’s Distance

Quantifying Spatial Domain Explanations in BCI using Earth M...

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International Joint Conference on Neural Networks (IJCNN)

作者： Param Rajpura Hubert Cecotti Yogesh Kumar Meena Human-AI Interaction (HAIx) Lab IIT Gandhinagar India Department of Computer Science California State University Fresno USA

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Brain-computer interface (BCI) systems facilitate unique communication between humans and computers, benefiting severely disabled individuals. Despite decades of research, BCIs are not fully integrated into clinical and commercial settings. It’s crucial to assess and explain BCI performance, offering clear explanations for potential users to avoid frustration when it doesn’t work as expected. This work investigates the efficacy of different deep learning and Riemannian geometry-based classification models in the context of motor imagery (MI) based BCI using electroencephalography (EEG). We then propose an optimal transport theory-based approach using earth mover’s distance (EMD) to quantify the comparison of the feature relevance map with the domain knowledge of neuroscience. For this, we utilized explainable AI (XAI) techniques for generating feature relevance in the spatial domain to identify important channels for model outcomes. Three state-of-the-art models are implemented - 1) Riemannian geometry-based classifier, 2) EEGNet, and 3) EEG Conformer, and the observed trend in the model’s accuracy across different architectures on the dataset correlates with the proposed feature relevance metrics. The models with diverse architectures perform significantly better when trained on channels relevant to motor imagery than data-driven channel selection. This work focuses attention on the necessity for interpretability and incorporating metrics beyond accuracy, underscores the value of combining domain knowledge and quantifying model interpretations with data-driven approaches in creating reliable and robust Brain-computer Interfaces (BCIs).

关键词： Measurement Earth Accuracy computer architecture Brain modeling Motors Feature extraction

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Instruction-Driven Game Engine: A Poker Case Study

Instruction-Driven Game Engine: A Poker Case Study

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Wu, Hongqiu Liu, Xingyuan Wang, Yan Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3 China Tencent China

ISBN: (纸本)9798891761674

The Instruction-Driven Game Engine (IDGE) project aims to democratize game development by enabling a large language model (LLM) to follow free-form game descriptions and generate game-play processes. The IDGE allows users to create games simply by natural language instructions, which significantly lowers the barrier for game development. We approach the learning process for IDGEs as a Next State Prediction task, wherein the model autoregressively predicts the game states given player actions. The computation of game states must be precise;otherwise, slight errors could corrupt the game-play experience. This is challenging because of the gap between stability and diversity. To address this, we train the IDGE in a curriculum manner that progressively increases its exposure to complex scenarios. Our initial progress lies in developing an IDGE for Poker, which not only supports a wide range of poker variants but also allows for highly individualized new poker games through natural language inputs. This work lays the groundwork for future advancements in transforming how games are created and played. © 2024 Association for Computational Linguistics.

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[DC] Context-Aware Inference and Adaptation in Augmented Reality

[DC] Context-Aware Inference and Adaptation in Augmented Rea...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Shakiba Davari Center for Human-Computer Interaction and Department of Computer Science Virginia TechUSA

ISBN: (纸本)9781665484039

Augmented Reality(AR) offers the potential for easy and efficient information access, reinforcing the wide belief that AR Glasses are the next-generation of personal computing devices. However, to realize this all-day AR vision, the AR interface must be able to address the challenges that constant and pervasive presence of virtual content can cause for the user. The optimal interface, that is the most efficient yet least intrusive, in one context may be the worst interface for another context. Throughout the day, as the user switches context, an optimal all-day interface must adapts its virtual content display and interactions as well. This work aims to propose a research agenda to design and validate different adaptation techniques and context-aware AR interfaces and introduce a framework for the design of such intelligent interfaces.

关键词： human computer interaction Three-dimensional displays Conferences Glass Next generation networking Augmented reality

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Gaze Behaviour in Adolescents with Obsessive-Compulsive Disorder During Exposure Within Cognitive-Behavioural Therapy 17th

Gaze Behaviour in Adolescents with Obsessive-Compulsive Di...

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17th EAI International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2023

作者： Thierfelder, Annika Severitt, Björn Klein, Carolin S. Alt, Annika K. Hollmann, Karsten Bulling, Andreas Ilg, Winfried Hertie Institute for Clinical Brain Research Section for Computational Sensomotorics University Hospital Tübingen Tübingen Germany Department of Computer Science Human-Computer Interaction University of Tübingen Tübingen Germany Department of Child and Adolescent Psychiatry Psychosomatics and Psychotherapy University Hospital Tübingen Tübingen Germany Institute for Visualisation and Interactive Systems University Stuttgart Stuttgart Germany

ISBN: (纸本)9783031597169

Digital health interventions that involve monitoring patient behaviour increasingly benefit from improvements in sensor technology. Eye tracking in particular can provide useful information for psychotherapy but an effective method to extract this information is currently missing. We propose a method to analyse natural gaze behaviour during exposure exercises for obsessive-compulsive disorder (OCD). At the core of our method is a neural network to detect fixations based on gaze patch similarities. Detected fixations are clustered into exposure-relevant, therapist, and other locations and corresponding eye movement metrics are correlated with subjective stress reported during exposure. We evaluate our method on gaze and stress data recorded during video-based psychotherapy of four adolescents with OCD. We found that fixation duration onto exposure-relevant locations consistently increases with the perceived stress level as opposed to fixations onto other locations. Fixation behaviour towards the therapist varied largely between patients. Taken together, our results not only demonstrate the effectiveness of our method for analysing natural gaze behaviour during exposure sessions. The fixation analysis shows that patients allocate more attention towards exposure-related objects under higher stress levels, suggesting higher mental load. As such, providing feedback on fixation behaviour holds significant promise to support therapists in monitoring intensity of exposure exercises. © ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Location

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How Students in Creative Educations Appropriate Technology: A phenomenological analysis. 25

How Students in Creative Educations Appropriate Technology: ...

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2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Horvath, Anca-Simona Raptis, Dimitrios Department of Communication and Psychology Research Laboratory for Art and Technology Aalborg University Aalborg Denmark Department of Computer Science Human-Centred Computing Group Aalborg University Aalborg Denmark

ISBN: (纸本)9798400713941

Building technological literacy is an important topic in education today while at the same time, creativity is seen as a desirable skill for professional practice and education alike as it is considered a catalyst for innovation. In this paper, we present a case study where we aim to understand how students in a creative education appropriate technology. We analyze qualitative data collected from students in a STEAM higher education undergraduate program called Art&Technology: a program where students are introduced to an assortment of technological tools including software, programming, digital fabrication and physical prototyping which they employ in creating a variety of artifacts. We analyze how students learn and interact with these technologies by analyzing the collected data through a phenomenological lens of technology appropriation. We contribute with understandings on how technology is appropriated as it transforms from an object, to a tool until it finally becomes equipment. © 2025 Copyright held by the owner/author(s).

关键词： Students

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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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