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IEEE International Conference on MOOCs, Innovation and Technology in Education (IEEE MITE)

作者： Rahul, R. Whitchurch, Ashwin Rao, Madhav Int Inst Informat Technol Bangalore 560100 Karnataka India Protocentral Bangalore 560075 Karnataka India

ISBN: (纸本)9781479968763

A graphical programming tool is developed in a view to help beginners realize the importance of coding in the form of physical robotic movement. Introducing a programming language to students with no background is often felt to be challenging in terms of syntax and control flow of a language. The paper discusses an open source graphical programming tool built on Minibloq platform that allows students to focus more on creative part of programming. The paper proposes a graphical approach to programming where a student need not remember any constructs of a programming language, but relies on the approach to solve a problem. The programming utility is developed for an open source Arduino platform. Currently the tool is developed to control a real robot built around Arduino platform. Thus a platform to learn fundamentals of programming as well as robotics is made available to students. The graphical programming tool with the robotic hardware was found to be easy to learn by high school students during an outreach program conducted by the authors. The framework is also extendable beyond programming and can be further developed to understand robotics.

关键词： control engineering computing control engineering education further education mobile robots public domain software robot programming software tools Minibloq platform introductory programming curriculum open source Arduino platform open source graphical programming tool open source graphical robot programming environment physical robotic movement undergraduates Educational robots Hardware programming profession robot sensing systems Software college student robot programming programming profession open source software control engineering computing Manipulator sensing systems Continuing Education control engineering education programming Computer hardware Software Tools Mobile robots Students computer software Computer programming Languages

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Robobo SmartCity: An Autonomous Driving Model for Computational Intelligence Learning Through Educational robotics

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IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES 2023年第4期16卷 543-559页

作者： Naya-Varela, Martin Guerreiro-Santalla, Sara Baamonde, Tamara Bellas, Francisco Univ A Coruna CIT Res Ctr Integrated Grp Engn Res Ferrol 15403 Spain

This article presents the Robobo SmartCity model, an educational resource to introduce students to computational intelligence (CI) topics using educational robotics as the core learning technology. Robobo SmartCity allows educators to train learners in artificial intelligence (AI) fundamentals from a feasible and practical perspective, following the recommendations of digital education plans to introduce AI at all educational levels. This resource is based on the Robobo educational robot and an autonomous driving setup. It is made up of a city mockup, simulation models, and programming libraries adapted to the students' skill level. In it, students can be trained in CI topics that support robot autonomy, as computer vision, machine learning, or human-robot interaction, while developing solutions in the motivating and challenging scope of autonomous driving. The main details of this open resource are provided with a set of possible challenges to be faced in it. They are organized in terms of the educational level and students' skills. The resource has been mainly tested with secondary and high school students, obtaining successful learning outcomes, presented here to inspire other teachers in taking advantage of this learning technology in their classes.

关键词： Computational intelligence (CI) educational robots educational simulations machine learning mobile and personal devices robot programming science technology engineering and mathematics (STEM)

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Educational robotics and programming in inclusive educational settings: a scoping review 25

Educational robotics and programming in inclusive educationa...

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25th International Symposium on Computers in Education, SIIE 2023

作者： Loureiro, Ana Claudia Meirinhos, Manuel Bragança Portugal

ISBN: (纸本)9798350329315

This article presents a map of studies on the educational potential of robotics and programming in inclusive settings. The scoping review methodology was used based on the procedures recommended by the Joanna Briggs Institute. This method was chosen because of the need to examine and map the main trends in the work done with robotics and programming in educational contexts for children with special needs. Our concern was to search for emerging scientific evidence on the educational potential of robotics and programming in inclusive contexts. Searches were conducted in the Scopus, Web of Science, and Eric databases between 2015 and 2022. The analysis identified five research papers that met the inclusion and exclusion criteria. The results show little abundance of studies in this area, which justifies the scoping methodology. The selected studies show a prevalent trend toward the inclusion of educational robotics and not so much programming. They reveal that the use of robotics and/or programming is a pedagogical strategy that promotes greater interaction, participation, and motivation in children, as well as greater socialization. The relevance of the theme and its complexity highlight the need for further research on this subject. © 2023 IEEE.

关键词： robot programming

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Switch Mode Building a middle ground between Block-based and Text-based programming 23

Switch Mode Building a middle ground between Block-based and...

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2023 Symposium on Learning, Design and Technology, LDT 2023

作者： Lin, Yuhan Weintrop, David McKenna, Jason University of Maryland United States VEX Robotics

ISBN: (纸本)9798400707360

This paper introduces Switch mode, a design strategy to introduce a middle ground to support learners in transitioning from block-based to text-based programming. The Switch mode strategy allows learners to author text-based commands inside a block-based programs. Switch mode blocks can be added by directly dragging and dropping Switch mode blocks from the blocks pallet to the program canvas (Figure 1a) or by right clicking a conventional block and selecting the convert option (Figure 1b). In embedding a scaffolded way to introduce text-based programming in a blocks-based environment, Switch mode can meet the user at their current level of ability in blocks, while also help them move to more sophisticated and powerful programming languages. In providing a means for learns to tinker with text-based programming while still having the supports of block-based tools, Switch mode contributes a novel addition to the growing ecosystem of tools designed to transit novices to the practice of text-based programming. © 2023 Copyright held by the owner/author(s).

关键词： robot programming

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Risk-Aware On-the-Fly Solving of Physical Vehicle Routing Problems 4th

Risk-Aware On-the-Fly Solving of Physical Vehicle Routing Pr...

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4th Workshops on Agents and robots for Reliable Engineered Autonomy

作者： Herynek, Jachym Edelkamp, Stefan Czech Tech Univ Artificial Intelligence Ctr Fac Elect Engn Comp Sci Dept Prague Czech Republic Charles Univ Prague Dept Theoret Comp Sci & Math Logic Fac Math & Phys Prague Czech Republic

ISBN: (纸本)9783031731792;9783031731808

In missions for a set of autonomous vehicles given a complex environment with obstacles and many waypoints to visit, risk-aware routing plays an important role. In this paper, we consider multi-robot, multi-goal motion planning where unsafe areas should be avoided. We assume a geometric environment for a set of high-dimensional robots, providing a motion model with nonlinear dynamics that, for a given state and a small time step, applies a control action and provides a next state or reports a collision. As there are anonymous goals meaning there is no predefined assignment of goals to the robots, the approach assigns goals to them on-the-fly during the solution process. We study the computational limits and possibilities of our approach, derive a scaling framework system that plans and executes the safe travel for the given fleet of robots, and we conduct experiments for benchmark scenarios.

关键词： robot programming

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Extended Reality for Enhanced Human-robot Collaboration: a Human-in-the-Loop Approach 33

Extended Reality for Enhanced Human-Robot Collaboration: a H...

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33rd IEEE International Conference on robot and Human Interactive Communication (IEEE RO-MAN) - Embracing Human-Centered HRI

作者： Karpichev, Yehor Charter, Todd Hong, Jayden Enayati, Amir M. Soufi Honari, Homayoun Tamizi, Mehran Ghafarian Najjaran, Homayoun Univ Victoria Adv Control & Intelligent Syst Lab ACIS Victoria BC V8P 5C2 Canada

ISBN: (纸本)9798350375039;9798350375022

The rise of automation has provided an opportunity to achieve higher efficiency in manufacturing processes, yet it often compromises the flexibility required to promptly respond to evolving market needs and meet the demand for customization. Human-robot collaboration attempts to tackle these challenges by combining the strength and precision of machines with human ingenuity and perceptual understanding. In this paper, we conceptualize and propose an implementation framework for an autonomous, machine learning-based manipulator that incorporates human-in-the-loop principles and leverages Extended Reality (XR) to facilitate intuitive communication and programming between humans and robots. Furthermore, the conceptual framework foresees human involvement directly in the robot learning process, resulting in higher adaptability and task generalization. The paper highlights key technologies enabling the proposed framework, emphasizing the importance of developing the digital ecosystem as a whole. Additionally, we review the existent implementation approaches of XR in human-robot collaboration, showcasing diverse perspectives and methodologies. The challenges and future outlooks are discussed, delving into the major obstacles and potential research avenues of XR for more natural human-robot interaction and integration in the industrial landscape.

关键词： robot programming

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TrustNavGPT: Modeling Uncertainty to Improve Trustworthiness of Audio-Guided LLM-Based robot Navigation

TrustNavGPT: Modeling Uncertainty to Improve Trustworthiness...

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2024 International Conference on Intelligent robots and Systems

作者： Sun, Xingpeng Zhang, Yiran Tang, Xindi Bedi, Amrit Singh Bera, Aniket Purdue Univ W Lafayette IN 47907 USA Univ Cent Florida Orlando FL 32816 USA

ISBN: (纸本)9798350377712;9798350377705

Large language models (LLMs) exhibit a wide range of promising capabilities - from step-by-step planning to commonsense reasoning -that provide utility for robot navigation. However, as humans communicate with robots in the real world, ambiguity and uncertainty may be embedded inside spoken instructions. While LLMs are proficient at processing text in human conversations, they often encounter difficulties with the nuances of verbal instructions and, thus, remain prone to hallucinate trust in human command. In this work, we present TrustNavGPT, an LLM-based audio-guided navigation agent that uses affective cues in spoken communication-elements such as tone and inflection that convey meaning beyond words-allowing it to assess the trustworthiness of human commands and make effective, safe decisions. Experiments across a variety of simulation and real-world setups show a 70.46% success rate in catching command uncertainty and an 80% success rate in finding the target, 48.30%, and 55% outperform existing LLM-based navigation methods, respectively. Additionally, TrustNavGPT shows remarkable resilience against adversarial attacks, highlighted by a 22%+ less decrease ratio than the existing LLM navigation method in success rate. Our approach provides a lightweight yet effective approach that extends existing LLMs to model audio vocal features embedded in the voice command and model uncertainty for safe robotic navigation. For more information, visit the TrustNav project page.

关键词： robot programming

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Online Damage Recovery for Physical robots with Hierarchical Quality-Diversity

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ACM Transactions on Evolutionary Learning and Optimization 2023年第2期3卷 1-23页

作者： Allard, Maxime Smith, Simón C. Chatzilygeroudis, Konstantinos Lim, Bryan Cully, Antoine Imperial College London United Kingdom University of Patras Greece

In real-world environments, robots need to be resilient to damages and robust to unforeseen scenarios. Quality-Diversity (QD) algorithms have been successfully used to make robots adapt to damages in seconds by leveraging a diverse set of learned skills. A high diversity of skills increases the chances of a robot to succeed at overcoming new situations since there are more potential alternatives to solve a new task. However, finding and storing a large behavioural diversity of multiple skills often leads to an increase in computational complexity. Furthermore, robot planning in a large skill space is an additional challenge that arises with an increased number of skills. Hierarchical structures can help to reduce this search and storage complexity by breaking down skills into primitive skills. In this article, we extend the analysis of the Hierarchical Trial and Error algorithm, which uses a hierarchical behavioural repertoire to learn diverse skills and leverages them to make the robot adapt quickly in the physical world. We show that the hierarchical decomposition of skills enables the robot to learn more complex behaviours while keeping the learning of the repertoire tractable. Experiments with a hexapod robot both in simulation and the physical world show that our method solves a maze navigation task with up to, respectively, 20% and 43% less actions than the best baselines while having 78% less complete failures. © 2023 Copyright held by the owner/author(s).

关键词： robot programming

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Optimizing Deep Q-Network for Shortest Path Computation of Mobile robot Agents

Optimizing Deep Q-Network for Shortest Path Computation of M...

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2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference

作者： Sumarudin, A. Sutisna, Nana Syafalni, Infall Trilaksono, Bambang Riyanto Adiono, Trio Inst Teknol Bandung Sch Elect Engn & Informat Bandung Indonesia

ISBN: (纸本)9798350367331;9798350367348

This paper studies the application of Deep Q-Networks (DQN) for shortest-path planning on mobile robots. Implementing DQN on mobile robots poses challenges due to the limited computational resources of embedded systems. The process consists of two mode: the training mode, where an inference model of DQN with weight and bias parameters is generated, and the operational mode, where the DQN model is loaded onto the robot to perform actions in a simulation maze environment with gazebo. This study investigates optimal computational techniques for matrix operations, which are the primary operations in DQN. Computational methods performed on embedded system platforms utilizing GPUs (Jetson Xavier NX) involve studying matrix computation techniques using arrays, 2D arrays with GPUs, and tensors. Based on the experiment, the results show that for the DQN model used in shortest-path planning, computation based on an array matrix significantly speeds up the process.

关键词： robot programming

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Codeless, Inclusive, and End-To-End robotized Manipulations by Leveraging Extended Reality and Digital Twin Technologies 16

Codeless, Inclusive, and End-To-End Robotized Manipulations ...

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16th International Conference on Human System Interaction (HSI)

作者： Huebel, Niklas Kaigom, Eric Guiffo Frankfurt Univ Appl Sci Dept Comp Sci & Engn Frankfurt Germany

ISBN: (纸本)9798350362923;9798350362916

Although the importance of robots for efficient production in smart factories and assistance in home settings is well recognized, their usage in industry and society still faces challenges. A cause lies in the difficulty that comes with programming robots by writing several lines of code to complete basic tasks. Unfortunately, workers in particular as well as citizens in general rarely have the necessary technical background and experience to achieve this complex goal. Recruiting professional robot programmers creates a dependency and increases costs associated with production and assistance. This issue gets more complicated and urgent when robots are deployed to accommodate small batch sizes and heterogeneous preferences from Industry 4.0 and Industry 5.0 applications. In fact, the duration allocated to the changeover in robotized applications might be brief to meet concurrent economic objectives. Furthermore, generic motion primitives provided by robot vendors might not match with irregular and domain-specific Cartesian trajectories in industry, society, and in-between. This work embraces these issues by integrating extended reality and digital twins to propose an intuitive, inclusive, fast, and effective framework to program (i.e., plan and execute) robot motions. Novices can thereby move a manipulator to reach freely specified Cartesian frames and complete grasping maneuvers. This is done without writing any line of code. How our approach empowers citizens is shown by completing manipulations to grasp and relocate workpieces in practice.

关键词： robot programming

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