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2024 ASEE Annual Conference and Exposition

作者： Brown, Leslie Anna Tsugawa, Marissa A. Utah State University United States

The purpose of this WIP research paper is to explore high school STEM teachers' perspectives on teaching computer programming through games and robotics in their classes. In response to high demands for software engineering and a decreased availability of programmers, student interest in computing needs to begin before higher education. Initiatives such as the creation of the Next Generation Science Standards (NGSS) call for cross-cutting engineering and technology instruction in K-12 STEM classes. We investigate how high school STEM teachers can incorporate games, underutilized educational technology (e.g., robots, smartphones), and block-based programming to increase motivation and engagement in computer programming among high school students through a qualitative, collective case-study design. Our case study implements an intervention where we train high school teachers to teach computational thinking through a game that leverages problem solving, block programming, and a 'robotics in healthcare' theme. After observing high school STEM teachers facilitate the designed learning unit, we will interview them about their perceptions on this teaching framework and we will observe their teaching when implementing the game lesson. Data will then be coded and analyzed using thematic analysis to find out the change in preparedness and engagement towards teaching computer science. © American Society for Engineering Education, 2024.

关键词： robot programming

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Towards Autonomous programming of Micro-Assembly robotics 10

Towards Autonomous Programming of Micro-Assembly Robotics

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10th CIRP Conference on Assembly Technology and Systems, CATS 2024

作者： Wiemann, Rolf Terei, Niklas Raatz, Annika Leibniz University Hanover Institute of Assembly Technology An der Universität 2 Garbsen30823 Germany Hanover Germany

Due to the strive towards miniaturized systems and the growing field of optical technologies, micro-assembly is becoming increasingly important. Micro-assembly is characterized by challenging processes that require sub-micron level positioning accuracy regardless of modeling and calibration errors in the manipulator system. Automating these processes requires not only profound expertise about the process itself but also highly skilled personnel for programming the micro-assembly robot since current interfaces lack intuitive programming methods and simulation capabilities. In this paper, we outline a roadmap towards autonomous programming by combining intuitive programming approaches with intelligent and self-learning algorithms. Following this roadmap, the user will be supported progressively by autonomous and intelligent sub-processes until the machine can finally program itself autonomously. Based on a systematic review of the current state of automated micro-assembly and simulation frameworks, we show the capabilities of current approaches and identify key enablers for an autonomous assembly. From these enablers, we derive modules building our proposed framework. Central aspects are the development of a holistic simulation and a data management, which include not only the robot with its sensor systems but also assembly-components. These form the foundation for offline programming and the usage of machine learning algorithms. In order to facilitate future research, we propose the utilization of the robot Operating System 2 framework (ROS2) as a basis for autonomous programming adhering the principles of open-source and enabling seamless integration. © 2024 Elsevier B.V.. All rights reserved.

关键词： robot programming

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Exploring the Impact of Arduino robotics Instruction on Physical Computing and programming Skills 22

Exploring the Impact of Arduino Robotics Instruction on Phys...

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22nd International Conference on Research and Education in Mechatronics, REM 2024

作者： Noordin, Nurul Hazlina Universiti Malaysia Pahang Al-Sultan Abdullah Umpsa Stem Lab The Faculty of Electrical & Electronics Engineering Pahang Pekan26600 Malaysia

ISBN: (纸本)9798331505974

This study examines the transformative potential of robotics education, specifically utilizing the open-source Arduino platform, within mechatronic engineering education. It assesses the influence of an Arduino robotics module on students' performance in engineering education, specifically programming proficiency, electronic components and physical computing. Employing a mixed-methods approach, combining quantitative assessments and qualitative exploration, the research shows improvements in students' skills and knowledge, as evidenced by pre-test and post-test assessments. Survey data shows the platform's positive impact on students' competencies in engineering-related domains. Qualitative analysis focuses into students' experiences and aspirations, highlighting their enhanced programming skills, Arduino proficiency, and increased confidence. Overall, the study offers valuable insights into how Arduino robotics education enhances students' educational experiences and outcomes in engineering education. © 2024 IEEE.

关键词： robot programming

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Middle Code Prediction: Enhancing Code Generation for Uncommon programming Languages in robotics 16

Middle Code Prediction: Enhancing Code Generation for Uncomm...

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16th Asian Conference on Machine Learning, ACML 2024

作者： Jia, Zixi Gao, Hongbin Li, Hexiao Faculty of Robot Science and Engineering Northeastern University Shenyang China

Generating executable code through natural language instructions to drive robotic movements is considered a crucial step towards achieving embodied intelligence. However, in the robotics domain, the scarcity of programming language data often necessitates manually encapsulating high-level APIs to enable Large Language Models(LLMs) to predict code correctly, which is time-consuming and incomplete. Therefore, this paper proposes a three-stage Middle Code Prediction(MCP) scheme, by injecting appropriate prompts at different stages, the LLMs can shift towards predicting middle code that it understands more easily. This middle code can then be converted into the final code through specific scripts, accomplishing the task of generating code in uncommon programming languages automatically and without the need for manually encapsulating high-level APIs. We tested our approach on Hospital Item Transport Dataset(HITD) and found that MCP could improve the mean accuracy of various baseline models to varying degrees, with an overall increase of 31%, while also enhancing the noise resistance of fine-tuned models. We conducted real-world experiments on industrial robotic arms, verifying the feasibility of MCP in scenarios with no API and partial API encapsulation. The method proposed in this paper provides a guideline for code generation in uncommon programming languages within the context of LLMs. Our experimental dataset is available at https://***/Ghbbbbb/MCP. © 2024 Z. Jia, H. Gao & H. Li.

关键词： robot programming

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Learning programming with VEX robotics: Influence on Student Motivation in International Secondary School from Teachers' Perspective 54

Learning Programming with VEX Robotics: Influence on Student...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Choi, Iek-Chong Choi, Wan-Chong Huang, Biyun Mendes, António José School of Education City University of Macau China Macao Polytechnic University Faculty of Applied Sciences China Cisuc University of Coimbra Coimbra Portugal Cisuc University of Coimbra Dep. of Informatics Engineering Coimbra Portugal

ISBN: (纸本)9798350351507

This Research Full paper explores teachers' perceptions of how VEX robotics programming courses influence secondary education students' programming learning motivation. Educational robotics is increasingly recognized as an effective teaching tool for enhancing students' interest in and proficiency in STEM (Science, Technology, Engineering, and Math). VEX robotics is one of the most well-known, practical learning tools that allow students to showcase their programming abilities and creativity. However, little research has been done on how VEX robotics impact teaching practices and students' learning motivation from teachers' perspectives. While VEX robotics is widely utilized in educational environments for teaching robotics and programming concepts, more detailed research is needed to understand how its implementation influences student learning motivation, and overall teaching effectiveness. This study was conducted by interviewing teachers, who were experienced in using VEX in this pedagogical context at an international secondary school in Macao. In particular, the study focused on teachers' opinions about the impact of VEX robotics on students' learning motivation. Qualitative data was obtained through semi-structured interviews with robotic teachers, providing deeper insights into students' motivation and participation in the robotics environment. The study employed the ARCS model as a theoretical framework. The teachers' interview outputs were examined considering the model's four dimensions: attention, relevance, confidence, and satisfaction. The findings highlighted that teachers valued the use of VEX robotics and believed that it increased students' motivation in all the dimensions of the ARCS model. © 2024 IEEE.

关键词： robot programming

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Kinematic Analysis and programming Implementation of Patrol robots Based on Ackermann’s Principle 1

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International Conference on Communications, Signal Processing, and Systems, CSPS 2023

作者： Wang, Renjun Li, Lu Li, Xiaojiang Zhao, Qunfeng Zhonghuan Information College Tianjin University of Technology Tianjin China

ISBN: (数字)9789819975051

ISBN: (纸本)9789819975396

The kinematic analysis of the patrol robot is based on Ackermann theory to derive the relationship between front wheel deflection angle, rear wheel speed and robot target speed. The fitted curve is obtained by plotting a scatter plot of the relationship between the deflection angle of the robot's rudder and the deflection angle of the front wheel and fitting the curve. Ultimately the whole robot is programmed for motion control. This paper provides a basis for theoretical analysis for further research on the Ackermann principle patrol robot. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： robot programming

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Encoding mechanical intelligence using ultraprogrammable joints

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SCIENCE ADVANCES 2025年第17期11卷

作者： Wu, Rui Girardi, Luca Mintchev, Stefano Swiss Fed Inst Technol Environm Robot Lab Dept Environm Syst Sci CH-8092 Zurich Switzerland Swiss Fed Inst Forest Snow & Landscape Res WSL CH-8903 Birmensdorf Switzerland Univ Bristol Sch Engn Math & Technol Bristol England

Animal bodies act as physical controllers, with their finely tuned passive mechanical responses physically "encoding" complex movements and environmental interactions. This capability allows animals to perform challenging tasks with minimal muscular or neural activities, a phenomenon known as embodied intelligence. However, realizing such robots remains challenging due to the lack of mechanically intelligent bodies with abundant tunable parameters-such as tunable stiffness-which is a critical factor akin to the programmable parameters of a neural network. We introduce an elastic rolling cam (ERC) with accurately inverse-designable rotational stiffness. The ERC can closely replicate 100,000 randomly generated stiffness profiles in simulation. Prototypes ranging from millimeters to centimeters were manufactured. To illustrate the mechanical intelligence encoded by programming the ERC's stiffness response, we designed a bipedal robot with optimized ERC passive knees, achieving energy-efficient, open-loop stable walking across uneven terrain. We also demonstrated a quadcopter drone with ERC joints encoding an impact-activated, dual-state morphing.

关键词： robot programming

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Introducing Novice Operators to Collaborative robots: A Hands-On Approach for Learning and Training

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2024年 22卷 3933-3946页

作者： Hansen, Andreas Kornmaaler Villani, Valeria Pupa, Andrea Lassen, Astrid Heidemann Aalborg Univ Ctr Ind Prod DK-9220 Aalborg Denmark Univ Coll Northern Denmark Ind Digital Transformat DK-9200 Aalborg Denmark Aalborg Univ Dept Architecture Design & Media Technol DK-9220 Aalborg Denmark Univ Modena & Reggio Emilia Dept Sci & Methods Engn DISMI I-41121 Reggio Emilia Italy

Collaborative robots (cobots) have seen widespread adoption in industrial applications over the last decade. Cobots can be placed outside protective cages and are generally regarded as much more intuitive and easy to program compared to larger classical industrial robots. However, despite the cobots' widespread adoption, their collaborative potential and opportunity to aid flexible production processes seem hindered by a lack of training and understanding from shop floor workers. Researchers have focused on technical solutions, which allow novice robot users to more easily train collaborative robots. However, most of this work has yet to leave research labs. Therefore, training methods are needed with the goal of transferring skills and knowledge to shop floor workers about how to program collaborative robots. We identify general basic knowledge and skills that a novice must master to program a collaborative robot. We present how to structure and facilitate cobot training based on cognitive apprenticeship and test the training framework on a total of 20 participants using a UR10e and UR3e robot. We considered two conditions: adaptive and self-regulated training. We found that the facilitation was effective in transferring knowledge and skills to novices, however, found no conclusive difference between the adaptive or self-regulated approach. The results demonstrate that, thanks to the proposed training method, both groups are able to significantly reduce task time, achieving a reduction of 40%, while maintaining the same level of performance in terms of position error. Note to Practitioners-This paper was motivated by the fact that the adoption of smaller, so-called collaborative robots is increasing within manufacturing but the potential for a single robot to be used flexibly in multiple places of a production seems unfulfilled. If more unskilled workers understood the collaborative robots and received structured training, they would be capable of programming the r

关键词： robot programming collaborative robotics adaptive training self-regulated training

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Integrated Optimization Method for Task Allocation and Hierarchical Reinforcement Learning in Cargo Transport robots

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2025年第3期145卷 299-306页

作者： Hayashida, Tomohiro Furukawa, Ryuya Sekizaki, Shinya Nishizaki, Ichiro Hiroshima University 1-4-1 Kagamiyama Higashihiroshima Hiroshima739-8527 Japan

This paper focuses on the development of learning methods for achieving effective collaborative transportation by multiple robots in a warehouse environment. In large-scale and complex environments, it is necessary for agents to undergo numerous iterations of learning, such as reinforcement learning, to make appropriate behavioral choices. Traditional multi-agent methods like MADDPG (Multi-Agent Deep Deterministic Policy Gradient) and QMIX face the issue of requiring extensive computation time for environmental exploration. Therefore, this paper proposes a two-stage learning procedure that separates overall optimization, including the formulation of general task execution procedures, from individual optimization based on local situation assessments. Additionally, the effectiveness of the proposed method is demonstrated through simulation system analysis adapted to the target environment. © 2025 The Institute of Electrical Engineers of Japan.

关键词： robot programming

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Thread Carefully: Preventing Starvation in the ROS 2 Multithreaded Executor

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 2024年第11期43卷 3588-3599页

作者： Teper, Harun Kuhse, Daniel Guenzel, Mario von der Brueggen, Georg Howar, Falk Chen, Jian-Jia TU Dortmund Univ Dept Comp Sci D-44227 Dortmund Germany Lamarr Inst D-44227 Dortmund Germany

The robot operating system 2 (ROS 2) is a widely used collection of tools and libraries for building robot applications. It is designed to be flexible and easy to use when creating complex robot systems with many interacting *** its alpha version release in 2015, ROS 2 provides two options in a multithreading operating system, namely the single-threaded executor and the multithreaded executor. The single-threaded executor is starvation-free by design (i.e., every task is eventually executed) even in over-utilized systems, since the set of eligible task instances (called wait set) is only refilled once all the task instances in the wait set are executed. The multithreaded executor extends this mechanism to multiple threads that manage the wait set collaboratively. While intuitively this extension preserves the starvation-free property, and analyses for the multithreaded executor even build upon this assumption, the multithreaded executor has not been shown to be *** this work, we examine the mechanism of the multithreaded executor in ROS 2 and demonstrate that it is prone to starvation, i.e., some tasks may never be executed even in under-utilized systems. This indicates risks for multithreaded executors in the current ROS 2 design and further leads to counterexamples to the state-of-the-art response-time analyses by Jiang et al. (RTSS 2022) and Sobhani et al. (RTAS 2023). We propose a minimal change in the software architecture of the ROS 2 multithreaded executor to enable starvation- and deadlock-free behavior. We empirically test that we prevent starvation in concrete ROS 2 system configurations, and show that our solution incurs a negligible overhead using the autoware reference benchmark. Moreover, we prove that our solution is starvation- and deadlock-free using formal proofs and model checking.

关键词： Software architecture Multithreading Operating systems Instruction sets System recovery programming Model checking Libraries Time factors robots Formal verification multithreading operating systems robot programming

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