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检索条件"主题词=Robot Programming"

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Intelligence Demand-Driven Automatic Path Planning Study for Substation Inspection robots 5

Intelligence Demand-Driven Automatic Path Planning Study for...

引用

5th International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2024

作者： Wang, Hongkai Feng, Jun Zhao, Shuai Wang, Yidan Song, Haomin State Grid Zhejiang Electric Power Company Information & Telecommunication Branch Zhejiang Hangzhou310000 China

ISBN: (纸本)9798331528911

[Purpose/Significance] The problems of insufficient path planning accuracy and poor environmental adaptability during substation inspection are rooted in the lack of a clear and accurate description of intelligence requirements in complex environments, which leads to insufficient inspection efficiency and safety. This study aims to improve the intelligence level of automatic path planning for substation inspection robots and reduce the risk of power accidents through an intelligence demand-driven approach. [Methods/Process] This study emphasizes the key role of intelligence requirements in the whole process of substation inspection. By identifying the intelligence requirements in the substation environment, the inspection tasks are fine-grained, the substation contingency task module library is constructed, and the intelligence requirement association library for inspection operations and execution subjects is established. Based on this, an automatic route optimization strategy integrating A∗ algorithm and potential field approach is proposed to form a research framework to effectively respond to inspection tasks under the complex environment of substations. [RESULTS/CONCLUSIONS] The constructed fine-grained task module library and intelligence requirement association library are established before inspection and dynamically updated during inspection. The synergistic effect of these two libraries makes the identification of intelligence requirements in the inspection process faster and more objective, enhances the robot's precision when acquiring environmental information, and enhances the flexibility and reliability of route determination. © 2024 IEEE.

关键词： robot programming

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Navigating Complexity: Data Structure Impact on Path Planning Algorithms in Autonomous Systems 6

Navigating Complexity: Data Structure Impact on Path Plannin...

引用

6th IEEE Novel Intelligent and Leading Emerging Sciences Conference, NILES 2024

作者： Emad, Hend Mabrouk, Mai S. Elnokrashy, Ahmed F. Nile University Biomedical Informatics Giza Egypt Nile University Computer Science Giza Egypt Benha University Electrical Engineering Benha Egypt

ISBN: (纸本)9798350378511

Navigating a busy cityscape with a fleet of autonomous vehicles requires each to seamlessly maneuver through traffic with split-second decisions. Path planning is the backbone of such advanced machinery applications, from mobile robots to unmanned ground vehicles, where the choice of data structure plays a pivotal role in determining memory usage, planning time, and algorithm reliability. This research rigorously evaluates Grassfire, Dijkstra, A *, and RRT* algorithms based on key metrics using real GPS readings, across diverse environment representations and obstacle conditions. Our findings provide guidance for selecting the optimal algorithms and data structures tailored to specific environmental complexities. By evaluating the performance of these algorithms under various environmental conditions, the study offers insights that can help researchers and practitioners choose the most suitable algorithms and data structures for their autonomous vehicle applications. The ability to match the algorithm and data structure to the specific environmental challenges faced by autonomous vehicles is crucial for ensuring efficient and reliable path planning, which is the backbone of advanced machinery applications. © 2024 IEEE.

关键词： robot programming

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An Improved Heuristic Path Planning Algorithm for Mobile robot Navigating on Uneven Terrains

An Improved Heuristic Path Planning Algorithm for Mobile Rob...

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2024 IEEE International Conference on Unmanned Systems, ICUS 2024

作者： Shao, Shiliang Shi, Xianyu Wang, Shaocong Liu, Da Liu, Yong Wang, Ting State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of the Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350384185

Planning secure and dependable paths for autonomous robot systems is crucial in uneven terrains. This research introduces an improved heuristic path-planning (IHPP) algorithm with multiple constraints. Initially, SLAM algorithm is utilized to generate a point cloud map of the uneven terrain, evaluating geometric information such as slope, roughness, and vertical obstacle height through the voxelized grid. Next, considering the robot's traversal capabilities, a non-linear relation is established between the robot's safe traversal cost and the geometric structure of the terrain to prevent hazardous behaviors like overturning on uneven terrain. Subsequently, the heuristic function of the IHPP algorithm is refined by utilizing the benefits of Chebyshev distance to handle obstacle avoidance. In addition, the cosine similarity to limit the deviation between the robot's current and target directions. This optimization aims to optimize the robot's turning behavior and minimize unnecessary turns, achieving smoother and greater path planning. Finally, experiments were conducted in four environments to validate the applicability and advantages of this algorithm in addressing safety path planning problems in uneven terrains. © 2024 IEEE.

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Towards Reconfigurable Cyber-Physical-Human Systems: Leveraging Mixed Reality and Digital Twins to integrate Human Operations 57

Towards Reconfigurable Cyber-Physical-Human Systems: Leverag...

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18th IFAC Workshop on Time Delay Systems, TDS 2024

作者： Mayer, Anjela Kastner, Kevin Mühlbeier, Edgar Chardonnet, Jean-Rémy Reichwald, Julian Puchta, Alexander Fleischer, Jürgen Ovtcharova, Jivka Institute for Information Management in Engineering Karlsruhe Institute of Technology Zirkel 2 Karlsruhe76131 Germany Institute of Production Science Karlsruhe Institute of Technology Kaiserstraße 12 Karlsruhe76131 Germany Virtual Engineering Competence Center Mannheim University of Applied Sciences Paul-Wittsack-Straße 10 Mannheim68163 Germany Arts et Métiers Institute of Technology LISPEN HESAM Université 11 rue Georges Maugey Chalon-sur-Saône71100 France

The agility to swiftly and efficiently reconfigure manufacturing systems is crucial in today's rapidly evolving market demands. Traditional reconfiguration operations often fall short, presenting non-intuitive and error-prone tasks for human operators, without the aid of systematic approaches or supportive technologies. This gap not only complicates the reconfiguration process but also significantly increases the risk of errors. In response, we introduce a novel approach that integrates Mixed Reality and Digital Twins within Cyber-Physical Systems to address these challenges. This enhances the human element in manufacturing reconfigurations by facilitating intuitive trajectory planning for robot (re)programming and comprehensive documentation of physical processes, including human operations. The design and implementation of the approach aim to significantly enhance manufacturing reconfigurations by reducing downtime, complexity, and human error. Further, the paper outlines directions for future work, including comprehensive system validation within a Cyber-Physical-Human manufacturing system, emphasizing the critical role of human operators in the reconfiguration process and the potential for technology to address traditional shortcomings. © 2024 The Authors.

关键词： robot programming

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Prototyping Educational and Scientific Devices with a Custom Python Library for Lego robot Inventor 5in1 Mindstorms Kit: A Leap Motion Integration Case Study 16

Prototyping Educational and Scientific Devices with a Custom...

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16th International Conference on Computer Supported Education, CSEDU 2024

作者： Malinowski, Jakub Artiemjew, Piotr Cybowski, Wojciech Scientific Circle of Robotics Univeristy of Warmia and Mazury in Olsztyn Poland University of Warmia and Mazury in Olsztyn Poland

ISBN: (纸本)9789897586972

This paper introduces a custom Python library specifically developed to enable the rapid prototyping of devices for educational and scientific purposes using the Lego Mindstorms robot Inventor set. The integration of Leap Motion as a case study exemplifies the library’s extensive capabilities in facilitating intuitive and interactive control mechanisms for mobile robots. Through the Leap Motion controller, this research explores the innovative application of real-time hand gesture recognition, allowing users to command the robot with natural gestures for movement, direction, and speed adjustments. The decision to use Leap Motion as a case study serves to highlight the library’s adaptability and effectiveness in processing and interpreting gesture data, thereby offering a glimpse into the broader potential of the library for various applications. This approach demonstrates how educators and researchers can utilize the library to create engaging learning experiences and conduct exploratory projects in robotics and beyond. By detailing the process of integrating Leap Motion with the robot Inventor set through our Python library, the paper underscores the potential of such tools in enhancing interactive learning environments and advancing the field of educational technology. The open-source nature of the library, coupled with its modular design, ensures that it can be easily extended and adapted to fit a wide range of educational and scientific prototyping needs. This paper thus presents a valuable resource for those looking to explore the frontiers of interactive technology in education and research. Copyright © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

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Multi-robots Path Planning and Mapping for Exploring Unknown Environment 7

Multi-robots Path Planning and Mapping for Exploring Unknown...

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7th International Conference on Intelligent robotics and Control Engineering, IRCE 2024

作者： Long, Jinghao Zhang, Bin Kanagawa University Dept. of Mechanical Engineering Yokohama Japan

ISBN: (纸本)9798350352399

This study focuses on improving multi-robots path planning and mapping efficiency for exploring unknow environment. By improving the conventional exploration algorithm based on frontier to adapt to multi-robot systems, the robots will explore different areas and dynamically fuse individual maps generated by each robot into a comprehensive global map. The study introduces a unique joint path planning mechanism for each robot, enabling dynamic optimization of exploration target points and minimizing redundant exploration. The improved approach significantly reduces exploration time and collision incidents, as demonstrated by experiments comparing single and multiple robot exploration scenarios. © 2024 IEEE.

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ROS-Based Control of an Industrial Micro-Assembly robot 57

ROS-Based Control of an Industrial Micro-Assembly Robot

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18th IFAC Workshop on Time Delay Systems, TDS 2024

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

Today's manufacturing is progressively challenged by high product variant turnovers, low standardization, and small lot sizes. These characteristics can also be seen in the growing sector of manufacturing of optical systems, in which the micro-assembly of the components is currently the main cost driver. In the sector of industrial robotics, research has addressed these challenges by developing rapidly reconfigurable robotic cells. Typically, these solutions are based on high-level task programming and a hardware and software-agnostic virtualised machine control interface, which is often facilitated by the open-source robot Operating System (ROS) platform. While research in the domain of micro-assembly has also introduced virtual programming to assembly systems, the focus has rather been on assisting experienced engineers with the implementation of processes than on enabling rapid assembly of prototypes by inexperienced personnel. To bridge this gap, we are working on a holistic framework for autonomous process implementation that is specifically focused on the unique boundary conditions of micro-assembly. As one of the initial steps, in this paper, we present a case study of the implementation of ROS2-based control of an industrial micro-assembly robot. Furthermore, we detail on the advantages, prospects, and limitations, our design choices encompass. © 2024 The Authors.

关键词： robot programming

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Mobile robot Path Planning Method Based on Improved A* Algorithm and robot Operating System 4

Mobile Robot Path Planning Method Based on Improved A* Algor...

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4th International Symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2024

作者： Ming, Keke Liu, Feifei Zhang, Zhen School of Mechanical and Electrical Engineering Jiangxi University of Science and Technology Ganzhou China School of Electrical Engineering and Automation Jiangxi University of Science and Technology Ganzhou China

ISBN: (纸本)9798331541729

As mobile robot technology advances, path planning emerges as a crucial research area. This paper introduces an improved A* algorithm to optimize path planning, addressing the A* algorithm's limitations like excessive node expansion, prolonged computation time, and frequent path turning angles, while ensuring safety, efficiency, and stability. The proposed algorithm enhances the A* algorithm's node expansion by selecting search nodes according to obstacle positions. Then, the heuristic function is dynamically weighted to enhance the search efficiency of the algorithm. Finally, the path is optimized using cubic Bézier curves to ensure smoothness. Experiments in ROS confirm that the proposed algorithm performs well and is suitable as path planning algorithm for mobile robots. © 2024 IEEE.

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Path Planning and Navigation in Autonomous Mobile robots (AMRs): A Review 3rd

Path Planning and Navigation in Autonomous Mobile Robots (AM...

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3rd International Conference on Artificial-Business Analytics, Quantum and Machine Learning: Trends, Perspectives, and Prospects, Com-IT-Con 2023

作者： Sharma, Urvashi Rani, Shalli Anand, Abhineet Chitkara University Institute of Engineering and Technology Chitkara University Punjab Patiala140401 India Computer Science and Engineering Apex Institute of Technology Chandigarh University Punjab Gharuna Mohali140413 India

ISBN: (纸本)9789819725076

Nowadays many roboticists are focusing on Autonomous Mobile robots (AMRs). Mobile robots are those that can move around their environment and are not limited to a specific physical region. An independent movement of a robot without the aid of any mechanical or electrical controlling devices makes it an autonomous mobile robot. AMRs carry out "free" or "natural" navigation without the use of any gear, including cables, tapes, reflectors, QR codes etc. As the development of Smart Cities includes Smart Vehicles/robots and to enable autonomous vehicle operation in metropolitan environments with unpredictable traffic, various real-time systems, path-planning, including the environment, must work together. Perception, localization, planning, and control are all important. In this paper, we have reviewed on various path planning and navigation techniques of Autonomous Mobile robots (AMR) and showing results on increasing trend of research on different algorithms in last ten years. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

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Fast LiDAR Informed Visual Search in Unseen Indoor Environments

Fast LiDAR Informed Visual Search in Unseen Indoor Environme...

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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Gupta, Ryan Morgenstein, Kyle Ortega, Steven Sentis, Luis University of Texas at Austin Department of Aerospace Engineering and Engineering Mechanics AustinTX78712 United States University of Texas at Austin Department of Mechanical Engineering AustinTX78712 United States

ISBN: (纸本)9798331531614

This paper details a system for fast visual exploration and search without prior map information. We leverage frontier based planning with both LiDAR and visual sensing and augment it with a perception module that contextually labels points in the surroundings from wide Field of View 2D LiDAR scans. The goal of the perception module is to recognize surrounding points more likely to be the search target in order to provide an informed prior on which to plan next best viewpoints. The robust map-free scan classifier used to label pixels in the robot's surroundings is trained from expert data collected using a simple cart platform equipped with a map-based classifier. We propose a novel utility function that accounts for the contextual data found from the classifier. The resulting viewpoints encourage the robot to explore points unlikely to be permanent in the environment, leading the robot to locate objects of interest faster than several existing baseline algorithms. Our proposed system is further validated in real-world search experiments for single and multiple search objects with a Spot robot in two unseen environments. Videos of experiments, implementation details and open source code can be found at https://***/view/lives-2024/home. © 2025 IEEE.

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