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6th International Conference on Internet of Things, Automation and Artificial Intelligence, IoTAAI 2024

作者： Yu, Haochen Ren, Xiaoming Shanghai Dianji University School of Electrical Engineering Shanghai China

ISBN: (纸本)9798350386974

Aiming at the shortcomings of sand cat swarm optimization (SCSO), such as long search time, easy to fall into local optimal and weak Dynamic planning ability, a path planning method combining improved sand cat and Dynamic Window Approach (DWA) was proposed. The problem of global path optimization and local dynamic obstacle avoidance path planning of mobile robot is solved. To solve the above problems, Cubic mapped chaotic search is firstly used to initialize the population, and triangular walking strategy is used to increase the diversity of particles, thus reducing the time of particle optimization and improving the convergence speed of the algorithm. Meanwhile, adaptive Levy flight mechanism is introduced to effectively improve the global search ability and the ability to jump out of the local optimal. Finally, the DWA algorithm is introduced into the improved sand cat algorithm for local path planning to realize the dynamic obstacle avoidance of the robot. The simulation results show that the proposed algorithm is better than the traditional algorithm in path length, iteration times, convergence time, path smoothness, safety and reliability. © 2024 IEEE.

关键词： robot programming

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Learning and Generalizing Cooperative Manipulation Skills Using Parametric Dynamic Movement Primitives

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2022年第4期19卷 3968-3979页

作者： Kim, Hyoin Oh, Changsuk Jang, Inkyu Park, Sungyong Seo, Hoseong Kim, H. Jin Samsung Elect Mechatron Res & Dev Ctr Gyeonggi 16677 South Korea Seoul Natl Univ Dept Mech & Aerosp Engn Seoul 08826 South Korea Seoul Natl Univ Automat & Syst Res Inst Seoul 08826 South Korea Samsung Elect Samsung Res Seoul 497335 South Korea

This paper presents an approach that generates the overall trajectory of mobile manipulators for a complex mission consisting of several sub-tasks. Parametric dynamic movement primitives (PDMPs) can quickly generalize the online motion of robot manipulation by learning multiple demonstrations in offline. However, regarding complex missions consisting of multiple sub-tasks, a large number of demonstrations are required for full generalization, which is impractical. In this paper, we propose a framework that reduces the number of demonstrations for a complex mission. In the proposed method, complex demonstrations are segmented into multiple unit motions representing sub-tasks, and one PDMP is formed per each segment, resulting in multiple PDMPs. The phase decision process determines which sub-task and associated PDMPs to be executed online, allowing multiple PDMPs to be autonomously configured within an integrated framework. In order to generalize the execution time and regional goal in each phase, the Gaussian process regression (GPR) is applied. Simulation results from two different scenarios confirm that the proposed framework not only effectively reduces the number of demonstrations but also improves generalization performance. The actual experiments also demonstrate that the mobile manipulators effectively perform complex missions through the proposed framework.

关键词： robots Trajectory Manipulator dynamics Heuristic algorithms Complexity theory Task analysis Real-time systems Motion-planning manipulator motion-planning mobile robot motion-planning robot programming multiple manipulators learning from demonstration motion representation algorithm parametric dynamic movement primitives dynamic movement primitives mobile manipulation

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Adaptive Path Planning Method for robot-Assisted Craniotomy 17th

Adaptive Path Planning Method for Robot-Assisted Craniotomy

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17th International Conference on Intelligent robotics and Applications, ICIRA 2024

作者： Li, Zhichao Hong, Shunming Ma, XiaoDong Wu, Dan Department of Mechanical Engineering Tsinghua University Beijing100084 China Department of Neurosurgery General Hospital of Chinese PLA Beijing100853 China

ISBN: (纸本)9789819607761

Craniotomy is a prerequisite for many neuro-surgeries such as intracranial tumor resection and decompression of cerebral hemorrhage. However, existing manual craniotomy methods are time-consuming and labor-intensive, presenting low efficiency and security. robots have shown great potential for safe, precise and efficient craniotomy by introducing accurate positioning and stable motion control. We proposed a method that automatically computes operation path for robotic craniotomy and adapt to the irregular geometric change of the skull, based on the surgeon’s surgical plan from computed tomography (CT) images. The drilling path is generated from intersection between the skull entity and surgeon-input drilling intents. A virtual-center (VC) method is developed to adaptively compute an initial milling path through the generated drilling path, which is then improved under both clinical and skull-cutting constrains. The results show that our method works effectively to generate the operation path adapting to the unstructured skull. This research highlights the potential for optimizing current craniotomy procedures by employing the robot, laying the foundation for future autonomous robot-based craniotomy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： robot programming

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Development of an Automation Module for Planning Trajectories for Painting Aircraft Fuselage Elements 1

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7th International Russian Automation Conference, RusAutoCon 2024

作者： Voroshchenko, V.D. Gorkavyy, M.A. Gudim, A.S. Komsomolsk-Na-Amure State University 27 Lenina St Komsomolsk-On-Amure681013 Russia

ISBN: (数字)9783031824944

ISBN: (纸本)9783031824937

The article is devoted to the development of a module for automating the planning of trajectories for painting aircraft fuselage elements. The scientific problem of the lack of modern control methods and technologies at aviation assembly plants, namely, in robotic areas for painting parts, is posed. And the applied problem of the inappropriate use of robotic painting due to lengthy readjustment due to the lack of automated adjustment of the robot’s control program is posed. The stages of development and implementation of module calculations are presented: the stage of processing a 3D model of a part to identify key vertices, generating points for the painting trajectory of one face, generating a complex of painting trajectories for the entire part, corrective transformation of the trajectory into the coordinate system of the central point of the robot manipulator tool. Based on the obtained trajectory, an automated synthesis of the robot's control program was implemented. The use of a control program was demonstrated and conclusions were drawn about the performance of the painting path planning module: it was empirically established that the robot performs the path according to the requirements. In the future, the module will be integrated into a hardware and software complex for managing and correcting control programs for painting aircraft parts. The use of a software and hardware complex will allow for robotic painting, improve the quality of the applied paint layer, reduce the production time of products and the paint consumption, and this will reduce the cost of products. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： robot programming

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Front Hair Styling robot System Using Path Planning for Root-Centric Strand Adjustment

Front Hair Styling Robot System Using Path Planning for Root...

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

作者： Kim, Soonhyo Kanazawa, Naoaki Hasegawa, Shun Kawaharazuka, Kento Okada, Kei The University of Tokyo JSK Laboratory Graduate School of Information Science and Technology 7-3-1 Hongo Bunkyo-ku Tokyo Japan

ISBN: (纸本)9798331531614

Hair styling is a crucial aspect of personal grooming, significantly influenced by the appearance of front hair. While brushing is commonly used both to detangle hair and for styling purposes, existing research primarily focuses on robotic systems for detangling hair, with limited exploration into robotic hair styling. This research presents a novel robotic system designed to automatically adjust front hairstyles, with an emphasis on path planning for root-centric strand adjustment. The system utilizes images to compare the current hair state with the desired target state through an orientation map of hair strands. By concentrating on the differences in hair orientation and specifically targeting adjustments at the root of each strand, the system performs detailed styling tasks. The path planning approach ensures effective alignment of the hairstyle with the target, and a closed-loop mechanism refines these adjustments to accurately evolve the hairstyle towards the desired outcome. Experimental results demonstrate that the proposed system achieves a high degree of similarity and consistency in front hair styling, showing promising results for automated, precise hairstyle adjustments. © 2025 IEEE.

关键词： robot programming

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-SLAM: A Visual SLAM Algorithm Based on Feature Mismatch Rejection and Map Construction

-SLAM: A Visual SLAM Algorithm Based on Feature Mismatch Rej...

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2024 IEEE International Conference on Cognitive Computing and Complex Data, ICCD 2024

作者： Wu, Xiao Zhu, Liucun Ma, Tao Wang, Nanxiang Chen, Sijie Beibu Gulf University Advanced Science and Technology Research Institute Qinzhou China

ISBN: (纸本)9798350352894

For the ORB-SLAM2 algorithm in the mis-matching rejection has the blindness of processing and lead to the low efficiency of the algorithm and can only build sparse point cloud map can not meet the robot real-time localisation and path planning problems, this paper introduces the Progressive Sample Consensus (PROSAC) to improve the mis-matching rejection in the ORB-SLAM2 and add a dense point cloud and octree map construction thread to compensate for the loss of map information. The PRO-SLAM algorithm pre-orders the feature points by evaluation function, selects high-quality feature points to solve the uni-responsive matrix, and eliminates the false matches based on the matrix solution and error threshold to achieve accurate position estimation and re-localisation of the camera. Finally, the dense point cloud and octree map are constructed according to the selected key frames. Compared with the sparse point cloud map, the newly constructed map can be directly used for robot navigation and path planning. The experimental results show that the improved algorithm reduces the mis-match rejection time by about 50%, Mismatch rejection is more efficient, the error of the system is smaller, and the average Rmse of APE is reduced by 45.45%, indicating that the algorithm in this paper has higher positioning accuracy and better robustness. © 2024 IEEE.

关键词： robot programming

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An Improved Diffusion Modeling Method with Environmental Priors for robot Path Planning

An Improved Diffusion Modeling Method with Environmental Pri...

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2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024

作者： Lu, Jushou Zhao, Wenzheng Wang, Yafei Hu, Chengwei Liu, Yinhua School of Mechanical Engineering University of Shanghai for Science and Technology Shanghai China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798350378658

The path planning algorithms for robots have consistently been a central focus in related research domains. In recent years, with the increasing complexity of industrial environments and the demand for enhanced production efficiency, higher requirements have been placed on the planning efficiency and adaptability of robots. However, traditional planning methods based on discrete point sampling suffer from low planning efficiency and insufficient adaptability to complex scenarios. To address these issues, this paper proposes an improved path planning framework based on the diffusion model. The denoising process is utilized to sample paths from the posterior path distribution constrained by the obstacle environment. This framework employs the Denoising Diffusion Probabilistic Model (DDPM) as the generative model and introduces a multi-head self-Attention mechanism to better learn the feature representation between obstacles and viable paths. To reduce sampling time in DDPM, a skip-layer sampling method is introduced. Experiments under various environments are conducted to validate the effectiveness of the algorithm. © 2024 IEEE.

关键词： robot programming

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Motion Planning of 3D Nonholonomic robots via Curvature-Constrained Vector Fields 63

Motion Planning of 3D Nonholonomic Robots via Curvature-Cons...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Qiao, Yike He, Xiaodong Li, Zhongkui Peking University State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Beijing100871 China University of Science and Technology Beijing School of Automation and Electrical Engineering Beijing100083 China

ISBN: (纸本)9798350316339

Vector-field-based methods are typical feedback planning algorithms, especially eligible for the motion planning of nonholonomic robots. Nevertheless, most existing vector fields (VF) do not account for the prevalent constraints on robot's kinematics. This paper addresses the motion planning problem for 3D nonholonomic robots with trajectories featuring upper bounded curvature. To this end, a curvature-constrained VF over R3 is proposed, whose integral curves guarantee an upperbound of curvature as well as an almost-global attraction region towards the desired position with a specified heading direction. Moreover, a control strategy is presented to determine the robot's control inputs subject to the curvature constraint. Under the designed control laws, the robot is guaranteed to track the VF while ensuring that the actual trajectory adheres to the curvature constraint. Finally, the efficacy of the presented motion planning algorithm is validated by numerical simulations. © 2024 IEEE.

关键词： robot programming

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Using iStar to Describe Human-robot Collaborations: Exploring Different Ways of Goal Model Usage 17

Using iStar to Describe Human-robot Collaborations: Explorin...

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17th International iStar Workshop, iStar 2024

作者： Jesus Raja, Jeshwitha Daun, Marian Center for Robotics Technical University of Applied Sciences Würzburg-Schweinfurt Schweinfurt Germany

In human-robot collaboration, humans and robots work closely together in a manufacturing process. To ensure proper and efficient execution of the manufacturing process while considering human safety and damages to the robot and the work product, advanced planning of the collaborative manufacturing process is important. Goal models can be used already in the early phases to specify and analyze human-robot collaborations. However, as model-based development along other established software engineering practices do not belong to the core of roboticists training, guidance is needed for the creation and usage of goal models for human-robot collaborations. In this paper, we investigate different ways how goal modeling can be used to specify human-robot collaborations to determine a set of best practices and recommendations in the future. To do so, we compare the results of two teams, who - after initial training on goal models - applied goal modeling to specify the same human-robot collaboration system. The outcome shows that multiple useful ways of using goal modeling for human-robot collaborations exist, that need to be considered in the future. © 2024 Copyright for this paper by its authors.

关键词： robot programming

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Path Planning and Control of a 6-DOF Manipulator for Freeform Surface Polishing Based-on a Point Cloud Model

Path Planning and Control of a 6-DOF Manipulator for Freefor...

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2024 International Conference on Advanced robotics and Intelligent Systems, ARIS 2024

作者： Tsai, Fu-Yu Song, Kai-Tai Institute of Electrical and Control Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University 1001 Ta Hsueh Road Hsinchu Taiwan

ISBN: (纸本)9798350362572

This paper presents a novel path generation method for robotic surface polishing based on point cloud data. In this method, an initial path is first planned to create waypoints via the point cloud. The method estimates the contact area to dynamically adjust initial path points to ensure uniform trajectory coverage on the surface. In this paper, the bilateral tool path generation (BTPG) algorithm is proposed based on a dual-thread strategy to expedite polishing path generation. Further, we introduce a method that generates smooth postures to enhance the stability of the robotic polishing pose. In this work, hybrid force/velocity control scheme is adopted to track polishing path and apply the assigned force on the workpiece freeform surface. Practical experimental results show that the proposed method achieves 95% improvement in path planning time and 85% in smoothness of the robot fourth joint's posture compared with the baseline slicing method. © 2024 IEEE.

关键词： robot programming

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