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第34届中国控制与决策会议

作者： Fang Li Fengshan Zou Zhenjun Du Faculty of Robots Science and Engineering Northeastern University SIASUN Robot & Automation CO. Ltd

Normally,SLAM algorithms are based on the assumption of static *** quality of lidar input directly affects the final performance of SLAM algorithm during this *** important factor that affects the input quality is the dynamic objects in the ***,how to segment dynamic objects from the 3 D point cloud to improve the quality of input is a question worth paying attention *** contrast to traditional methods,we use convolutional neural network to segment points on moving ***'s achallenge to improve the segmentation accuracy with a low amount of computation effort by carefully designing the network structure to control the number of parameters of the network.A method was proposed to convert the 3 D point cloud into a range image and combine the residual information as the input of CNN and the multi-hierarchical feature extraction module was used to improve the accuracy of the existing *** focus on segmenting moving objects rather than dividing the points into their semantic *** have shown that the proposed method can effectively improve the accuracy of dynamic object segmentation while keeping the neural network model lightweight.

关键词： 3D Lidar Point Cloud Dynamic Object Segmentation Multi-Hierarchical Feature Extraction

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Automatic Stiffness Measurement of Small Objects Using an Integrated System of Simultaneous Multi-scale Observation and Two-Directional Force Measurement

Automatic Stiffness Measurement of Small Objects Using an In...

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IEEE International Conference on Cyborg and Bionic Systems (CBS)

作者： Masaru Kojima Ryo Yoshikawa Yasushi Mae Tatsuo Arai Science Graduate School of Engineering Science Osaka University Toyonaka Osaka Japan Department of Mechanical Engineering Faculty of Engineering Science Kansai University Suita Osaka Japan Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Center for Neuroscience and Biomedical Engineering The University of Electro-Communications Chofu Tokyo Japan

ISBN: (数字)9798350388039

ISBN: (纸本)9798350388046

Recently, the field of life sciences has witnessed significant advancements, leading to the exploration of various cell characteristics to evaluate cellular behavior. Among these characteristics, cell stiffness has garnered considerable attention. It is widely acknowledged that cell stiffness undergoes changes based on the cell’s physiological state, rendering stiffness measurement a critical parameter in cell evaluation. However, the extensive research into cell stiffness has been hindered by the challenges associated with manipulating micron-scale cells and measuring nano-scale forces. Previous studies have proposed a cell stiffness measurement system utilizing a two-fingered microhand equipped with a micro force sensor. Nonetheless, this approach required manual manipulation of the target object, resulting in potential errors in stiffness measurement. Additionally, manual manipulation restricted the workspace, limiting its applicability. To address these limitations, this paper introduces an automated stiffness measurement technique that integrates force data and image data. Furthermore, a multi-scale simultaneous observation system is presented, combining optical systems from two microscopes with different magnification levels.

关键词： Force measurement Optical microscopy Microscopy Measurement uncertainty Measurement techniques Rendering (computer graphics) Optical imaging Physiology Force sensors Optical sensors

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RMS: Redundancy-Minimizing Point Cloud Sampling for Real-Time Pose Estimation

arXiv

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arXiv 2023年

作者： Petracek, Pavel Alexis, Kostas Saska, Martin The Department of Cybernetics Faculty of Electrical Engineering Czech Technical University Czech Republic The Autonomous Robots Lab Norwegian University of Science and Technology O. S. Bragstads Plass 2D Trondheim7034 Norway

The typical point cloud sampling methods used in state estimation for mobile robots preserve a high level of point redundancy. This redundancy unnecessarily slows down the estimation pipeline and may cause drift under real-time constraints. Such undue latency becomes a bottleneck for resource-constrained robots (especially UAVs), requiring minimal delay for agile and accurate operation. We propose a novel, deterministic, uninformed, and single-parameter point cloud sampling method named RMS that minimizes redundancy within a 3D point cloud. In contrast to the state of the art, RMS balances the translation-space observability by leveraging the fact that linear and planar surfaces inherently exhibit high redundancy propagated into iterative estimation pipelines. We define the concept of gradient flow, quantifying the local surface underlying a point. We also show that maximizing the entropy of the gradient flow minimizes point redundancy for robot ego-motion estimation. We integrate RMS into the point-based KISS-ICP and feature-based LOAM odometry pipelines and evaluate experimentally on KITTI, Hilti-Oxford, and custom datasets from multirotor UAVs. The experiments demonstrate that RMS outperforms state-of-the-art methods in speed, compression, and accuracy in well-conditioned as well as in geometrically-degenerated settings. Copyright © 2023, The Authors. All rights reserved.

关键词： Redundancy

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Context-Based Meta Reinforcement Learning for Robust and Adaptable Peg-in-Hole Assembly Tasks

arXiv

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arXiv 2024年

作者： Shokry, Ahmed Gomaa, Walid Zaenker, Tobias Dawood, Murad Menon, Rohit Maged, Shady A. Awad, Mohammed I. Bennewitz, Maren Humanoid Robots Lab Center for Robotics University of Bonn Germany Lamarr Institute for Machine Learning and Artificial Intelligence Bonn Germany Cyber Physical Systems Lab Egypt Japan University of Science and Technology Alexandria Egypt Faculty of Engineering Alexandria University Alexandria Egypt Mechatronics Department Ain Shams University Cairo Egypt

Autonomous assembly is an essential capability for industrial and service robots, with Peg-in-Hole (PiH) insertion being one of the core tasks. However, PiH assembly in unknown environments is still challenging due to uncertainty in task parameters, such as the hole position and orientation, resulting from sensor noise. Although context-based meta reinforcement learning (RL) methods have been previously presented to adapt to unknown task parameters in PiH assembly tasks, the performance depends on a sample-inefficient procedure or human demonstrations. Thus, to enhance the applicability of meta RL in real-world PiH assembly tasks, we propose to train the agent to use information from the robot’s forward kinematics and an uncalibrated camera. Furthermore, we improve the performance by efficiently adapting the meta-trained agent to use data from force/torque sensor. Finally, we propose an adaptation procedure for out-of-distribution tasks whose parameters are different from the training tasks. Experiments on simulated and real robots prove that our modifications enhance the sample efficiency during meta training, real-world adaptation performance, and generalization of the context-based meta RL agent in PiH assembly tasks compared to previous approaches. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Design and Analysis of the Comb Gripper of the Saffron Flowers Harvesting Robot

Design and Analysis of the Comb Gripper of the Saffron Flowe...

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

作者： Shima Shademani Shahriyar Kouravand Payam Zarafshan Khalil Aalipour Amir Ghalamzan Esfahani Department of Agro-Technology College of Aburaihan University of Tehran Teltran Iran Department of Mechatronics Engineering AGRicultural INtelligent Systems (AGRINS) Faculty of New Sciences and Technologies University of Tehran Teltran Iran Department of Mechatronics Engineering Advanced Service Robots (ASR) Laboratory Faculty of New Sciences and Technologies University of Tehran Teltran Iran School of Computer Science University of Lincoln United Kingdom

Saffron is one of the most valuable spices in the world, whose origin is attributed to Iran. Iran produces about 90% of the world's saffron annually, however, the harvesting of this product in Iran is mostly done manually. Manual harvest of saffron brings problems. Decreasing the quality of saffron and contamination of saffron with microorganisms are among the problems that arise during manual harvesting. For this purpose, a gripper is recommended for harvesting saffron flowers. One of the special features of the saffron plant is that several flowers may come out from each corm at different time intervals, for this reason, the proposed gripper uses the plucking method to harvest the flowers and separate flowers from the stem so that the next flowers can grow easily. Design, simulation, and control of the gripper have been conducted using conventional software such as SOLIDWORKS, ADAMS, and MATLAB.

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Mechanism Design, Kinematics and Hydrodynamics Simulation of a Novel Rocker Driving Bionic Robot

Mechanism Design, Kinematics and Hydrodynamics Simulation of...

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IEEE International Conference on Robotics and Biomimetics

作者： Zhongyin Zhang Liwei Shi Shuxiang Guo Pengxiao Bao Key Laboratory of Convergence Medical Engineering System and Healthcare Technology the Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology Beijing China Key Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing Institute of Technology Beijing China Faculty of Engineering Kagawa University Kagawa Japan

ISBN: (纸本)9781665405362

With the gradual development of the Marine field, the underwater robot has gradually entered people's perspective. However, the structure and control of the current amphibious robot is too complex, and most of them need to switch two sets of structures to adapt to the amphibious environment. Therefore, a simple and reliable robot that can adapt to two environments with seven sets of structures is urgently needed. Based on the undulation motion principle of ray's pectoral fin, the undulation mechanism driven by 6 groups of crank rocker mechanism on both sides is designed, and the rocker mechanism is connected by rubber material to form the fin driven by rocker. The structure modeling and kinematics simulation of the robot are carried out, and it is confirmed that the mechanism of the ray can move effectively and the fin can realize regular fluctuation, which verifies the feasibility of the bionic ray underwater robot.

关键词： Autonomous underwater vehicles Analytical models Biological system modeling Fluid dynamics Kinematics Switches Production

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Correction to: Scanning strategies for the 316L part with lattice structures fabricated by selective laser melting

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The International Journal of Advanced Manufacturing Technology 2024年第7期133卷 3179-3179页

作者： Huang, Renkai Wu, Yunshu Huang, Linqing Pan, Chunrong Sun, Yuchun Tian, Sukun Wang, Dongsheng Yang, Youwen School of Mechanical and Electrical Engineering Jiangxi University of Science and Technology Jiangxi China Center of Digital Dentistry Faculty of Prosthodontics Peking University School and Hospital of Stomatology Beijing China Key Laboratory of Construction Hydraulic Robots of Anhui Higher Education Institutes Tongling University Tongling China

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Robust RGB-D Camera and IMU Fusion-based Cooperative and Relative Close-range Localization for Multiple Turtle-inspired Amphibious Spherical robots

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Journal of Bionic engineering 2019年第3期16卷 442-454页

作者： Huiming Xing Liwei Shi Kun Tang Shuxiang Guo Xihuan Hou Yu Liu Huikang Liu Yao Hu Key Laboratory of Convergence Medical Engineering System and Healthcare Technology the Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology Beijing 100081 China Key Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing Institute of Technology Beijing 100081 China Faculty of Engineering Kagawa University 2217-20 Hayashicho Takamatsu Kagawa 761-0396 Japan

In the narrow, submarine, unstructured environment, the present localization approaches, such as GPS measurement, dead?rcckoning, acoustic positioning, artificial landmarks-based method, are hard to be used for multiple small-scale underwater robots. Therefore, this paper proposes a novel RGB-D camera and Inertial Measurement Unit (IMU) fusion-based cooperative and relative close-range localization approach for special environments, such as underwater caves. Owing to the rotation movement with zero-radius, the cooperative localization of Multiple Turtle-inspired Amphibious Spherical Robot (MTASRs) is realized. Firstly, we present an efficient Histogram of Oriented Gradient (HOG) and Color Names (CNs) fusion feature extracted from color images ofTASRs. Then, by training Support Vector Machine (SVM) classifier with this fusion feature, an automatic recognition method of TASRs is developed. Secondly, RGB-D camerabased measurement model is obtained by the depth map In order to realize the cooperative and relative close-range localization of MTASRs, the MTASRs model is established with RGB-D camera and IMU. Finally, the depth measurement in water is corrected and the efficiency of RGB-D camera for underwater application is validated. Then experiments of our proposed localization method with three robots were conducted and the results verified the feasibility of the proposed method for MTASRs.

关键词： vision localization bio-inspired robots RGB-D camera histogram of oriented gradient and color names fusion feature Co operative and Relative Localization (CRL)

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A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI

arXiv

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arXiv 2025年

作者： Wong, Lik Hang Kenny Kang, Xueyang Bai, Kaixin Zhang, Jianwei Department of Computer Science City University of Hong Kong Hong Kong Department of Informatics Universität Hamburg Hamburg Germany Faculty of Engineering and Information Technology The University of Melbourne Parkville Australia Technical University of Munich Munich Germany KU Leuven Leuven Belgium Department of Informatics Universität Hamburg Hamburg Germany and Agile Robots Munich Germany

Navigation and manipulation are core capabilities in Embodied AI, yet training agents with these capabilities in the real world faces high costs and time complexity. Therefore, sim-to-real transfer has emerged as a key approach, yet the sim-to-real gap persists. This survey examines how physics simulators address this gap by analyzing their properties overlooked in previous surveys. We also analyze their features for navigation and manipulation tasks, along with hardware requirements. Additionally, we offer a resource with benchmark datasets, metrics, simulation platforms, and cutting-edge methods—such as world models and geometric equivariance—to help researchers select suitable tools while accounting for hardware constraints. Copyright © 2025, The Authors. All rights reserved.

关键词： robots

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Improved small gain conditions for input-to-state stability with respect to measurement functions: Discrete time networked system

Improved small gain conditions for input-to-state stability ...

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IEEE Conference on Decision and Control

作者： Yuanqiu Mo Changbin Yu Soura Dasgupta Westlake Institute for Advanced Study Westlake University Hangzhou China College of Artificial Intelligence and Big Data Shandong First Medical University & Shandong Academy of Medical Sciences Jinan China Institute for Intelligent Robots Fudan University Shanghai China Shandong Computer Science Center Shandong Provincial Key Laboratory of Computer Networks China Faculty of Engineering & the Built Environment University of Johannes-Burg Johannesburg South Africa University of Iowa Iowa City Iowa USA

ISBN: (纸本)9781665436601

In this paper we study input-to-state stability with respect to measurement functions for discrete time networked systems. In such a networked system, the trajectory of each subsystem is affected by another in each time step, and this constraining system may change from step to step. We derive small gain conditions of input-to-state stability with respect to measurement functions for this type of discrete time networked system relying on the construction of dissipative-form finite time Lyapunov function. These conditions loosen those presented in [1] and [2]. Finally, we demonstrate the applicability of our results by applying them to the stability analysis of a distributed graph algorithm which does not satisfy the conditions of [1] and [2].

关键词： Network topology Conferences Gain measurement Stability analysis Time measurement Trajectory Topology

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