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Kirigami-inspired continuum soft arm with embedded sensing for non-destructive inspection and sorting

Science China Materials 2025年第2期68卷 552-560页

作者： Jinsui Xu Boyi Xu Honghao Yue Yifan Lu Zheping Wang Zongquan Deng Fei Yang State Key Laboratory of Robotics and System School of Mechatronics EngineeringHarbin Institute of TechnologyHarbin 150001China Wu Xianming School of Intelligent Engineering South China University of TechnologyGuangzhou 510641China

The sensing capabilities of a soft arm are ofparamount importance to its overall performance as they allow precise control of the soft arm and enhance its interactionwith the surrounding environment. However, the actuationand sensing of a soft arm are not typically integrated into amonolithic structure, which would impede the arm’s movement and restrict its performance and application scope. Toaddress this limitation, this study proposes an innovativemethod for the integrated design of actuator structures andsensing. The proposed method combines the art of kirigamiwith soft robotics technology. In the proposed method, sensorsare embedded in the form of kirigami structures into actuatorsusing laser cutting technology, achieving seamless integrationwith a soft arm. Compared to the traditional amanogawakirigami and fractal-cut kirigami structures, the proposedmiddle-cut kirigami (MCK) structure does not buckle duringstretching and exhibits superior tensile performance. Based onthe MCK structure, an advanced interdigitated capacitivesensor with a high degree of linearity, which can significantlyoutperform traditional kirigami sensors, is developed. Theexperimental results validate the effectiveness of the proposedsoft arm design in actual logistics sorting tasks, demonstratingthat it is capable of accurately sorting objects based on sensorsignals. In addition, the results indicate that the developedcontinuum soft arm and its embedded kirigami sensors havegreat potential in the field of logistics automation *** work provides a promising solution for high-precisionclosed-loop feedback control and environmental interaction ofsoft arms.

关键词： kirigami embedded sensing continuous soft arm non-destructive inspection

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Artificial Neural Networks for the Forward Kinematics of a SCARA Manipulator: A Comparative Study with Two Datasets

Artificial Neural Networks for the Forward Kinematics of a S...

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2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2024

作者： Bouzid, Rania Narayan, Jyotindra Gritli, Hassène Tunis Borj Cedria1164 Tunisia Indian Institute of Technology Guwahati Mechatronics and Robotics Laboratory Department of Mechanical Engineering Assam Guwahati781039 India Le Belvédère Tunis1002 Tunisia

ISBN: (纸本)9798350372229

In the field of robotics and automation, the precise determination of manipulator positions is a fundamental aspect with widespread applications. Despite the significance of analytical methods, solving the Forward Kinematics (FK) for Selective Compliance Assembly Robot Arm (SCARA) manipulator robots can be complex and computationally intensive. Our research introduces a method to address the FK problem for the four degrees of freedom (4-DoF) SCARA manipulator through Artificial Neural Networks (ANNs). We utilize two different generated datasets, one with a fixed step size and another one based on a sinusoidal signal, for training the ANNs. This choice of datasets allows us to assess the ANN s' generalization capabilities across a range of operating conditions. Thereafter, the study is planned to investigate the ANN's performance while employing three distinct training algorithms: Levenberg-Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG). Through a comprehensive comparison of the performance of different ANN models, different training algorithms, and the two adopted generated datasets, this study provides valuable insights into selecting the most optimal training configurations for the SCARA robot's FK solutions. We employ the Mean Squared Error (MSE) and the error histogram as two performance metrics to assess the accuracy of various ANNs. The results reveal that optimal MSE outcomes were obtained when utilizing a balanced architecture with three hidden layers in the analysis of the sinusoidal-signal-based datasets. © 2024 IEEE.

关键词： Artificial Neural Network Fixed-step- and sinusoidal-signal-based datasets Forward kinematics SCARA manipulator robot Training optimizers

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A Sensorless Speed Control of High-Speed BLDC Motor Using Variable Slope SMO

A Sensorless Speed Control of High-Speed BLDC Motor Using Va...

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作者： Ok, Sangjae Xu, Zhenyao Lee, Dong-Hee Department of Mechatronics Engineering Kyungsung University Busan48434 Korea Republic of State Key Laboratory of Robotics Shenyang Institute of Automation The Chinese Academy of Sciences Shenyang110016 China

Low-power and high-speed BLDC(Brushless DC) motor is widely used in vacuum cleaners. This paper presents a sensorless speed control scheme for a high-speed BLDC motor of a hand-stick vacuum cleaner using a variable slope sliding mode observer(SMO). The SMO using the signum function is very effective for the sensorless estimation of the BLDC motor. However, the chattering effect on the slide surface from the signum function decreases the sensorless performance in the wide speed range. The sigmoid function instead of the signum function can reduce the chattering effect. However, the convergence is inversely proportional to the reduced chattering effect. In order to reduce the chattering effect and keep the proper convergence performance, the proposed method uses a variable acceleration slope of the sigmoid function. In the low-speed range, the acceleration slope of SMO is decreased to reduce the chattering. And, it is increased to improve the convergence in the high-speed region. The acceleration slope of the sigmoid function is designed as a function of the estimated speed to keep the constant convergence with reduced chattering in the sensorless speed and position estimation. In order to verify the proposed sensorless control scheme, 115 krpm speed 540W BLDC motor for a vacuum cleaner is tested with various SMO methods. In the experimental results, the proposed method shows better sensorless speed control performance in the wide speed range. © 2023 IEEE.

关键词： Sensorless control

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Comparison of UAVs' Trajectories for Sea Surface Survey within Fish Search

Comparison of UAVs' Trajectories for Sea Surface Survey with...

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Ocean Studies (ICOS), International Conference on

作者： Filipp M. Belchenko Ivan L. Ermolov Georgij N. Nagajcev Artem N. Sukhanov Pavel P. Ostrikov Laboratory of Robotics and Mechatronics Institute for Problems in Mechanics of the Russian Academy of Sciences Moscow Russian Federation

ISBN: (数字)9798331532307

ISBN: (纸本)9798331532314

Within this paper we suggest to use UAVs for fishes' search. We investigate existing methods used in this area. Basing on selected photogravimetry method we suggest UAVs trajectory for motion over the sea surface. Some calculations for various trajectories lengths at various altitudes. Scenarios of using these trajectories are discussed.

关键词： Water Surveys Visualization Sea surface Color Visual systems Search problems Throughput Trajectory Marine animals

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Exoskeletal Development of a Hand Complex for Rehabilitation Activities

Exoskeletal Development of a Hand Complex for Rehabilitation...

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2021 International Conference on Intelligent Technologies, CONIT 2021

作者： Mathew, Meby Arun, M. Francis, Rodrigues Neil Sudheer, A.P. National Institue of Technology Mechatronics/Robotics Laboratory Calicut India

ISBN: (纸本)9781728185835

Hand exoskeletons are becoming inevitable in the journey of rehabilitation robotics. The practical considerations of human interactions are always constraining the developments in hand exoskeletons. In this paper, the design, kinematic modeling, and static structural analysis are carried out to synthesis the mechanism for a hand exoskeleton. The minimum grasping capacity for the index finger is analyzed and found to be in the range of the literature. This paper also finally presents the prototype fabrication of a lightweight and robust hand exoskeleton. © 2021 IEEE.

关键词： Exoskeleton (robotics)

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Fast and Modular Whole-Body Lagrangian Dynamics of Legged Robots with Changing Morphology

arXiv

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arXiv 2025年

作者： Farghdani, Sahand Abdelrahman, Omar Chhabra, Robin Autonomous Space Robotics and Mechatronics Laboratory Carleton University OttawaON Canada Mechanical Industrial and Mechatronics Engineering Department Toronto Metropolitan University TorontoON Canada

Fast and modular modeling of multi-legged robots (MLRs) is essential for resilient control, particularly under significant morphological changes caused by mechanical damage. Conventional fixed-structure models, often developed with simplifying assumptions for nominal gaits, lack the flexibility to adapt to such scenarios. To address this, we propose a fast modular whole-body modeling framework using Boltzmann-Hamel equations and screw theory, in which each leg’s dynamics is modeled independently and assembled based on the current robot morphology. This singularity-free, closed-form formulation enables efficient design of model-based controllers and damage identification algorithms. Its modularity allows autonomous adaptation to various damage configurations without manual rederivation or retraining of neural networks. We validate the proposed framework using a custom simulation engine that integrates contact dynamics, a gait generator, and local leg control. Comparative simulations against hardware tests on a hexapod robot with multiple leg damage confirm the model’s accuracy and adaptability. Additionally, runtime analyses reveal that the proposed model is approximately three times faster than real-time, making it suitable for real-time applications in damage identification and recovery. Copyright © 2025, The Authors. All rights reserved.

关键词： Modular robots

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Design and Simulation for an Indoor Inspection Robot 1

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2nd International Scientific Conference on Innovation in Engineering, ICIE 2022

作者： Ottaviano, Erika Figliolini, Giorgio LARM Laboratory of Robotics and Mechatronics University of Cassino and Southern Lazio via Di Biasio 43 FR Cassino03043 Italy

ISBN: (数字)9783031093852

ISBN: (纸本)9783031093845

In this paper, we propose the design and simulation for an inspection robot that can be effective in indoor or outdoor surveys. robotics are traditionally employed wherever human limits are achieved. In the context of inspection of structures and infrastructure, automatic or semiautomatic solutions can be used for monitoring purposes for securing the access to the manholes and pipes. Indeed, the proposed robot can be effective for the survey of indoor sites, which are difficult or almost impossible to access, and for which tele-operated survey by mobile robots can be a solution. As an illustrative case of study, we refer to the inspection of box girder bridges, in which obstacles are represented by steps, longitudinal stiffeners, and debris. In this paper, we propose the design and simulation for a hybrid rover developed for indoor and outdoor inspections, and equipped with suitable sensors to detect defects, such as cracks, or corrosion, according to the nature of the inspected elements. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mobile robots

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A deep learning-based model for automated STN localization using local field potentials in Parkinson’s disease

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Soft Computing 2025年第4期29卷 2343-2362页

作者： Hosny, Mohamed Naeem, Mohamed A. Zhu, Minwei Gao, Wenpeng Elshenhab, Ahmed M. Fu, Yili Department of Electrical Engineering Benha Faculty of Engineering Benha University Benha Egypt State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150080 China Department of Mechatronics and Robotics Engineering Faculty of Engineering South Valley University Qena Egypt First Affiliated Hospital Harbin Medical University Harbin150001 China School of Life Science and Technology Harbin Institute of Technology Harbin150080 China Department of Mathematics Faculty of Science Mansoura University Mansoura35516 Egypt

Accurate identification of the subthalamic nucleus (STN) borders is time-consuming, relying heavily on the neurosurgeon expertise in manually interpreting the electrophysiological signals. Local field potentials (LFPs) have garnered imperative attention due to their strong correlation with the STN. However, existing detection models often face challenges with high computational complexity, hyperparameter optimization and lack of explainability, making them unreliable for clinicians. Therefore, this study introduces an explanatory framework using convolutional neural networks (CNN) for detecting the STN region from LFPs. Continuous wavelet transform is employed to convert LFPs signals into scalogram images, which are then processed by sixteen CNN models. We evaluated our framework by examining the impact of various limiting factors on the classification performance, including model size, learning rate (LR), optimizers and data scaling. Deep features are extracted from the top-performing CNN architectures to capture rich representations of the scalograms. These features are then fused and classified using k-nearest neighbour algorithm. Gradient-weighted class activation mapping is used to explain the decisions made by the proposed model. Our approach achieved an accuracy of 99.61%, outperforming individual CNN models for STN localization. The experimental results revealed that CNN models, embedded with additional hyperparameters and layers, generally outperformed smaller models. Besides, low LR significantly enhanced the performance compared to high LR. Moreover, features extracted from untuned networks produced lower performance than tuned networks. The proposed system could revolutionize deep brain stimulation surgery by increasing efficiency and reducing reliance on clinician expertise for STN detection. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Wavelet transforms

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A WLS-Based Step-by-Step Identification Method for Industrial Robot Dynamics Parameters

A WLS-Based Step-by-Step Identification Method for Industria...

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International Conference on Control, Automation and robotics (ICCAR)

作者： Qianjiang Wang Mingxiu Kong Chuancheng Bian Hao Hong State Key Laboratory of Robotics and System School of Mechatronics Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350373172

ISBN: (纸本)9798350373189

In order to improve the accuracy of robot dynamics parameter identification, this paper designs a step-by-step identification method based on weighted least squares. The robot dynamics model is first linearized to obtain the minimum parameter set. Subsequently, the friction model is built separately and experiments are designed to recognize the joint friction parameters first. Based on this, the excitation trajectory of finite term Fourier series is designed and optimized and data are collected. The joint moments obtained from the difference between the overall experimentally collected moments and the calculated friction moments are used to obtain the complete robot dynamics parameters based on weighted least squares identification. Comparison of the designed overall identification experiments shows that the total moment residuals of this method are reduced by 35.52% compared with the one-time identification method, which proves the effectiveness of this method.

关键词： Parameter estimation Accuracy Automation Service robots Friction Industrial robots Kinetic theory

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Wheeled Mobile Robots on Rough Terrains as Stochastic Nonholonomic Systems

Wheeled Mobile Robots on Rough Terrains as Stochastic Nonhol...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Vaughn Gzenda Robin Chhabra Mechanical and Aerospace Engineering Department Autonomous Space Robotics and Mechatronics Laboratory Carleton University Ottawa ON Canada

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In this paper, we investigate the motion of wheeled mobile robots on rough terrains modeled as noisy nonholonomic constraints. Such constraints are the natural extension of ideal nonholonomic constraints when the Stratonovich process is directly introduced in the constraint equations. The resulting stochastic model can capture motion on rough surfaces, random deformation in the wheel-ground contact, or stochastic loss/gain of traction. We study a differential robot with ideal noisy and affine noisy constraints, where each case models a certain aspect of motion on rough terrains. We then investigate their corresponding stochastic dynamics and the propagation of mean and covariance through Monte-Carlo simulations. The proposed model for roving rough terrains has the potential to serve as the stochastic model employed in model-based motion planning, pose estimation, and control of rover systems. The main challenge will be dealing with the nonlinear appearance of the noise and its feedback in the equations of motion.

关键词： Deformation Noise Dynamics Stochastic processes Mathematical models Surface roughness Rough surfaces Noise measurement Mobile robots Surface treatment

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