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Field robotics 2025年 2卷 1721-1753页

作者： Riccardo Giubilato Cedric Le Gentil Mallikarjuna Vayugundla Martin J. Schuster Teresa Vidal-Calleja Rudolph Triebel Institute of Robotics and Mechatronics German Aerospace Center (DLR) Centre for Autonomous Systems University of Technology Sydney

Simultaneous Localization and Mapping (SLAM) techniques play a key role towards long-term autonomy of mobile robots due to the ability to correct localization errors and produce consistent maps of an environment over time. Contrarily to urban or man-made environments, where the presence of unique objects and structures offer unique cues for localization, the apperance of unstructured natural environments is often ambiguous and self-similar, hindering the performances of loop closure detection. In this paper, we present an approach to improve the robustness of place recognition in the context of a submap-based stereo SLAM based on Gaussian Process Gradient Maps (GPGMaps). GPGMaps embed a continuous representation of the gradients of the local terrain elevation by means of Gaussian Process regression and Structured Kernel Interpolation, given solely noisy elevation measurements. We leverage the imagelike structure of GPGMaps to detect loop closures using traditional visual features and Bag of Words. GPGMap matching is performed as an SE(2) alignment to establish loop closure constraints within a pose graph. We evaluate the proposed pipeline on a variety of datasets recorded on Mt. Etna, Sicily and in the Morocco desert, respectively Moon- and Mars-like environments, and we compare the localization performances with state-of-the-art approaches for visual SLAM and visual loop closure detection.

关键词： Simultaneous localization and mapping Robots Location awareness Visualization Robot sensing systems Gaussian processes Cameras mechatronics Feature extraction Deserts

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Unified Modelling Language Application for Laparoscopic Instrument Design

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International Journal Bioautomation 2024年第3期28卷 117-132页

作者： Ivanova, Veronika Boneva, Ani Vasilev, Plamen Robotized and Mechatronics Intelligent Systems Institute of Robotics Bulgarian Academy of Sciences Sofia Bulgaria Communication Systems and Services Institute of Information and Communication Technologies Bulgarian Academy of Science Sofia Bulgaria Industrial Automation University of Chemical Technologies and Metallurgy Sofia Bulgaria

Laparoscopic surgery is a very popular medical intervention for the diagnosis and treatment of some abdominal problems and diseases. Compared with open surgery, laparoscopic procedures reduce patient trauma and recovery time. Still, at the same time, the surgeon’s dexterity is reduced as a result of the operation specificity and instrument construction. Correct behaviour of every device and instrument during its activities is an important condition for the proper operation of the whole system. The main purpose of this work is to model the operating behaviour of an instrument-organ interaction in an environment which is similar to the real one. The ultimate target of this study is focused on the development of a functionally operating model of a laparoscopic executive instrument for robots with improved engineering characteristics. To achieve the goals, the following main tasks are decided: i) Unified Modelling Language is applied to demonstrate the operating behaviour of a device in real-time. UseCase diagram and 3 Activity diagrams have been developed;ii) an original model of an instrument with 4 degrees of freedom for robot-assisted surgery is designed. In contrast to EndoWrist technology created by Intuitive Surgical Incorporation, USA for DaVinci instruments (with 3 orthogonal rotations), we offered other construction decisions. The designed instrument provides a kinematic structure with a combination of perpendicular and parallel rotations ((Formula presented)) which avoids additional rolls and allows obtaining the optimal working area of this instrument. This study is a continuation of previous work in the surgical robotics area. © (2024), (Institute of Biophysics and Biomedical Engineering). All rights reserved.

关键词： Unified Modeling Language

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SURROGATE MODELS FOR COMPLIANT JOINTS IN PROGRAMMABLE STRUCTURES

SURROGATE MODELS FOR COMPLIANT JOINTS IN PROGRAMMABLE STRUCT...

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ASME 2024 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2024

作者： Pieber, Michael Zhang, Zhaowei Manzl, Peter Gerstmayr, Johannes University of Innsbruck Department of Mechatronics Innsbruck6020 Austria State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Liaoning Shenyang110016 China

ISBN: (纸本)9780791888438

This work focuses on compliant joints in autonomous cells. These cells are able to preserve the underlying geometry of a mesh and enable self-reconfiguration through the utilization of six-bar linkages. The six-bar linkages, essential for maintaining triangular mesh geometry, are realized as 3D-printable compliant mechanisms. However, challenges arise from compliance in the hinges and deviation from the desired center of rotation which results in positioning errors. To address these issues, a surrogate model which is derived from beam elements, is used to predict positioning errors during self-reconfiguration. Finally, these errors are corrected by solving the inverse kinematics of a hyper-redundant manipulator. Our study illustrates the benefits of utilizing a surrogate model, which reduces computation time compared to beam elements. For the first time, we successfully correct positioning errors within a system of cells. Copyright © 2024 by ASME.

关键词： Inverse kinematics

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Unknown Object Grasping for Assistive robotics

arXiv

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arXiv 2024年

作者： Miller, Elle Durner, Maximilian Humt, Matthias Quere, Gabriel Boerdijk, Wout Sundaram, Ashok M. Stulp, Freek Vogel, Jörn The DLR Institute of Robotics and Mechatronics The University of Edinburgh United Kingdom

We propose a novel pipeline for unknown object grasping in shared robotic autonomy scenarios. State-of-the-art methods for fully autonomous scenarios are typically learning-based approaches optimised for a specific end-effector, that generate grasp poses directly from sensor input. In the domain of assistive robotics, we seek instead to utilise the user’s cognitive abilities for enhanced satisfaction, grasping performance, and alignment with their high level task-specific goals. Given a pair of stereo images, we perform unknown object instance segmentation and generate a 3D reconstruction of the object of interest. In shared control, the user then guides the robot end-effector across a virtual hemisphere centered around the object to their desired approach direction. A physics-based grasp planner finds the most stable local grasp on the reconstruction, and finally the user is guided by shared control to this grasp. In experiments on the DLR EDAN platform, we report a grasp success rate of 87% for 10 unknown objects, and demonstrate the method’s capability to grasp objects in structured clutter and from shelves. Copyright © 2024, The Authors. All rights reserved.

关键词： End effectors

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A Data-Centric Approach for Object Recognition in Hemispherical Camera Images 49

A Data-Centric Approach for Object Recognition in Hemispheri...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Balgabekova, Zarema Alaran, Muslim Varol, Huseyin Atakan Inst. of Smart Systems and Ai Nazarbayev University Astana Kazakhstan Nazarbayev University Dept. of Robotics and Mechatronics Astana Kazakhstan

ISBN: (纸本)9798350331820

Object recognition is a machine learning problem that involves the correct classification and localization of objects in an image. Object recognition has found wide applications in Industry 4.0, surveillance, and autonomous driving. Prominent datasets such as Pascal VOC, ImageNet, and MS COCO have further spurred advances in object recognition. However, the images in these datasets were captured using ordinary perspective lenses. Unlike ordinary cameras, fisheye or hemispherical cameras have a wide FoV reaching 180°. Due to this property, they can acquire wide panoramic images, thus, capturing more objects in a scene as compared to ordinary perspective lenses. In this work, we provide the first benchmark testing dataset of real fisheye images containing commonly-occurring objects in the human environment obtained with hemispherical cameras. The dataset comprises 1,000 images containing 39 classes with a total number of 14,218 object instances. We trained the YOLOv7 model on the original MS COCO and transformed FisheyeCOCO datasets and tested the obtained models with our dataset. The results indicate that training the model on the combination of original and transformed datasets improves the performance by 2.5% compared to using these datasets separately. © 2023 IEEE.

关键词： Cameras

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Advanced Handheld Micro-Surgical System using an Hall Sensor and a Magnet Trocar for Retinal Microsurgery

Advanced Handheld Micro-Surgical System using an Hall Sensor...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Myung Ho Lee Jintaek Im Cheol Song Department of Robotics and Mechatronics Engineering DGIST Daegu South Korea

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Diseases affecting the retina, such as retinal detachment, diabetic retinopathy, and macular degeneration, are significant contributors to blindness globally, with a substantial risk of vision loss among those afflicted. Surgical treatment of these conditions is complex due to the delicate nature of retinal tissue and the challenges posed by involuntary hand movements. While existing methods aim to compensate for hand tremors using sensor-based systems, they are hindered by limitations in accurately tracking retinal surface movement during surgery, particularly in response to patient movements under anesthesia. To address these issues, this study proposes a novel handheld micro-surgical tool equipped with a 1-degree of freedom (DOF) mechanism and a 3-axis Hall sensor to mitigate physiological hand tremors effectively. By utilizing magnetic flux density measurements, the tool can pinpoint the position of a magnet embedded within the surgical instrument, enabling precise tremor compensation without reliance on a global coordinate system. The design incorporates a piezoelectric (PZT) linear actuator and a Hall sensor for compactness and sensitivity. Optimization of the magnet’s dimensions through simulation ensures optimal sensor performance. Experimental validation using artificial and ex-vivo porcine eye models demonstrates the tool’s effectiveness in reducing hand tremors, suggesting potential enhancements in the safety and accuracy of retinal surgeries. For the desired positions from 4000 µm to 1000 µm, the RMS error of the synthetic eye model and porcine eye decreased from 71.10 µm to 33.27 µm and 71.36 µm to 33.39 µm, respectively.

关键词： Hands Sensitivity Tracking Position measurement Retina Robot sensing systems Physiology Safety Surface treatment Optimization

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Micro-Seismic Event Detection using statistical feature extraction and machine learning techniques 7

Micro-Seismic Event Detection using statistical feature extr...

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7th IEEE International conference for Convergence in Technology, I2CT 2022

作者： Chakraborty, Mainak Das, Manisha Aruchamy, Srinivasan Indian Institute of Engineering Science and Technology School of Mechatronics and Robotics Shibpur India CSIR- Cmeri Robotics and Automation Group Durgapur India

ISBN: (纸本)9781665421683

In this paper, we propose a novel methodology for micro-seismic event detection using multiple statistical feature extraction and machine learning techniques. The method is based on amplitude thresholding and is grounded on the idea, that each relevant seismic event crosses a particular threshold value. We have created a unique dataset of movement, hammering and no-movement using off-the-shelve geophones and 16-bit analog to digital converter. The data is sampled at 10000Hz. Each recorded dataset is of duration 2 min. The data recorded is passed through amplitude thresholding method. Multiple statistical features like root mean square, standard deviation, variance, minimum value and maximum value are extracted from the dataset in both time and frequency domain. k-fold cross validation is done to obtain validation accuracy. We have explored various machine learning algorithms and the results are discussed here. Among all classifiers, Random Forest algorithm achieves the overall highest accuracy of 92.76%. © 2022 IEEE.

关键词： Decision trees

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Spectral and Morphological Classification of Celestial Objects using Physics Informed Machine Learning

Spectral and Morphological Classification of Celestial Objec...

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robotics, Automation, Artificial-intelligence and Internet-of-Things (RAAICON), 2019 IEEE International Conference on

作者： Md Fairuz Siddiquee Md Mehedi Hasan Department of Robotics and Mechatronics Engineering University of Dhaka Dhaka Bangladesh

ISBN: (数字)9798331534400

ISBN: (纸本)9798331534417

The classification of celestial objects has traditionally relied on spectral analysis, which involves identifying unique patterns in the light emitted or absorbed by the objects. In this study, we present a novel approach to categorizing celestial objects based on their spectral properties and morphological structures, leveraging physics-informed machine learning (PIML) techniques to enhance the classification accuracy and efficiency. In the spectral analysis, using Sloan Digital Sky Survey (SDSS) dataset, we classified stars, galaxies, and quasars, focusing on redshift and near-infrared values with i and z filters. Our analysis employed three machine learning models (K-Neighbors, SVM, Random Forest), and the performances were verified to be resilient applying hyperparameter tuning and cross-validation. The best-performing model, Random Forest Classifier, achieved 98% accuracy. In the morphological analysis, the YOLO v5 model was utilized on a customized dataset of astronomical images to further classify the Galaxy Class into five distinct categories and the YOLOv5 model detected those with an average precision of 92.6% and recall of 68.9%. In addition, the interpretability of the model is enhanced by the incorporation of physical knowledge, allowing astronomers to gain deeper insights into the underlying processes. Integrating physical knowledge into these ML models enhances interpretability, facilitating automated real-time analysis of big astronomical data and advancing our understanding of the cosmos.

关键词： YOLO Surveys Support vector machines Analytical models Accuracy Stars Spectral analysis Random forests Tuning Robots

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Mimicking Muscle Relaxation Through 3D Print Materials & Magnetic Systems 19

Mimicking Muscle Relaxation Through 3D Print Materials & Mag...

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19th IEEE International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI, HONET 2022

作者： Roberts, Santana Voicu, Razvan Cristian Moghadam, Amir Ali Amiri Chang, Yusun Kennesaw State University Department of Robotics & Mechatronics Engineering AtlantaGA United States

ISBN: (纸本)9781665461979

The purpose of this study is to examine the inter-action of a magnetic system with that of an elastic 3D print design to replicate a muscle in contraction expanding back to its original relaxed state. An electromagnetic system uses a design made of soft material to maintain a compression length when an electric current is applied. When the current is removed, the system expands back to its original length due to the geometry and elastic properties of the material. Preliminary experiments on differing magnets help establish a separation distance between the magnets within the design. Mathematical models then further detailed the design using the cross-sectional area, length, and angle between supports to estimate deflection. This design was then tested using nonlinear simulations to displace the component at a distance equivalent to the estimated distance given from the calculations. The reaction force was then compared to the force in the calculations to estimate the percent difference. Once decent results were obtained, a model was 3D printed and tested to verify the findings. The secondary goals of this endeavor are to utilize common materials, reduce the complexity of production, and limit the number of components within the system to reduce failure points along with an estimated lower cost for the overall apparatus. © 2022 IEEE.

关键词： Muscle

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Robust Control of a DC Motor and Load Using Quantitative Feedback Theory 19

Robust Control of a DC Motor and Load Using Quantitative Fee...

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19th IEEE International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI, HONET 2022

作者： Moghadam, Amir Ali Amiri Voicu, Razvan Cristian Patel, Kishan Wang, Ying Chang, Yusun Kennesaw State University Department of Robotics & Mechatronics Engineering AtlantaGA United States

ISBN: (纸本)9781665461979

This paper reports on robust position control of a DC motor and gear system attached to a mechanical load. The dynamics of the system will be identified using the sine wave inputs and least square method. It has been found out that a single linear time invariant (LTI) model cannot perfectly predicts the behavior of the system for a range of different frequencies. So, we are using a family of LTI systems instead with parameter uncertainty. Next a robust controller will be designed using Quantitative Feedback Theory (QFT) to provide consistent robust performance for the system. The performance of the QFT controller will be validated through both simulations and experimental data and will be compared with a PID controller. It has been shown that the QFT controller has a superior performance over the PID controller in terms of tracking error. © 2022 IEEE.

关键词： Controllers

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