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2. Deep Kernel and Image Quality Estimators for Optimizing Robotic Ultrasound Controller using Bayesian Optimization

Author

Raina, Deepak, Chandrashekhara, SH, Voyles, Richard, Wachs, Juan, and Saha, Subir Kumar

Subjects
Computer Science - Robotics, Computer Science - Machine Learning
Abstract

Ultrasound is a commonly used medical imaging modality that requires expert sonographers to manually maneuver the ultrasound probe based on the acquired image. Autonomous Robotic Ultrasound (A-RUS) is an appealing alternative to this manual procedure in order to reduce sonographers' workload. The key challenge to A-RUS is optimizing the ultrasound image quality for the region of interest across different patients. This requires knowledge of anatomy, recognition of error sources and precise probe position, orientation and pressure. Sample efficiency is important while optimizing these parameters associated with the robotized probe controller. Bayesian Optimization (BO), a sample-efficient optimization framework, has recently been applied to optimize the 2D motion of the probe. Nevertheless, further improvements are needed to improve the sample efficiency for high-dimensional control of the probe. We aim to overcome this problem by using a neural network to learn a low-dimensional kernel in BO, termed as Deep Kernel (DK). The neural network of DK is trained using probe and image data acquired during the procedure. The two image quality estimators are proposed that use a deep convolution neural network and provide real-time feedback to the BO. We validated our framework using these two feedback functions on three urinary bladder phantoms. We obtained over 50% increase in sample efficiency for 6D control of the robotized probe. Furthermore, our results indicate that this performance enhancement in BO is independent of the specific training dataset, demonstrating inter-patient adaptability., Comment: Accepted in IEEE International Symposium on Medical Robotics (ISMR) 2023

Published
2023
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3. RUSOpt: Robotic UltraSound Probe Normalization with Bayesian Optimization for In-plane and Out-plane Scanning

Author

Raina, Deepak, Mathur, Abhishek, Voyles, Richard M., Wachs, Juan, Chandrashekhara, SH, and Saha, Subir Kumar

Subjects
Computer Science - Robotics, Computer Science - Machine Learning
Abstract

The one of the significant challenges faced by autonomous robotic ultrasound systems is acquiring high-quality images across different patients. The proper orientation of the robotized probe plays a crucial role in governing the quality of ultrasound images. To address this challenge, we propose a sample-efficient method to automatically adjust the orientation of the ultrasound probe normal to the point of contact on the scanning surface, thereby improving the acoustic coupling of the probe and resulting image quality. Our method utilizes Bayesian Optimization (BO) based search on the scanning surface to efficiently search for the normalized probe orientation. We formulate a novel objective function for BO that leverages the contact force measurements and underlying mechanics to identify the normal. We further incorporate a regularization scheme in BO to handle the noisy objective function. The performance of the proposed strategy has been assessed through experiments on urinary bladder phantoms. These phantoms included planar, tilted, and rough surfaces, and were examined using both linear and convex probes with varying search space limits. Further, simulation-based studies have been carried out using 3D human mesh models. The results demonstrate that the mean ($\pm$SD) absolute angular error averaged over all phantoms and 3D models is $\boldsymbol{2.4\pm0.7^\circ}$ and $\boldsymbol{2.1\pm1.3^\circ}$, respectively., Comment: Accepted in IEEE International Conference on Automation Science and Engineering (CASE) 2023

Published
2023
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4. Expert-Agnostic Ultrasound Image Quality Assessment using Deep Variational Clustering

Author

Raina, Deepak, Ntentia, Dimitrios, Chandrashekhara, SH, Voyles, Richard, and Saha, Subir Kumar

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Ultrasound imaging is a commonly used modality for several diagnostic and therapeutic procedures. However, the diagnosis by ultrasound relies heavily on the quality of images assessed manually by sonographers, which diminishes the objectivity of the diagnosis and makes it operator-dependent. The supervised learning-based methods for automated quality assessment require manually annotated datasets, which are highly labour-intensive to acquire. These ultrasound images are low in quality and suffer from noisy annotations caused by inter-observer perceptual variations, which hampers learning efficiency. We propose an UnSupervised UltraSound image Quality assessment Network, US2QNet, that eliminates the burden and uncertainty of manual annotations. US2QNet uses the variational autoencoder embedded with the three modules, pre-processing, clustering and post-processing, to jointly enhance, extract, cluster and visualize the quality feature representation of ultrasound images. The pre-processing module uses filtering of images to point the network's attention towards salient quality features, rather than getting distracted by noise. Post-processing is proposed for visualizing the clusters of feature representations in 2D space. We validated the proposed framework for quality assessment of the urinary bladder ultrasound images. The proposed framework achieved 78% accuracy and superior performance to state-of-the-art clustering methods., Comment: Accepted in IEEE International Conference on Robotics and Automation (ICRA) 2023

Published
2023
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5. Robotic Sonographer: Autonomous Robotic Ultrasound using Domain Expertise in Bayesian Optimization

Author

Raina, Deepak, Chandrashekhara, SH, Voyles, Richard, Wachs, Juan, and Saha, Subir Kumar

Subjects
Computer Science - Robotics
Abstract

Ultrasound is a vital imaging modality utilized for a variety of diagnostic and interventional procedures. However, an expert sonographer is required to make accurate maneuvers of the probe over the human body while making sense of the ultrasound images for diagnostic purposes. This procedure requires a substantial amount of training and up to a few years of experience. In this paper, we propose an autonomous robotic ultrasound system that uses Bayesian Optimization (BO) in combination with the domain expertise to predict and effectively scan the regions where diagnostic quality ultrasound images can be acquired. The quality map, which is a distribution of image quality in a scanning region, is estimated using Gaussian process in BO. This relies on a prior quality map modeled using expert's demonstration of the high-quality probing maneuvers. The ultrasound image quality feedback is provided to BO, which is estimated using a deep convolution neural network model. This model was previously trained on database of images labelled for diagnostic quality by expert radiologists. Experiments on three different urinary bladder phantoms validated that the proposed autonomous ultrasound system can acquire ultrasound images for diagnostic purposes with a probing position and force accuracy of 98.7% and 97.8%, respectively., Comment: Accepted in IEEE International Conference on Robotics and Automation (ICRA) 2023

Published
2023
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6. Slim U-Net: Efficient Anatomical Feature Preserving U-net Architecture for Ultrasound Image Segmentation

Author

Raina, Deepak, Verma, Kashish, Chandrashekhara, SH, and Saha, Subir Kumar

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

We investigate the applicability of U-Net based models for segmenting Urinary Bladder (UB) in male pelvic view UltraSound (US) images. The segmentation of UB in the US image aids radiologists in diagnosing the UB. However, UB in US images has arbitrary shapes, indistinct boundaries and considerably large inter- and intra-subject variability, making segmentation a quite challenging task. Our study of the state-of-the-art (SOTA) segmentation network, U-Net, for the problem reveals that it often fails to capture the salient characteristics of UB due to the varying shape and scales of anatomy in the noisy US image. Also, U-net has an excessive number of trainable parameters, reporting poor computational efficiency during training. We propose a Slim U-Net to address the challenges of UB segmentation. Slim U-Net proposes to efficiently preserve the salient features of UB by reshaping the structure of U-Net using a less number of 2D convolution layers in the contracting path, in order to preserve and impose them on expanding path. To effectively distinguish the blurred boundaries, we propose a novel annotation methodology, which includes the background area of the image at the boundary of a marked region of interest (RoI), thereby steering the model's attention towards boundaries. In addition, we suggested a combination of loss functions for network training in the complex segmentation of UB. The experimental results demonstrate that Slim U-net is statistically superior to U-net for UB segmentation. The Slim U-net further decreases the number of trainable parameters and training time by 54% and 57.7%, respectively, compared to the standard U-Net, without compromising the segmentation accuracy., Comment: Accepted in 9th ACM International Conference on Biomedical and Bioinformatics Engineering (ICBBE) 2022 http://www.icbbe.com/

Published
2023
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8. Experimental Validation of the Position and Orientation Workspaces of the Stewart–Gough Platform

Author

Ashwath Ram, S., Nag, Anirban, Kumar, Sandeep, Saha, Subir Kumar, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Tolio, Tullio A. M., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Schmitt, Robert, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Kumar, Rajana Suresh, editor, Sanyal, Shubhashis, editor, and Pathak, P. M., editor

Published
2024
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9. Design and Development of a Three-Link Rigid-Flexible Manipulator

Author

Kumar, Sandeep, Vishwakarma, Sanjay, Singh, Rajmeet, Singla, Ashish, Saha, Subir Kumar, Bera, Tarun Kumar, Singh, Satinder Paul, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Ghoshal, Sanjoy K., editor, Samantaray, Arun K., editor, and Bandyopadhyay, Sandipan, editor

Published
2024
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10. The Inverse Kinematics Problem of the Generalised Stanford Arm

Author

Das, Aritra, Nag, Anirban, Saha, Subir Kumar, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Ghoshal, Sanjoy K., editor, Samantaray, Arun K., editor, and Bandyopadhyay, Sandipan, editor

Published
2024
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11. Robust Artificial Delay based Impedance Control of Robotic Manipulators with Uncertain Dynamics

Author

Banerjee, Udayan, Dey, Bhabani Shankar, Kar, Indra Narayan, and Saha, Subir Kumar

Subjects
Computer Science - Robotics, Electrical Engineering and Systems Science - Systems and Control
Abstract

In this paper an artificial delay based impedance controller is proposed for robotic manipulators with uncertainty in dynamics. The control law unites the time delayed estimation (TDE) framework with a second order switching controller of super twisting algorithm (STA) type via a novel generalized filtered tracking error (GFTE). While time delayed estimation framework eliminates the need for accurate modelling of robot dynamics by estimating the uncertain robot dynamics and interaction forces from immediate past data of state and control effort, the second order switching control law in the outer loop provides robustness against the time delayed estimation (TDE) error that arises due to approximation of the manipulator dynamics. Thus, the proposed control law tries to establish a desired impedance model between the robot end effector variables i.e. force and motion in presence of uncertainties, both when it is encountering smooth contact forces and during free motion. Simulation results for a two link manipulator using the proposed controller along with convergence analysis are shown to validate the proposition.

Published
2022

12. Interpretation of Black Box NLP Models: A Survey

Author

Choudhary, Shivani, Chatterjee, Niladri, and Saha, Subir Kumar

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Information Retrieval
Abstract

An increasing number of machine learning models have been deployed in domains with high stakes such as finance and healthcare. Despite their superior performances, many models are black boxes in nature which are hard to explain. There are growing efforts for researchers to develop methods to interpret these black-box models. Post hoc explanations based on perturbations, such as LIME, are widely used approaches to interpret a machine learning model after it has been built. This class of methods has been shown to exhibit large instability, posing serious challenges to the effectiveness of the method itself and harming user trust. In this paper, we propose S-LIME, which utilizes a hypothesis testing framework based on central limit theorem for determining the number of perturbation points needed to guarantee stability of the resulting explanation. Experiments on both simulated and real world data sets are provided to demonstrate the effectiveness of our method.

Published
2022

15. Gear Meshing Visualization for Effective Education Using MechAnalyzer Software

Author

Saha, Nilabro, Chittawadigi, Rajeevlochana G., Saha, Subir Kumar, Cavas-Martínez, Francisco, Editorial Board Member, Chaari, Fakher, Series Editor, di Mare, Francesca, Editorial Board Member, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Editorial Board Member, Ivanov, Vitalii, Series Editor, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Gupta, Vijay Kumar, editor, Amarnath, C., editor, Tandon, Puneet, editor, and Ansari, M. Zahid, editor

Published
2023
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17. Conclusion

Author

Hayat, Abdullah Aamir, Chaudhary, Shraddha, Boby, Riby Abraham, Udai, Arun Dayal, Dutta Roy, Sumantra, Saha, Subir Kumar, Chaudhury, Santanu, Kacprzyk, Janusz, Series Editor, Hayat, Abdullah Aamir, Chaudhary, Shraddha, Boby, Riby Abraham, Udai, Arun Dayal, Dutta Roy, Sumantra, Saha, Subir Kumar, and Chaudhury, Santanu

Published
2022
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18. Integrated Assembly and Performance Evaluation

Author

Hayat, Abdullah Aamir, Chaudhary, Shraddha, Boby, Riby Abraham, Udai, Arun Dayal, Dutta Roy, Sumantra, Saha, Subir Kumar, Chaudhury, Santanu, Kacprzyk, Janusz, Series Editor, Hayat, Abdullah Aamir, Chaudhary, Shraddha, Boby, Riby Abraham, Udai, Arun Dayal, Dutta Roy, Sumantra, Saha, Subir Kumar, and Chaudhury, Santanu

Published
2022
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19. Force Control and Assembly

Author

Hayat, Abdullah Aamir, Chaudhary, Shraddha, Boby, Riby Abraham, Udai, Arun Dayal, Dutta Roy, Sumantra, Saha, Subir Kumar, Chaudhury, Santanu, Kacprzyk, Janusz, Series Editor, Hayat, Abdullah Aamir, Chaudhary, Shraddha, Boby, Riby Abraham, Udai, Arun Dayal, Dutta Roy, Sumantra, Saha, Subir Kumar, and Chaudhury, Santanu

Published
2022
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20. Identification

Author

Hayat, Abdullah Aamir, Chaudhary, Shraddha, Boby, Riby Abraham, Udai, Arun Dayal, Dutta Roy, Sumantra, Saha, Subir Kumar, Chaudhury, Santanu, Kacprzyk, Janusz, Series Editor, Hayat, Abdullah Aamir, Chaudhary, Shraddha, Boby, Riby Abraham, Udai, Arun Dayal, Dutta Roy, Sumantra, Saha, Subir Kumar, and Chaudhury, Santanu

Published
2022
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21. Uncertainty and Sensitivity Analysis

Author

Hayat, Abdullah Aamir, Chaudhary, Shraddha, Boby, Riby Abraham, Udai, Arun Dayal, Dutta Roy, Sumantra, Saha, Subir Kumar, Chaudhury, Santanu, Kacprzyk, Janusz, Series Editor, Hayat, Abdullah Aamir, Chaudhary, Shraddha, Boby, Riby Abraham, Udai, Arun Dayal, Dutta Roy, Sumantra, Saha, Subir Kumar, and Chaudhury, Santanu

Published
2022
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22. Vision System and Calibration

Author

Hayat, Abdullah Aamir, Chaudhary, Shraddha, Boby, Riby Abraham, Udai, Arun Dayal, Dutta Roy, Sumantra, Saha, Subir Kumar, Chaudhury, Santanu, Kacprzyk, Janusz, Series Editor, Hayat, Abdullah Aamir, Chaudhary, Shraddha, Boby, Riby Abraham, Udai, Arun Dayal, Dutta Roy, Sumantra, Saha, Subir Kumar, and Chaudhury, Santanu

Published
2022
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23. Dynamics of Serial Rigid–Flexible Robots

Author

Nandihal, Paramanand Vivekanand, Mohan, Ashish, Saha, Subir Kumar, Valavanis, Kimon P., Series Editor, Antsaklis, P., Advisory Editor, Borne, P., Advisory Editor, Carelli, R., Advisory Editor, Fukuda, T., Advisory Editor, Gans, N.R., Advisory Editor, Harashima, F., Advisory Editor, Martinet, P., Advisory Editor, Monaco, S., Advisory Editor, Negenborn, R.R., Advisory Editor, Pascoal, António, Advisory Editor, Schmidt, G., Advisory Editor, Sobh, T.M., Advisory Editor, Tzafestas, C., Advisory Editor, Nandihal, Paramanand Vivekanand, Mohan, Ashish, and Saha, Subir Kumar

Published
2022
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24. Experimental Results

Author

Nandihal, Paramanand Vivekanand, Mohan, Ashish, Saha, Subir Kumar, Valavanis, Kimon P., Series Editor, Antsaklis, P., Advisory Editor, Borne, P., Advisory Editor, Carelli, R., Advisory Editor, Fukuda, T., Advisory Editor, Gans, N.R., Advisory Editor, Harashima, F., Advisory Editor, Martinet, P., Advisory Editor, Monaco, S., Advisory Editor, Negenborn, R.R., Advisory Editor, Pascoal, António, Advisory Editor, Schmidt, G., Advisory Editor, Sobh, T.M., Advisory Editor, Tzafestas, C., Advisory Editor, Nandihal, Paramanand Vivekanand, Mohan, Ashish, and Saha, Subir Kumar

Published
2022
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25. Dynamics of Closed-Loop Systems

Author

Nandihal, Paramanand Vivekanand, Mohan, Ashish, Saha, Subir Kumar, Valavanis, Kimon P., Series Editor, Antsaklis, P., Advisory Editor, Borne, P., Advisory Editor, Carelli, R., Advisory Editor, Fukuda, T., Advisory Editor, Gans, N.R., Advisory Editor, Harashima, F., Advisory Editor, Martinet, P., Advisory Editor, Monaco, S., Advisory Editor, Negenborn, R.R., Advisory Editor, Pascoal, António, Advisory Editor, Schmidt, G., Advisory Editor, Sobh, T.M., Advisory Editor, Tzafestas, C., Advisory Editor, Nandihal, Paramanand Vivekanand, Mohan, Ashish, and Saha, Subir Kumar

Published
2022
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26. Numerical Stability and Efficiency

Author

Nandihal, Paramanand Vivekanand, Mohan, Ashish, Saha, Subir Kumar, Valavanis, Kimon P., Series Editor, Antsaklis, P., Advisory Editor, Borne, P., Advisory Editor, Carelli, R., Advisory Editor, Fukuda, T., Advisory Editor, Gans, N.R., Advisory Editor, Harashima, F., Advisory Editor, Martinet, P., Advisory Editor, Monaco, S., Advisory Editor, Negenborn, R.R., Advisory Editor, Pascoal, António, Advisory Editor, Schmidt, G., Advisory Editor, Sobh, T.M., Advisory Editor, Tzafestas, C., Advisory Editor, Nandihal, Paramanand Vivekanand, Mohan, Ashish, and Saha, Subir Kumar

Published
2022
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27. Dynamics of Spatial Four-Bar Mechanism

Author

Nandihal, Paramanand Vivekanand, Mohan, Ashish, Saha, Subir Kumar, Valavanis, Kimon P., Series Editor, Antsaklis, P., Advisory Editor, Borne, P., Advisory Editor, Carelli, R., Advisory Editor, Fukuda, T., Advisory Editor, Gans, N.R., Advisory Editor, Harashima, F., Advisory Editor, Martinet, P., Advisory Editor, Monaco, S., Advisory Editor, Negenborn, R.R., Advisory Editor, Pascoal, António, Advisory Editor, Schmidt, G., Advisory Editor, Sobh, T.M., Advisory Editor, Tzafestas, C., Advisory Editor, Nandihal, Paramanand Vivekanand, Mohan, Ashish, and Saha, Subir Kumar

Published
2022
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28. Dynamic Formulation Using the Decoupled Natural Orthogonal Complement (DeNOC)

Author

Nandihal, Paramanand Vivekanand, Mohan, Ashish, Saha, Subir Kumar, Valavanis, Kimon P., Series Editor, Antsaklis, P., Advisory Editor, Borne, P., Advisory Editor, Carelli, R., Advisory Editor, Fukuda, T., Advisory Editor, Gans, N.R., Advisory Editor, Harashima, F., Advisory Editor, Martinet, P., Advisory Editor, Monaco, S., Advisory Editor, Negenborn, R.R., Advisory Editor, Pascoal, António, Advisory Editor, Schmidt, G., Advisory Editor, Sobh, T.M., Advisory Editor, Tzafestas, C., Advisory Editor, Nandihal, Paramanand Vivekanand, Mohan, Ashish, and Saha, Subir Kumar

Published
2022
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29. Dynamics of Six-Link Spatial Robot Arms

Author

Nandihal, Paramanand Vivekanand, Mohan, Ashish, Saha, Subir Kumar, Valavanis, Kimon P., Series Editor, Antsaklis, P., Advisory Editor, Borne, P., Advisory Editor, Carelli, R., Advisory Editor, Fukuda, T., Advisory Editor, Gans, N.R., Advisory Editor, Harashima, F., Advisory Editor, Martinet, P., Advisory Editor, Monaco, S., Advisory Editor, Negenborn, R.R., Advisory Editor, Pascoal, António, Advisory Editor, Schmidt, G., Advisory Editor, Sobh, T.M., Advisory Editor, Tzafestas, C., Advisory Editor, Nandihal, Paramanand Vivekanand, Mohan, Ashish, and Saha, Subir Kumar

Published
2022
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30. Introduction

Author

Nandihal, Paramanand Vivekanand, Mohan, Ashish, Saha, Subir Kumar, Valavanis, Kimon P., Series Editor, Antsaklis, P., Advisory Editor, Borne, P., Advisory Editor, Carelli, R., Advisory Editor, Fukuda, T., Advisory Editor, Gans, N.R., Advisory Editor, Harashima, F., Advisory Editor, Martinet, P., Advisory Editor, Monaco, S., Advisory Editor, Negenborn, R.R., Advisory Editor, Pascoal, António, Advisory Editor, Schmidt, G., Advisory Editor, Sobh, T.M., Advisory Editor, Tzafestas, C., Advisory Editor, Nandihal, Paramanand Vivekanand, Mohan, Ashish, and Saha, Subir Kumar

Published
2022
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31. Degenerate Cases in the Inverse Kinematics Problem of a General 6R Serial Robot

Author

Das, Aritra, Nag, Anirban, Saha, Subir Kumar, Siciliano, Bruno, Series Editor, Khatib, Oussama, Series Editor, Antonelli, Gianluca, Advisory Editor, Fox, Dieter, Advisory Editor, Harada, Kensuke, Advisory Editor, Hsieh, M. Ani, Advisory Editor, Kröger, Torsten, Advisory Editor, Kulic, Dana, Advisory Editor, Park, Jaeheung, Advisory Editor, Altuzarra, Oscar, editor, and Kecskeméthy, Andrés, editor

Published
2022
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32. Differentially Flat Prosthetic Leg for Unilateral Transfemoral Amputees

Author

Sinha, Sasanka Sekhar, Saha, Subir Kumar, Mukherjee, Sudipto, Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, Larochelle, Pierre, editor, and McCarthy, J. Michael, editor

Published
2022
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33. MechAnalyzer for Teaching of Kinematics of Linkage Mechanisms Through Simulations and Historical Context

Author

Saha, Nilabro, Chittawadigi, Rajeevlochana G., Saha, Subir Kumar, Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, Khang, Nguyen Van, editor, and Hoang, Nguyen Quang, editor

Published
2022
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36. Deformation Analysis of Cosserat Rods Using Piecewise Clothoid Approximation.

Author

Sivaj, Sreejath, Saha, Subir Kumar, and Singh, Satinder Paul

Abstract

This paper presents an alternative to isogeometric analysis (IGA) for static analysis of planar curved slender beams. Geometrically exact Cosserat rod model is employed to establish the governing equations. In contrast to conventional IGA, which uses NURBS as the basis function, our method incorporates clothoid curves to represent the curved geometry. We use piecewise clothoid curves to approximate the initial curvature of the undeformed beam, facilitating a seamless integration into the Cosserat rod model. A straightforward solution of the governing equations is implemented using shooting method, verifying applicability across a range of problems. Interestingly, the parameters that define the clothoid segments also appear in the governing equations of the beam. This bridges the gap between the geometric design of the beams and their static simulations. In this way, we present the proposed formulation as an alternative to conventional IGA. The notable features of the method are easy implementation, good accuracy, and convergence. Moreover, the method predicts bending stress in the beam, capturing the nonlinearity of the deformation. [ABSTRACT FROM AUTHOR]

Published
2025
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38. Underactuated Control of Serial Manipulator

Author

Jain, Aditya, Kumar, Rajesh, Kar, Indra Narayan, Saha, Subir Kumar, Chaari, Fakher, Series Editor, Haddar, Mohamed, Series Editor, Kwon, Young W., Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Sen, Dibakar, editor, Mohan, Santhakumar, editor, and Ananthasuresh, Gondi Kondaiah, editor

Published
2021
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39. MechAnalyzer: Software to Teach Kinematics Concepts Related to Cams, Gears, and Instantaneous Center

Author

Dikshithaa, R., Jain, Siddhant, Swaminathan, Janani, Chittawadigi, Rajeevlochana G., Saha, Subir Kumar, Chaari, Fakher, Series Editor, Haddar, Mohamed, Series Editor, Kwon, Young W., Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Sen, Dibakar, editor, Mohan, Santhakumar, editor, and Ananthasuresh, Gondi Kondaiah, editor

Published
2021
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40. Prioritizing Tasks Within a Robotic Transportation System for a Smart Hospital Environment

Author

Safin, Ruslan, Lavrenov, Roman, Tsoy, Tatyana, Magid, Evgeni, Svinin, Mikhail, Roy, Sumantra Dutta, Saha, Subir Kumar, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ronzhin, Andrey, editor, Rigoll, Gerhard, editor, and Meshcheryakov, Roman, editor

Published
2021
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