scholarly journals Shape Sensing of Hyper-Redundant Robots Using an AHRS IMU Sensor Network

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 373
Author(s):  
Ciprian Lapusan ◽  
Olimpiu Hancu ◽  
Ciprian Rad
Keyword(s):  
Sensor Network ◽  
Kinematic Model ◽  
Sensory System ◽  
Feedback System ◽  
Computational Time ◽  
Redundant Robots ◽  
Testing Method ◽  
Operational Space ◽  
Novel Approach ◽  
Shape Sensing

The paper proposes a novel approach for shape sensing of hyper-redundant robots based on an AHRS IMU sensor network embedded into the structure of the robot. The proposed approach uses the data from the sensor network to directly calculate the kinematic parameters of the robot in modules operational space reducing thus the computational time and facilitating implementation of advanced real-time feedback system for shape sensing. In the paper the method is applied for shape sensing and pose estimation of an articulated joint-based hyper-redundant robot with identical 2-DoF modules serially connected. Using a testing method based on HIL techniques the authors validate the computed kinematic model and the computed shape of the robot prototype. A second testing method is used to validate the end effector pose using an external sensory system. The experimental results obtained demonstrate the feasibility of using this type of sensor network and the effectiveness of the proposed shape sensing approach for hyper-redundant robots.

scholarly journals Realtime Motion Assessment For Rehabilitation Exercises: Integration Of Kinematic Modeling With Fuzzy Inference

2014 ◽  
Vol 4 (4) ◽  
pp. 267-285 ◽  
Author(s):  
Wenbing Zhao ◽  
Roanna Lun ◽  
Deborah D. Espy ◽  
M. Ann Reinthal
Keyword(s):  
Fuzzy Inference ◽  
Kinematic Model ◽  
Integrated Approach ◽  
Kinematic Modeling ◽  
Motion Data ◽  
Fuzzy Interference System ◽  
Novel Approach ◽  
Motion Assessment ◽  
Rehabilitation Exercises ◽  
Rehabilitation Exercise

Abstract This article describes a novel approach to realtime motion assessment for rehabilitation exercises based on the integration of comprehensive kinematic modeling with fuzzy inference. To facilitate the assessment of all important aspects of a rehabilitation exercise, a kinematic model is developed to capture the essential requirements for static poses, dynamic movements, as well as the invariance that must be observed during an exercise. The kinematic model is expressed in terms of a set of kinematic rules. During the actual execution of a rehabilitation exercise, the similarity between the measured motion data and the model is computed in terms of their distances, which are then used as inputs to a fuzzy interference system to derive the overall quality of the execution. The integrated approach provides both a detailed categorical assessment of the overall execution of the exercise and the degree of adherence to individual kinematic rules.

scholarly journals Comparative study on the redundancy of mobile single- and dual-arm robots

2016 ◽  
Vol 13 (6) ◽  
pp. 172988141666678
Author(s):  
Hongxing Wang ◽  
Ruifeng Li ◽  
Yunfeng Gao ◽  
Chuqing Cao ◽  
Lianzheng Ge
Keyword(s):  
Rate Control ◽  
Control Algorithm ◽  
Redundant Robot ◽  
Motion Models ◽  
Redundant Robots ◽  
Operational Space ◽  
Rate Control Algorithm ◽  
Simulation Results ◽  
Dual Arm Robot ◽  
Dual Arm

A whole resolved motion rate control algorithm designed for mobile dual-arm redundant robots is presented in this article. Based on this algorithm, the end-effector movements of the dual arms of the mobile dual-arm redundant robot can be decomposed into the movements of the two driving wheels of the differential driving platform and the movements of the dual-arm each joint of this robot harmoniously. The influence of the redundancies of the single- and dual-arm robots on the operation based on the fixed- and differential-driving platforms, which are then based on the whole resolved motion rate control algorithm, is studied after building their motion models. Some comparisons are made to show the advantages of this algorithm on the entire modeling of the complicated robotic system and the influences of the redundancy. First, the comparison of the simulation results between the fixed single-arm robot and the mobile single-arm robot is presented. Second, a comparison of the simulation results between the mobile single-arm robot and the mobile dual-arm robots is shown. Compared with the mobile single-arm robot and the fixed dual-arm robot based on this algorithm, the mobile dual-arm robot has more redundancy and can simultaneously track and operate different objects. Moreover, the mobile dual-arm redundant robot has better smoothness, more flexibility, larger operational space, and more harmonious cooperation between the two arms and the differential driving platform during the entire mobile operational process.

Impedance Control of Dual-Arm Systems Based on the Object with Senseless Force

2013 ◽  
Vol 765-767 ◽  
pp. 1920-1923
Author(s):  
Li Jiang ◽  
Yang Zhou ◽  
Bin Wang ◽  
Chao Yu
Keyword(s):  
Numerical Simulations ◽  
Relative Position ◽  
Position Control ◽  
Impedance Control ◽  
Force Sensors ◽  
Operational Space ◽  
Novel Approach ◽  
Control Scheme ◽  
Statics And Dynamics ◽  
Dual Arm

A novel approach to impedance control based on the object is proposed to control dual-arm systems with senseless force. Considering the motion of the object, the statics and dynamics of the dual-arm systems are modeled. Extending the dynamics of dual-arm system and the impedance of object to the operational space, impedance control with senseless force is presented. Simulations on a dual-arm system are carried out to demonstrate the performance of the proposed control scheme. Comparing with position control, results of numerical simulations show that the proposed scheme realizes suitable compliant behaviors in terms of the object, and minimizes the error of the relative position between the manipulators even without force sensors.

scholarly journals Random Tanglegram Partitions (Random TaPas): An Alexandrian Approach to the Cophylogenetic Gordian Knot

2018 ◽  
Author(s):  
Juan Antonio Balbuena ◽  
Óscar Alejandro Pérez-Escobar ◽  
Cristina Llopis-Belenguer ◽  
Isabel Blasco-Costa
Keyword(s):  
Recursive Partitioning ◽  
Computational Time ◽  
Ecological Diversity ◽  
Passerine Birds ◽  
Symbiotic Associations ◽  
The Public ◽  
Novel Approach ◽  
Open Issue ◽  
Key Driver ◽  
Global Fit

AbstractSymbiosis is a key driver of evolutionary novelty and ecological diversity, but our understanding of how macroevolutionary processes originate extant symbiotic associations is still very incomplete. Cophylogenetic tools are used to assess the congruence between the phylogenies of two groups of organisms related by extant associations. If phylogenetic congruence is higher than expected by chance, we conclude that there is cophylogenetic signal in the system under study. However, how to quantify cophylogenetic signal is still an open issue. We present a novel approach, Random Tanglegram Partitions (Random TaPas) that applies a given global-fit method to random partial tanglegrams of a fixed size to identify the associations, terminals and nodes that maximize phylogenetic congruence. By means of simulations, we show that the output value produced is inversely proportional to the number and proportion of cospeciation events employed to build simulated tanglegrams. In addition, with time-calibrated trees, Random TaPas is also efficient at distinguishing cospeciation from pseudocospeciation. Random TaPas can handle large tanglegrams in affordable computational time and incorporates phylogenetic uncertainty in the analyses. We demonstrate its application with two real examples: Passerine birds and their feather mites, and orchids and bee pollinators. In both systems, Random TaPas revealed low cophylogenetic signal, but mapping its variation onto the tanglegram pointed to two different coevolutionary processes. We suggest that the recursive partitioning of the tanglegram buffers the effect of phylogenetic nonindependence occurring in current global-fit methods and therefore Random TaPas is more reliable than regular global-fit methods to identify host-symbiont associations that contribute most to cophylogenetic signal. Random TaPas can be implemented in the public-domain statistical software R with scripts provided herein. A User’s Guide is also available at GitHub.

scholarly journals A REVIEW ON A NOVEL APPROACH FOR DATA COLLECTION IN WSN

2017 ◽  
Vol 16 (3) ◽  
pp. 6213-6218
Author(s):  
Ramandeep Kaur ◽  
Dinesh Kumar
Keyword(s):  
Sensor Network ◽  
Data Aggregation ◽  
Energy Cost ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Threshold Values ◽  
Novel Approach ◽  
Wide Range ◽  
Network Application ◽  
Soft Threshold

Wireless sensor networks have become increasingly popular due to their wide range of application. Clustering sensor nodes organizing them hierarchically have proven to be an effective method to provide better data aggregation and scalability for the sensor network while conserving limited energy. Minimizing the energy consumption of a wireless sensor network application is crucial for effective realization of the intended application in terms of cost, lifetime, and functionality. However, the minimizing task is hardly possible as no overall energy cost function is available for optimization. In this paper, we have proposed a modified alogirthm of leach where hard and soft threshold values will be applied for improving the overall throughput and network lifetime.

A Novel Approach to Detect Abnormal Chest X-rays of COVID-19 Patients Using Image Processing and Deep Learning

2021 ◽  
pp. 23-41
Author(s):  
Subhagata Chattopadhyay
Keyword(s):  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Hessian Matrix ◽  
Region Of Interest ◽  
Computational Time ◽  
X Rays ◽  
Feed Forward Neural Network ◽  
Novel Approach ◽  
Input Dataset

The study proposes a novel approach to automate classifying Chest X-ray (CXR) images of COVID-19 positive patients. All acquired images have been pre-processed with Simple Median Filter (SMF) and Gaussian Filter (GF) with kernel size (5, 5). The better filter is then identified by comparing Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) of denoised images. Canny's edge detection has been applied to find the Region of Interest (ROI) on denoised images. Eigenvalues [-2, 2] of the Hessian matrix (5 × 5) of the ROIs are then extracted, which constitutes the 'input' dataset to the Feed Forward Neural Network (FFNN) classifier, developed in this study. Eighty percent of the data is used for training the said network after 10-fold cross-validation and the performance of the network is tested with the remaining 20% of the data. Finally, validation has been made on another set of 'raw' normal and abnormal CXRs. Precision, Recall, Accuracy, and Computational time complexity (Big(O)) of the classifier are then estimated to examine its performance.

Shape sensing and feedback control of the catheter robot for interventional surgery

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fei Qi ◽  
Bai Chen ◽  
Shigang She ◽  
Shuyuan Gao
Keyword(s):  
Feedback Control ◽  
Control Strategy ◽  
Kinematic Model ◽  
Shape Reconstruction ◽  
Reconstruction Method ◽  
Content Type ◽  
Feedback Control Strategy ◽  
Shape Sensing ◽  
Control Accuracy ◽  
Reconstruction Model

Purpose This paper aims to present a shape sensing method and feedback control strategy based on fiber Bragg grating (FBG) sensor to improve the control accuracy of the robot and ensure the safety of the cardiac interventional surgery. Design/methodology/approach To theoretically describe the shape of the catheter robot, the kinematic model is established by the geometric analysis method. And to obtain the actual shape, a large curvature assemble sensor based on FBG is adopted and a novel simple shape reconstruction model is proposed, which can provide the shape curve and distal position. In addition, the influence of external load on the bending deformation is investigated by experiments. To improve the shape accuracy of the robot, a shape feedback control method is presented to control the catheter robot, which can control the robot to bend into the pre-given desired shape. Findings Experiment results verify the effectiveness of the shape sensing method and the reconstruction model, and the correlation coefficients of three sets of curve in different coordinate directions are 0.9986, 0.9992 and 0.9999. Results of the shape feedback experiment show that the curvature error and direction angle error are 1.42% and 10.3%, respectively. The continuum catheter robot can be controlled to achieve the desired bending shape. Originality/value The shape reconstruction method and feedback control strategy proposed in this paper can improve the control accuracy of the robot to avoid the risk of the collision with the surrounding blood vessels, the tissues and organs.

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