Pavan Chakraborty

Development of Adaptive Modular Active Leg (AMAL) using bipedal robotics technology

The objective of the work presented here is to develop a low cost active above knee prosthetic device exploiting bipedal robotics technology which will work utilizing the available biological motor control circuit properly integrated with a Central Pattern Generator (CPG) based control scheme. The approach is completely different from the existing Active Prosthetic devices, designed primarily as standalone systems utilizing multiple sensors and embedded rigid control schemes. In this research, first we designed a fuzzy logic based methodology for offering suitable gait pattern for an amputee, followed by formulating a suitable algorithm for designing a CPG, based on Rayleighs oscillator. An indigenous probe, Humanoid Gait Oscillator Detector (HGOD) has been designed for capturing gait patterns from various individuals of different height, weight and age. These data are used to design a Fuzzy inference system which generates most suitable gait pattern for an amputee. The output of the Fuzzy inference system is used for designing a CPG best suitable for the amputee. We then developed a CPG based control scheme for calculating the damping profile in real time for maneuvering a prosthetic device called AMAL (Adaptive Modular Active Leg). Also a number of simulation results are presented which show the stable behavior of knee and hip angles and determine the stable limit cycles of the network.

Recognizing & interpreting Indian Sign Language gesture for Human Robot Interaction

This paper describes a novel approach towards recognizing of Indian Sign Language (ISL) gestures for Humanoid Robot Interaction (HRI). An extensive approach is being introduced for classification of ISL gesture which imparts an elegant way of interaction between humanoid robot HOAP-2 and human being. ISL gestures are being considered as a communicating agent for humanoid robot which is being used in this context explicitly. It involves different image processing techniques followed by a generic algorithm for feature extraction process. The classification technique deals with the Euclidean distance metric. The concrete HRI system has been established for initiation based learning mechanism. The Real time robotics simulation software, WEBOTS has been adopted to simulate the classified ISL gestures on HOAP-2 robot. The JAVA based software has been developed to deal with the entire HRI process.

Biped model based on human Gait pattern parameters for sagittal plane movement

The present research as described in this paper tries to impart how imitation based learning for behavior-based programming can be used to teach the robot. The simulated model tries to imitate human GAIT pattern and negotiate push with efficient recovery [1]. This paper also proposes the HOAP2 [2] based biped model to achieve gait cycle imitation and push recovery on humanoid. The proposed model follows the Gait cycle [1] and can be further used for developing a model capable to recover from push similar to human biology. This development is a big step in way to prove that push recovery is a software engineering problem and not hardware engineering problem. The walking algorithm used here aims to select a subset of push recovery problem i.e. disturbance from environment. We applied the physics at each joint of Halo with some degree of freedom. The proposed model, Halo is different from other models as previously developed model were inconsistent with data for different persons. This would lead to development of the generalized biped model in future and will bridge the gap between performance and inconsistency. In this paper the proposed model is applied to data of different persons. Accuracy of model, performance and result is measured using the behavior negotiation capability of model developed. In order to improve the performance, proposed model gives the freedom to handle each joint independently based on the belongingness value for each joint. The development can be considered as important development for future world of robotics. The accuracy of model is 70% in one go. In this paper, we achieve to imitate the human gait cycle for HOAP-2 [2] robots model Halo. We validate our model by giving different input configuration parameter i.e. CoM, CoP and joint angle of different samples to HOAP-2[2] model designed in Webots, which can demonstrate the behavior as per new configuration provided for different person.

Recognition of Isolated Indian Sign Language Gesture in Real Time

Indian Sign Language (ISL) consists of static as well as dynamic hand gestures for communication among deaf and dumb persons. Most of the ISL gestures are produced using both hands. A video database is created and utilized which contains several videos, for a large number of signs. Direction histogram is the feature used for classification due to its appeal for illumination and orientation invariance. Two different approaches utilized for recognition are Euclidean distance and K-nearest neighbor metrics.

Local directional gradient pattern: a local descriptor for face recognition

In this paper a local pattern descriptor in high order derivative space is proposed for face recognition. The proposed local directional gradient pattern (LDGP) is a 1D local micropattern computed by encoding the relationships between higher order derivatives of the reference pixel in four distinct directions. The proposed descriptor identifies relationship between the high order derivatives of the referenced pixel in four different directions to compute the micropattern which corresponds to the local feature. Proposed descriptor considerably reduces the length of the micropattern which consequently reduces the extraction time and matching time while maintaining the recognition rate. Results of the extensive experiments conducted on benchmark databases AT&T, Extended Yale B and CMU-PIE show that the proposed descriptor significantly reduces the extraction as well as matching time while the recognition rate of the descriptor is almost similar to existing state of the art methods. Moreover the proposed descriptor is more resistant against the AWGN compared to the other state of the art descriptors used for face recognition problems.

Robotic Services in Cloud Computing Paradigm

Cloud computing and service oriented architecture (SOA) are the dominant computing paradigm. Since past few years Robotics applications have also started to build around these paradigms. This paper presents entrance of robotic services in SOA and cloud computing. Where a client/user can opt for the robotic services present at the cloud like navigation, map building, object recognition etc. Map-reduce computing cluster is also facilitated at the cloud to process large amount of data for the cloud robotic services. The whole system follows the Web 2.0 standard. We also reported the simulation results for service based speech controlled robots with visual programming language (VPL) of Microsoft Development Robotics Studio (MDRS) and implementation of map-reduce computing cluster in robotic cloud.

A Framework for Synthesis of Human Gait Oscillation Using Intelligent Gait Oscillation Detector (IGOD)

The main objective of this paper illustrates an elementary concept about the designing, development and implementation of a bio-informatics diagnostic tool which understands and analyzes the human gait oscillation in order to provide an insight on human bi-pedal locomotion and its stability. A multi sensor device for detection of gait oscillations during human locomotion has been developed effectively. It has been named “IGOD”, an acronym of the “Intelligent Gait Oscillation Detector”. It ensures capturing of different person’s walking pattern in a very elegant way. This device would be used for creating a database of gait oscillations which could be extensively applied in several implications. The preliminary acquired data for eight major joints of a human body have been presented significantly. The electronic circuit has been attached to IGOD device in order to customize the proper calibration of every joint angle eventually.

Cloth invariant gait recognition using pooled segmented statistical features

Abstract A natural and normal gait can be used as a biometric cue in finding a solution to the human identification problem. An individual׳s appearance is likely to change with the variation in different clothes which further compounds the problem of gait identification. The clothing differences between gallery and probe datasets capture the possible changes in their silhouette׳s shape which increases the inability to discriminate between individuals. In this paper, an attempt has been made to provide a novel statistical shape analysis method based on Gait Energy Image (GEI) which is decomposed into three independent shape segmentations such as horizontal, vertical and grid resolution. The pooled segmented statistical features describe the shape of the GEI edge contour. The higher order moments about the shape centroid are likely to be invariant to small changes in silhouette shape. They implicitly describe the underlying distribution of the shape and can be used in conjunction with a set of other area based features to increase the efficacy of the classification results. The features reliability test has been performed with three classical statistical methods such as intra cloths variance (F-Statistics), inter subject distance (t-Statistics) and Intra-Class Correlation (ICC) on each set of segment of features. This analysis illustrates that combination of features holds less discrimination in comparison to grid based shape segmentation for different clothes. The similarity measurement comprises of different classification techniques (k-Nearest Neighbor, Naive Bayes׳, Decision Tree (C4.5) and Random Forest) to produce acceptable recognition results on OU-ISIR dataset. The degree of discriminability of these classifiers has been measured by statistical metrics such as F1-Score, Precision, Recall, and ROC curve.

Next-generation sequencing revolution through big data analytics

ABSTRACT Next-generation sequencing (NGS) technology has led to an unrivaled explosion in the amount of genomic data and this escalation has collaterally raised the challenges of sharing, archiving, integrating and analyzing these data. The scale and efficiency of NGS have posed a challenge for analysis of these vast genomic data, gene interactions, annotations and expression studies. However, this limitation of NGS can be safely overcome by tools and algorithms using big data framework. Based on this framework, here we have reviewed the current state of knowledge of big data algorithms for NGS to reveal hidden patterns in sequencing, analysis and annotation, and so on. The APACHE-based Hadoop framework gives an on-interest and adaptable environment for substantial scale data analysis. It has several components for partitioning of large-scale data onto clusters of commodity hardware, in a fault-tolerant manner. Packages like MapReduce, Cloudburst, Crossbow, Myrna, Eoulsan, DistMap, Seal and Contrail perform various NGS applications, such as adapter trimming, quality checking, read mapping, de novo assembly, quantification, expression analysis, variant analysis, and annotation. This review paper deals with the current applications of the Hadoop technology with their usage and limitations in perspective of NGS.

Development of a Robust Microcontroller Based Intelligent Prosthetic Limb

Adaptive Modular Active Leg (AMAL), a robotic Intelligent Prosthetic Limb has been developed at the Indian Institute of Information Technology Allahabad. The aim of the project was to provide the comfort of an intelligent prosthetic knee joint for differently abeled person with one leg amputated above the knee. AMAL provides him with the necessary shock absorption and a suitable bending of the knee joint oscillation. The bending and the shock absorption are provided by artificial muscles. In our case, it is the MR (Magneto Rheological) damper which controls the knee movement of an amputee. The feedback signal is provided by the heel’s strike sensor. AMAL has been kept simple with minimal feedback sensors and controls so that the product is economically viable for the patients. In this paper we describe the mechanical design, the electronic control with its successful testing on differently abeled persons.