Proceedings of the international conference on signal, networks, computing, and systems ICSNCS 2016, volume 2

Lecture Notes in Electrical Engineering 396 Daya K. Lobiyal Durga Prasad Mohapatra Atulya Nagar Manmath N. Sahoo Editors Proceedings of the International Conference on Signal, Networks, Computing, and Systems ICSNCS 2016, Volume Lecture Notes in Electrical Engineering Volume 396 Board of Series editors Leopoldo Angrisani, Napoli, Italy Marco Arteaga, Coyoacán, México Samarjit Chakraborty, München, Germany Jiming Chen, Hangzhou, P.R China Tan Kay Chen, Singapore, Singapore Rüdiger Dillmann, Karlsruhe, Germany Haibin Duan, Beijing, China Gianluigi Ferrari, Parma, Italy Manuel Ferre, Madrid, Spain Sandra Hirche, München, Germany Faryar Jabbari, Irvine, USA Janusz Kacprzyk, Warsaw, Poland Alaa Khamis, New Cairo City, Egypt Torsten Kroeger, Stanford, USA Tan Cher Ming, Singapore, Singapore Wolfgang Minker, Ulm, Germany Pradeep Misra, Dayton, USA Sebastian Möller, Berlin, Germany Subhas Mukhopadyay, Palmerston, New Zealand Cun-Zheng Ning, Tempe, USA Toyoaki Nishida, Sakyo-ku, Japan Bijaya Ketan Panigrahi, New Delhi, India Federica Pascucci, Roma, Italy Tariq Samad, Minneapolis, USA Gan Woon Seng, Nanyang Avenue, Singapore Germano Veiga, Porto, Portugal Haitao Wu, Beijing, China Junjie James Zhang, Charlotte, USA About this Series “Lecture Notes in Electrical Engineering (LNEE)” is a book series which reports the latest research and developments in Electrical Engineering, namely: • • • • • Communication, Networks, and Information Theory Computer Engineering Signal, Image, Speech and Information Processing Circuits and Systems Bioengineering LNEE publishes authored monographs and contributed volumes which present cutting edge research information as well as new perspectives on classical fields, while maintaining Springer’s high standards of academic excellence Also considered for publication are lecture materials, proceedings, and other related materials of exceptionally high quality and interest The subject matter should be original and timely, reporting the latest research and developments in all areas of electrical engineering The audience for the books in LNEE consists of advanced level students, researchers, and industry professionals working at the forefront of their fields Much like Springer’s other Lecture Notes series, LNEE will be distributed through Springer’s print and electronic publishing channels More information about this series at http://www.springer.com/series/7818 Daya K Lobiyal Durga Prasad Mohapatra Atulya Nagar Manmath N Sahoo • • Editors Proceedings of the International Conference on Signal, Networks, Computing, and Systems ICSNCS 2016, Volume 123 Editors Daya K Lobiyal School of Computer and Systems Sciences Jawaharlal Nehru University New Delhi, Delhi India Atulya Nagar Faculty of Science Liverpool Hope University Liverpool UK Durga Prasad Mohapatra Department of Computer Science and Engineering National Institute of Technology Rourkela, Odisha India Manmath N Sahoo Department of Computer Science and Engineering National Institute of Technology Rourkela, Odisha India ISSN 1876-1100 ISSN 1876-1119 (electronic) Lecture Notes in Electrical Engineering ISBN 978-81-322-3587-3 ISBN 978-81-322-3589-7 (eBook) DOI 10.1007/978-81-322-3589-7 Library of Congress Control Number: 2016942038 © Springer India 2016 This work is subject to copyright All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed The use of general descriptive names, registered names, trademarks, service marks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer (India) Pvt Ltd Preface International Conference on Signal, Networks, Computing, and Systems (ICSNCS 2016), organized by School of Computer and Systems Sciences, Jawaharlal Nehru University, India, during February 25–27, 2016, certainly marks a success toward bringing researchers, academicians, and practitioners to the same platform It is indeed a pleasure to receive overwhelming response from researchers of premier institutes of the country and abroad for participating in ICSNCS 2016, which makes our endeavor successful Being the first conference of its series, it was challenging for us to broadcast the conference among researchers and scientists and to receive their valuable works for review A very systematic workflow by the committee has made it possible We have received 296 articles and have selected 73 articles of the highest quality among them for presentation and publication through peer-review done by at least two experts for each article We are unable to accommodate many promising works as we restricted our selection to limited articles which could be elaborately presented in a three-day conference We are thankful to have the advice of dedicated academicians and experts from industry to organize the conference We thank all researchers who participated and submitted their valued works in our conference The articles presented in the proceedings discuss the cutting-edge technologies and recent advances in the domain of the conference We conclude with our heartiest thanks to everyone associated with the conference and seeking their support to organize the next editions of the conference in subsequent years New Delhi, India Rourkela, India Liverpool, UK Rourkela, India Daya K Lobiyal Durga Prasad Mohapatra Atulya Nagar Manmath N Sahoo v Conference Organization General Chair Daya K Lobiyal, Jawaharlal Nehru University, India Organizing Chairs Ram Shringar Rao, Ambedkar Institute of Advanced Communication Technologies and Research, India Sushil Kumar, Jawaharlal Nehru University, India Buddha Singh, Jawaharlal Nehru University, India Program Chairs Manmath N Sahoo, National Institute of Technology, Rourkela, India Zaheeruddin, Jamia Millia Islamia University, India Yulei Wu, University of Exeter, Exeter Program Co-Chairs Sandip Rakshit, Kaziranga University, Assam, India Syed Rizvi, Pennsylvania State University, USA Yogesh H Dandawate, SMIEEE, Vishwakarma Institute of Information Technology, India vii viii Conference Organization Publication Chairs Soubhagya Sankar Barpanda, National Institute of Technology, Rourkela, India Sambit Bakshi, National Institute of Technology, Rourkela, India Area Chairs ASIA: Ompraksh Kaiwartya, Faculty of Computing Universiti Teknologi, Malaysia EUROPE: Atilla Elci, Aksaray University, Turkey USA: Adam Schmidt, Poznan University of Technology, Poland Technical Track Chairs Signal: Binod K Kanaujia, AIACTR, India Networking: Sanjay K Soni, Delhi Technological University, Delhi, India Computing: Nanhay Singh, AIACTR, India Systems: Naveen Kumar, Indira Gandhi National Open University, India Web Chairs Sanjoy Das, Galgotias University, India Rahul Raman, National Institute of Technology, Rourkela, India Technical Program Committee Anand Paul, SMIEEE, Kyungpook National University, Republic of Korea Andrey V Savchenko, National Research University Higher School of Economics, Russia Ch Aswani Kumar, Vellore Institute of Technology, India Dilip Singh Sisodia, National Institute of Technology, Raipur, India Ediz Saykol, Beykent University, Turkey Flavio Lombardi, Roma Tre University of Rome, Italy Jamuna Kanta Sing, SMIEEE, Jadavpur University, India Jaya Sil, Bengal Engineering and Science University, India Conference Organization ix Krishnan Nallaperumal, SMIEEE, Manonmaniam Sundaranar University, India Lopamudra Chowdhury, Jadavpur University, India Narayan C Debnath, Winona State University, USA Nidul Sinha, SMIEEE, National Institute of Technology, Silchar, India Paulo Quaresma, University of Evora, Portugal Patrick Siarry, SMIEEE, Université de Paris, France Pradeep Singh, National Institute of Technology, Raipur, India Raghvendra Mall, University of Leuven, Belgium Rajarshi Pal, Institute for Development and Research in Banking Technology, India Sotiris Kotsiantis, University of Patras, Greece Yogesh H Dandawate, SMIEEE, Vishwakarma Institute of Information Technology, Pune, India Zhiyuan (Thomas) Tan, University of Twente, the Netherlands Organizing Committee Adesh Kumar, Shri Lal Bahadur Shastri Rashtriya Sanskrit Vidyapeetha, India Ajay Sikandar, Jawaharlal Nehru University, India Anil Kumar Sagar, Galgotias University, India Arvind Kumar, Ambedkar Institute of Advanced Communication Technologies and Research, India Ashok Kumar Yadav, Amity School of Engineering and Technology, India Indrani Das, Jawaharlal Nehru University, India Kamlesh Kumar Rana, Galgotias College of Engineering and Technology (GCET), India Karan Singh, Jawaharlal Nehru University, India Mahendra Ram, Jawaharlal Nehru University, India Meenakshi Sihag, Guru Tegh Bahadur Institute of Technology, India Prashant Singh, Northern India Engineering College, India Rajesh Kumar Yadav, Delhi Technological University, India Rameshwar Lal Ujjwal, Guru Gobind Singh Indraprastha University, India Sanjeev Kumar, Ambedkar Institute of Advanced Communication Technologies and Research, India Shailender Kumar, Ambedkar Institute of Advanced Communication Technologies and Research, India Sunil Kumar, Jawaharlal Nehru University, India Suresh Kumar, Ambedkar Institute of Advanced Communication Technologies and Research, India x Conference Organization External Reviewers Ajay Shankar Shukla, Central Council for Research in Ayurvedic Sciences, India Amar Jeet Singh, Himachal Pradesh University, India R Kingsy Grace, Anna University, India Shiv Prakash, Indian Institute of Technology, Delhi, India Snehasis Banerjee, Tata Consultancy Services Research, India Taymaz Farshi, Gazi University, Turkey Omprakash Kaiwartya, Jawaharlal Nehru University, India Xavier Bellekens, University of Strathclyde, Glasgow 334 V Sharma and B Negi Fig a Simulink model of ZSI boost converter circuit b FFT spectrum 1.1 ZSI Boost Operation with Induction Motor Load Figure shows the MATLAB Simulink model of system implemented for boosted output This configuration shows a desirable boost operation of input voltage of 100 V to a high output of 200 V The signature diagram of harmonics using fast Fourier transform is shown in Fig 1b The value of harmonic distortion at fundamental frequency is 41.35 % 1.2 Fault at Gate Terminal of Phase A The Simulink system of condition under consideration is presented in Fig 2a To depict this faulty condition, the gate terminal of MOSFET of one phase is grounded, i.e not provided with gate pulse Introduction to such faults exhibits only one half of distorted output waveform The percentage harmonics measured at 50 Hz is 37.42 % Current Signature Analysis of Single-Phase ZSI-Fed … 335 Fig a Simulink model of with gate grounded b FFT spectrum 1.3 High Resistance Condition Fault This faulty condition resembles open circuiting of the phase A switch In this case, the switch device is replaced by a high resistance of order of mega ohm The current through this device is very small and it leads to high resistance low current fault Figure 3a shows the Simulink model for present faulty condition The obtained output waveform is highly distorted and the % harmonics at operating frequency is 37.42 % Fig a Simulink model for high resistance fault b FFT spectrum 336 V Sharma and B Negi Simulation Study for Buck Operation 2.1 With Induction Motor Load To simulate practical conditions, the above system is simulated for induction motor load The Simulink model for this condition is shown in Fig 4a The output voltage waveform shows a reduced output of 50 V for an input supply of 100 V The measured value of harmonics at fundamental frequency is 431.35 % 2.2 Gate Terminal Grounded Fault Figure 5a shows the Simulink circuit for gate terminal grounded fault under buck operation of CSI In this topology, the gate of phase A MOSFET is deprived of the gate pulse In this faulty condition, only one half of distorted wave is obtained at the load with reverse polarity The percentage value of harmonics at fundamental frequency is 310.18 % 2.3 MOSFET Blown off Fault The simulation equivalent for such circuit is obtained by replacing phase A MOSFET by high resistance as shown in Fig Fig a Simulink diagram of buck converter for IM load b FFT spectrum Current Signature Analysis of Single-Phase ZSI-Fed … 337 Fig a Simulink model of gate terminal grounded fault b FFT spectrum Fig a Simulink model with blown off fault b FFT spectrum This condition depicts the replacement of power electronic switch of phase A with high resistance in the circuit Due to high resistance in the converter side large value of distortion comes and the value of THD at operating frequency is 80.31 % The summary of fault is tabulated in Table This study analyses both modes of operation, i.e boost and buck modes of operation 338 Table Summary of FFT analysis V Sharma and B Negi Type of fault Boost operation No fault Gate grounded High resistance at phase A Buck operation Without fault Gate grounded High resistance at phase A % THD Load current (A) 41.35 36.32 37.42 21 27 28 431.35 310.18 80.31 13 18 22 Conclusion In this study, the variable frequency required for the harmonic control of single-phase AC motor is obtained from single-phase inverter The magnetic saturation is avoided and constant flux operation is considered for the machine The inverter uses PWM technique for voltage control and hence it has low ripples due to harmonics for no fault condition For the faulty conditions, lower order harmonics are removed by switching of the device and the higher order harmonics are neglected by selective harmonic reduction method This study can be extended for three-phase systems with higher value of voltages References Chandana Jayampathi Gajanayak, Fang Lin Luo, Hoay Beng Gooi, Ping LamSo, Lip Kian Siow, “Extended boost Z-source inverters.” IEEE Transactions On Power Electronics, vol 25, no 10, pp 2242–2252 Vivek Sharma, Gaurav Mendiratta, “Harmonic Analysis of CSI-fed Induction Motor Drive”, In Proceedings of the 8th INDIACom 2014 IEEE International Conference on “Computing for Sustainable Global Development”, 2014 Vivek Sharma, Chiranjeev panwar, “Comparative Analysis Of PV Fed Dc-Dc Converters,” in proceedings of IEEE International Conference on Green Computing, Communication and Electrical Engineering (ICGCCEE 2014), 2014 Vivek Sharma, Lokesh Yadav, “Harmonic Analysis of PWM Full Bridge Converter,” in proceedings of IEEE International Conference on Power, Control and Embedded System (ICPCES-2014), 2014 Vivek Sharma, Nikita Rawat, “Comparison of Interleaved Coupled-Inductor Boost Converter with Conventional DC Converters,” in IEEE sponsored 4th International Conference on Computing of Power, Energy & Communication”, ICCPEIC 2015, April 2015 Vivek Sharma, Nikita Rawat, “Fault Diagnosis of Single phase Z-Source Inverter,” International Conference on Advances in Computing & Communication Engineering ICACCE-2015, 2015 B Biswas, S Das, P Purkait, M.S Mandal, D Mitra, “Current Harmonics Analysis of Inverter-Fed Induction Motor Drive System under Fault Conditions”, Proceedings of the International Multi Conference of Engineers and Computer Scientists 2009,Vol II IMECS 2009, March, Hong Kong, ISBN: 978-988-17012-7-5 Kinematic Control of a Mobile Manipulator B.B.V.L Deepak, Dayal R Parhi and Ravi Praksh Abstract Proper motion planning algorithms are necessary for intelligent robotic systems in order to execute their specific tasks To solve this problem, current research work introduces the inverse kinematic models for mobile manipulators In general, a systematic closed-form solution is not available in the case of inverse kinematic models To obtain elucidation for inverse kinematic problem is more complex as compared to direct kinematics problem The current research work aims to combine the functionality of a robot arm with an autonomous platform It means development of an autonomous wheeled mobile robot on which the robot arm is mounted The purpose of this work is to integrate both the segments (i.e., mobile manipulator and mobile platform), such that the system can perform the constrained moves of the arm in the mean while as the platform is moving Á Á Á Keywords Robotic manipulator Wheeled mobile platform Inverse kinematic models End effector constraints Geometric wheel constraints Á Introduction Proper motion planning algorithms are necessary for robotic systems may be of manipulator or mobile platforms, in order to execute their specific tasks [1] Motion planning of industrial robots is a critical issue because of its end effectors path B.B.V.L.Deepak (&) Á D.R Parhi Department of Mechanical Engineering, National Institute of Technology-Rourkela, Rourkela, India e-mail: bbv@nitrkl.ac.in D.R Parhi e-mail: DRKPARHI@nitrkl.ac.in B.B.V.L.Deepak Á R Praksh Department of Industrial Design, National Institute of Technology-Rourkela, Rourkela, India e-mail: 113ID1274@nitrkl.ac.in © Springer India 2016 D.K Lobiyal et al (eds.), Proceedings of the International Conference on Signal, Networks, Computing, and Systems, Lecture Notes in Electrical Engineering 396, DOI 10.1007/978-81-322-3589-7_38 339 340 B.B.V.L Deepak et al constraints [2] Whereas, the motion control of mobile robots or the mechanical behavior of the robot depends upon the wheel geometric constraints while the robot is in motion [3, 4] To sustenance the progress and to enlarge the solicitation potential of robotic manipulators (industrial robotics), it is coherent to integrate locomotion features with manipulation capabilities, hereby developing wheeled mobile manipulators [5, 6] Matched to conventional industrial robotic arms, mobile manipulators adapt to environmental changes for performing wide range of manufacturing tasks Another benefit of this category of robotic systems is that the existing industrial environments not have to be altered or modified as in the case of Automated Guided Vehicles (AGV’s), where permanent cable layouts and/or markers are required for navigation [5] In past [4, 7], authors dealt with kinematic models of wheeled mobile robots to generate trajectory within its environments The developed kinematic models according to the wheel geometric constraints: Wheel sliding constraint and Wheel rolling constraints But the kinematic analysis of manipulators is quite different from as compared to wheeled mobile robots Kinematics deals with joint space coordinates, link reference frames, and end effector reference frames [1, 8] To obtain solutions of inverse kinematics, several algorithms have been developed subjected to end effector constraints [9] Motion planning of mobile robot deals with generation of safest and shortest pats while reaching its target position [10–12] Several motion planning techniques have been developed based on artificial intelligence algorithms [13, 14] But these techniques are not suitable for mobile manipulator control [15, 17, 18] In this paper, we propose inverse kinematic solutions for both the mobility platform and robotic manipulator The purpose of this work is to integrate both the segments (i.e., mobile manipulator and mobile platform), such that the system can perform the constrained moves of the arm in the mean while as the platform is moving Mechanical Design Architecture of Mobile Manipulator The main characteristic of an automated mobile manipulator is its flexible operational workspace Coordinated motion of the manipulator and mobile platform leads to a wide range of redundancy Owing the velocity restrictions enforced on the mobile base, the WMM is a nonholonomic system So it is required to develop a kinematic controller to make the robot system follow a desired end effector and platform trajectories in its workspace coordinates simultaneously In the current research work, a wheeled mobile manipulator is considered with a 4-axis manipulator equipped on a nonholonomic differential wheeled mobile platform For the considered 4-axis manipulator coordinate frames for the manipulator are assigned as shown in Fig and corresponding kinematic parameters are represented in Table Kinematic Control of a Mobile Manipulator 341 Fig Link coordinate frame of the manipulator Table Kinematic parameters of the manipulator Axis h d (mm) a (mm) a h1 h2 h3 h4 d1 ¼ 70 0 d2 ¼ 45 a2 ¼ 100 a3 ¼ 70 a4 ¼ Àp=2 Àp=2 The arm equation is obtained using D–H notation [16] as represented in Eq (4), which is function of h1, h2, h3, and h4 The arm equation consists of six elements; three correspond to the end effector’s position and the remaining three represent yaw, pitch, and roll orientations of the tool Using a homogeneous coordinate transformation matrix, the relation between adjacent links is given in Eq (1) Ti ẳ Rotz; hi ị Transð0; 0; di Þ Ã Transðai ; 0; 0Þ Ã Rotðx; Þ ShSai Chi Chi ÀShi Cai Shi Chi Cai ÀChi Sai Shi 7 ¼6 Sai Cai di 0 1ị 2ị Here, Ci ẳ coshi ị; Si ¼ sinðhi Þ On replacing the kinematic parameters illustrated in Table in Eq (2), individual transformation matrices T01 to T45 can be found and the global transformation matrix T05 of the robot arm is found according to Eq (3) tool wrist tool Tbase ¼ Tbase à Twrist mx my ¼6 mz nx ny nz ox oy oz px py 7 ¼ RðhÞ3x3 pz P3x1 ! ð3Þ 342 B.B.V.L Deepak et al wrist tool where Tbase ¼ T01 à T12 and Twrist ¼ T23 à T34 Where (px ; py ; pz ) represents the position and RðhÞ3Â3 represents the rotation matrix of the end effector Tool configuration is six-dimensional because arbitrary is specified by three position coordinates (x, y, z) and orientation coordinates (yaw, pitch, roll) 9 px > > c1 a2 c2 ỵ a3 c23 À d4 s23 Þ > > > > > > > > > py > > s1 ða2 c2 ỵ a3 c23 d4 s23 ị > > > > > > = > = < < d1 À a2 s2 À a3 s23 À d4 c23 pz ẳ 4ị Xẳ y > ẵexph4 ị=pc1 s23 > > > > > > > > > > > > > > > ẵexph4 ị=ps1 s23 > > ; > ; : p > : r ẵexph4 ị=pc23 The time derivative of the end effector’s position gives the linear velocity of the T end effector The position of the end effector ½ px py pz Š is a function of (h1, h2, h3) because h4 indicates the orientation of the tool 9 < v x = d < px = < h_ = ð5Þ vy ẳ py ẳ ẵJM 33 h_ : ; dt : ; :_ ; vz pz h3 where ½JM Š3Â3 is manipulator velocity Jacobean matrix and is equal to s1 a2 c2 ỵ a3 c23 d4 s23 ị c a c ỵ a c d s Þ 2 23 23 2.1 _ Àa22 s2 c1 À a23 s23 c1 À d4 c23 c1 Àa2 s1 s2 À a3 s1 s23 d4 s1 s23 a3 c23 ỵ d4 s23 Àa3 s23 c1 À d4 c23 c1 s1 ðÀa3 s23 d4 s23 ị 6ị a3 c23 ỵ d4 s23 Inverse Kinematic Model This section describes the development of inverse kinematic models of an arm based on its link coordinate systems From Eq (9), it is observed that there is a possibility of getting two wrist angles (Ỉh3 ) for the same tool position Since the elbow angle (h2 ) depends on h3 , two elbow angles will obtain corresponds to each h3 The base angle can be found easily by Eq (7) À  Á Base angle h1 ẳ arctan py px 7ị where px and py are determined from Eq (8) and from the arm equation, the global pitch angle h23 can be found as follows: h23 ẳ arctanc1 y ỵ s1 pị=r ị 8ị Kinematic Control of a Mobile Manipulator 343 The wrist angle can be found as follows: ÀÀ  Á Á h3 ¼ Æ arccos b2  À a22 À a23 px ð9Þ   where b2  ẳ b21 ỵ b22 ; and b1 ẳ c1 px ỵ c2 py ỵ d4 s23 and b2 ¼ d1 À d4 c23 À pz Once h3 is known then elbow angle h2 can be found from the global pitch angle h23 * h23 ẳ h3 ỵ h2 ) h2 ẳ h23 h3 ð10Þ The final joint parameter h4 can be found from the arm Eq (14) as follows: Tool roll angle h4 ¼ p à ln 2.2 pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ð y þ p2 þ r Þ ð11Þ Velocity Jacobean of Mobile Platform There are three constraints for a differential platform: first one corresponds to move the platform in the direction of axis of symmetry and the remaining two are rolling constraints, not allow the wheels to slip The motion equation of a differential mobile platform is a function of left wheel and right wheel velocities (vLt ; vRt ) as represented in Eq (12) & ' s à cos w s à cos w < x_ = vRt s à sin w à n_ I ẳ y_ ẳ s sin w 12ị vLt : _ ; 2s À1 w While moving the mobile platform with a heading angle w, the following kinematic Eq (13) is used which relates the linear velocity of the mobile platform reference frame to the wheel velocities & Vx Vy ' & ẳ ẵJMP 22 h_ rt h_ lt ' 13ị where ẵJMP 33 is mobile platform velocity Jacobean matrix and h_ rt and h_ lt are angular velocities of right and left wheels, respectively ! cos w cos w Velocity Jacobean matrix ẵJMP ẳ 2r sin w sin w 344 2.3 B.B.V.L Deepak et al Velocity Jacobean of Mobile Manipulator The differential kinematics of the mobile manipulator is obtained by combining the kinematic Eqs (5) and (13) of a 4-axis manipulator and the differential mobile platform as shown in Eq (14) The first three parameters in the above equation relate to the manipulator and the remaining two correspond to the differential platform 9 8 h_ > h_ > > > > > > > > > > > > > = = < h_ > < h_ > ẳ ẵJWMP 55 h_ 14ị fq_ g ẳ h_ > > > > > > > > > h_ rt > > h_ rt > > > > > : _ ; : _ ; hlt hlt where ½JWMP Š is the Velocity Jacobean of Mobile Manipulator and is represented as follows: ½JWMP Š11 ½JWMP Š12 ½JWMP Š13 ½JWMP Š14 ½JWMP Š15 ½JWMP Š21 ½JWMP Š22 ½JWMP Š23 ½JWMP Š24 ½JWMP Š25 7 ẵJWMP ẳ 6 ẵJWMP 31 ẵJWMP 32 ½JWMP Š33 ½JWMP Š34 ½JWMP Š35 ½JWMP Š ½JWMP Š13 ½JWMP Š43 ½JWMP Š44 ½JWMP Š45 13 ½JWMP Š13 ½JWMP Š13 ½JWMP Š53 ½JWMP Š54 ½JWMP Š55 where ẵJWMP 11 ẳ s1 a2 c2 ỵ a3 c23 d4 s23 ị; ẵJWMP 12 ẳ a22 s2 c1 À a23 s23 c1 À d4 c23 c1 ; ½JMP Š13 ¼ Àa3 s23 c1 À d4 c23 c1 ; ½JWMP Š14 ¼ ½JMP Š15 ¼ 0; ½JWMP Š21 ¼ c1 a2 c2 ỵ a3 c23 d4 s23 ị; ½JWMP Š22 ¼ Àa2 s1 s2 À a3 s1 s23 d4 s1 s23 ẵJWMP 23 ẳ s1 a3 s23 d4 s23 ị; ẵJWMP 24 ẳ ẵJMP 25 ẳ 0; ẵJWMP 31 ẳ ẵJWMP 32 ẳ a3 c23 ỵ d4 s23 ; ẵJWMP 33 ẳ a3 c23 ỵ d4 s23 ; ẵJWMP 34 ẳ ẵJMP 35 ẳ ½JWMP Š41 ¼ ½JMP Š42 ¼ ½JMP Š43 ¼ 0; ẵJWMP 44 ẳ ẵJMP 45 ẳ cos wị=2r ẵJWMP 51 ¼ ½JMP Š52 ¼ ½JMP Š53 ¼ 0; ½JWMP Š54 ẳ ẵJMP 55 ẳ sin wị=2r Fig Workspace generated by a Fixed manipulator and b WMM Kinematic Control of a Mobile Manipulator 345 Figure represents the workspace generated by the mobile manipulator, when it is at a specific position The developed hybridized system extends the workspace of a fixed manipulator by two times as shown in Fig Conclusion This study integrates the kinematic models of a 4-axis manipulator and a differential mobile platform The motion of the developed WMM is controlled by five parameters in which three parameters give the velocity information of the manipulator and the remaining two correspond to the differential mobile platform Finally, comparison has been performed in between the theoretical result obtained from the current analysis with the experimental results of a fabricated real mobile manipulator (4 DOF) References Ali T Hasan, A M S Hamouda, N Ismail, H M A A Al-Assadi, (2006) An adaptive-learning algorithm to solve the inverse kinematics problem of a D.O.F serial robot manipulator, Advances in Engineering Software, 37(7), pp 432–438 Deepak, B B V L., Parhi, D R., & Jha, A K (2011) Kinematic Model of Wheeled Mobile Robots Int J on Recent Trends in Engineering & Technology, 5(04) Parhi, D R., & Deepak, B B V L (2011) Kinematic model of three wheeled mobile robot Journal of Mechanical Engineering Research, 3(9), 307–318 Hamner, B., Koterba, S., Shi, J., Simmons R., Singh, S (2009) An autonomous mobile manipulator for assembly tasks, Autonomous Robot, vol 28, pp 131– 149 Deepak, B B V L., Parhi, D R., & Amrit, A (2012) Inverse Kinematic Models for Mobile Manipulators Caspian Journal of Applied Sciences Research, 1(13) Deepak, B B V L., & Parhi, D R (2011) Kinematic Analysis of Wheeled Mobile Robot Automation & Systems Engineering, 5(2) Manfred L Husty,, Martin Pfurner, Hans-Peter Schröcker, (2007), Anew and efficient algorithm for the inverse kinematics of a general serial 6R manipulator, Mechanism and Machine Theory, 42(1), pp 66–81 Dayal R P, Deepak B, Nayak D, Anand A (2012), Forward and Inverse Kinematic Models for an Articulated Robotic Manipulator, International Journal of Artificial Intelligence and Computational Research, (2): 103–109 Deepak, B B V L., Parhi, D R., & Kundu, S (2012) Innate immune based path planner of an autonomous mobile robot Procedia Engineering, 38, 2663–2671 10 Deepak, B B V L., & Parhi, D R (2013, December) Target seeking behaviour of an intelligent mobile robot using advanced particle swarm optimization In Control, Automation, Robotics and Embedded Systems (CARE), 2013 International Conference on (pp 1–6) IEEE 11 E J Van Henten, J Hemming, B A J Van Tuijl, J G Kornet and J Bontsema, (2003), Collision-free Motion Planning for a Cucumber Picking Robot, Biosystems Engineering, 86 (2), pp 135–144 12 Kundu, S., Parhi, R., & Deepak, B B (2012) Fuzzy-neuro based navigational strategy for mobile robot International Journal of Scientific & Engineering Research, 3(6) 346 B.B.V.L Deepak et al 13 Deepak, B B V L., Parhi, D R., & Raju, B M V A (2014) Advance particle swarm optimization-based navigational controller for mobile robot Arabian Journal for Science and Engineering, 39(8), 6477–6487 14 Datta, S., Ray, R., Banerji, D (2008) Development of autonomous mobile robot with manipulator for manufacturing environment, International Journal of Advanced Manufacturing Technology, Vol 38, pp 536‐542 15 Deepak, B B V L (2015), Design and Development of an Automated Mobile Manipulator for Industrial Applications, Ph.D Thesis, National Institute of Technology—Rourkela, http:// ethesis.nitrkl.ac.in/6652/ 16 Eliot, E., Deepak, B., Parhi, D., & Srinivas, J (2013), Design & Kinematic Analysis of an Articulated Robotic Manipulator International Journal of Mechanical and Industrial Engineering, 3(1), 105–108 17 Deepak, B B & Parhi, D (2013) Intelligent adaptive immune-based motion planner of a mobile robot in cluttered environment Intelligent Service Robotics, 6(3), 155–162 18 B.B.V.L Deepak & Dayal R Parhi (2016) Control of an automated mobile manipulator using artificial immune system, Journal of Experimental & Theoretical Artificial Intelligence, 28:1–2, 417–439 Author Index A Achuthan, Krishnashree, 57 Agrawal, Himanshu, 273 Agrawal, Vinod Kumar, 123 Ahmad, Mohammad Oqail, 25 Akhil, Katiki, 261 Azharuddin, Md., B Banerjee, Arundhati, Bansal, Bhavya, 75 Bhatt, Rakesh Mohan, 301 Bidikar, Bharati, 233 Bisht, Vimal Singh, 197 C Chakraborty, Amrita, 155, 225, 317 Chaturvedi, Mayank, 181, 205, 241, 249, 255, 325 Chauhaan, Prateeksha, 205 Chhotray, Animesh, 87, 137 D Das, Manik Lal, 75 Deepak, B.B.V.L., 291, 339 Diwakar, Shyam, 57 G Gandhi, Charu, 43 Ganesh, L., 233 Gupta, Jyoti, Gupta, Manik, 255 H Hemalatha, N., 13 J Jadaun, Neha, 325 Jain, Nidhi, 181 Jana, Prasanta K., Jena, Sanjay Kumar, 171, 281 Jha, Pooja, 95 Juneja, Pradeep K., 181, 189, 197, 205, 241, 249, 255, 325 K Kar, Arpan Kumar, 155, 225, 317 Kartika, C.H.V., 123 Kaur, Moninder, 281 Kaushik, Shweta, 43 Kavyashree, C.K., 123 Khan, Rafiqul Zaman, 25 Kumar, Dhanush, 57 Kumar, Ramesh, 281 Kumar, Sushant, 213 L Lakshmi Narayana Reddy, P., 261 M Maurya, Ajay Kumar, 189 Mohanty, Asit, 105, 115 Mohanty, R.K., 67 Mohanty, Sthitapragyan, 105, 115 N Nagamani, A.N., 123 Nagpal, Bharti, 309 Nair, Bipin, 57 Narayanan, N.K., 13, 147 Negi, Bhawana, 333 Nizar, Nijin, 57 P Pandey, Anish, 137 Pandey, Krishna Kant, 87, 137 Pant, Mohit, 197 Paramita, Pragyan, 105, 115 © Springer India 2016 D.K Lobiyal et al (eds.), Proceedings of the International Conference on Signal, Networks, Computing, and Systems, Lecture Notes in Electrical Engineering 396, DOI 10.1007/978-81-322-3589-7 347 348 Parhi, Dayal R., 87, 137, 339 Patel, Alka, 241 Patel, Jyoti, 241 Patel, Ronak, 75 Pradhan, Manas K., 87 Praksh, Ravi, 339 Prince, Shanthi, 33 R Rajalakshmi, T., 33 RajaSekhar, D., 261 Rajesh, R., 213 Raju, B.M.V.A., 291 Ranjan, Prabhat, 213 Rao, C.A., 291 Ray, Sujay, Rout, Jitendra Kumar, 171 S Sahu, Santosh Kumar, 281 Santosh Kumar, M.N.V.S., 233 Saraswathy, R.M., 123 Sasibhushana Rao, G., 233 Sasidharakurup, Hemalatha, 57 Author Index Sharma, A., 325 Sharma, Vivek, 333 Shree, Shweta, 189 Singh, Abhaya Pal, 273 Singh, P.K., 291 Singh, Sameer Kumar, 181 Singh, Smriti, 171 Smitha, C.K., 147 Sooraj, T.R., 67 Sreekar Reddy, M.B.S., 261 Sridharan, Aadityan, 57 Sridhar Patnaik, K., 95 Sunori, Sandeep Kumar, 189, 197 T Tripathy, B.K., 67 V Vigneshwar, P., 261 Viswavandya, Meera, 105, 115 W Wadhwa, Vinayak, 309 ... Protein Leads … Table Ionic interactions among gp 120 and CD4 after the duo and trio complex formation Position gp 120 -CD4 14 130 21 0 28 9 gp 120 -CD4-CCR5 23 28 9 50 21 0 130 14 Protein G and Protein C represents... in pink and green shades (colour online) 3 .2 Analysis of Conformational Transitions in gp 120 The conformational switching in the gp 120 HIV protein at S1, S2, and S3 stages was evaluated and compared... consequently Therefore, the present study indulged into the molecular and computational basis of HIV entry The structural and computational molecular contribution of gp 120 and its interactions