Intelligent Control, Robotics, and Industrial Automation

Dr. Sanjay Sharma received a B.Tech. (Hons.) in Electrical Engineering from the Indian Institute of Technology (IIT) Kharagpur, M.Tech. degree with distinction in Control Systems (Electrical Engineering) from the Indian Institute of Technology Varanasi (IIT-BHU). He received his Ph.D. degree in Systems and Control Engineering from the University of Sheffield, the UK in 2000. He completed Postgraduate Certificate in Higher Education Teaching (PGCHET) course from Queen’s University Belfast in the year 2004. Currently, he serves as Associate Professor, in Intelligent Autonomous Control Systems, School of Engineering, Computing and Mathematics (Faculty of Science and Engineering) at the University of Plymouth, United Kingdom. He was invited as one of the five International Experts along with colleagues from TAMU USA, MIT USA, UiT Norway, and IST Portugal to assist in the control systems technology of IIT Madras’s initiative to open a Centre for Marine Autonomous Systems. Hehas published more than 50 referable journal papers and more than 50 conference papers in the area of marine, control, and AI. He has supervised 10 Ph.D. and 1 M.Phil. students. His current research activities include the use of AI techniques such as genetic algorithms, fuzzy logic, and neural networks for modeling and the design of novel control systems for industrial and marine plants, particularly for wave energy devices, robotics, automobiles, and uninhabited marine vehicles for both surface and underwater operations. Prof. Bidyadhar Subudhi received a Bachelor of Electrical Engineering from the National Institute of Technology (NIT) Rourkela, M.Tech. degree in Control and Instrumentation from the Indian Institute of Technology (IIT) Delhi and a Ph.D. degree in Control System Engineering from the University of Sheffield, the UK in 2002. He served as a Post-Doctoral Research Fellow at the National University of Singapore (NUS). Currently, he serves as aProfessor, at the School of Electrical Sciences, and Dean (R&D) at IIT Goa. He was a recipient of the prestigious Samanta Chandra Sekhar Award of the Odisha Bigyan Academy, Government of Odisha for his contribution to science and technology. He was awarded NITRAA Research Excellence Award in Electrical Sciences. He is a Fellow of the Indian National Academy of Engineering and a Fellow of IET (UK) and Fellow of Asia-Pacific Artificial Intelligence Association. He has supervised 40 Ph.D. theses. His research interests include system & control, PV & microgrid systems, and autonomous underwater vehicles. He featured in the top 2% of scientists in the field of industrial engineering and automation in 2020 as per Stanford University’s study group. Dr. Umesh Kumar Sahu received his Bachelor of Electronics and Telecommunication Engineering from Pandit Ravishankar Shukla University, India, and his M.Tech. degree in Instrumentation and Control Engineering from Chhattisgarh Swami Vivekanand Technical University, India. He received his Ph.D. degree in Robotics and Machine Vision from the National Institute of Technology (NIT) in Rourkela, India in 2020. Currently, he serves as an Assistant Professor in the Department of Mechatronics, Manipal Institute of Technology, Manipal Academy of Higher Education, India. He has published 16 papers in reputed journals and international conferences. He also has 3 IPRs (Copyrights) under literary work. He received two best paper awards in TENCON-2017 and IRIA-2021. He is a Fellow of the IETE India, and a Member of Young Professional Activity Group (YPAG) in ACDOS. He is a Member in The Robotics Society (TRS), IAENG Hong Kong, IAOE, and an Editorial Member in AJAI. He has supervised a total of 27 undergraduate/postgraduate students. His research interests include robotics and machine vision, image processing, instrumentation and control, network control systems, control of flexible robot manipulators, industrial automation, and intelligent robotic control.

• Landmark Detection for Auto Landing of Quadcopter using YOLOv5.- ROS-based Evaluation of SLAM algorithms and Autonomous Navigation for a Mecanum Wheeled Robot.- An Autonomous Home Assistant Robot for Elderly Care.- 3-D Mapping using Multi-Agent Systems.- Design of Robotic Platform for ADAS Testing.- Design of a novel tree-type robot for pipeline repair.- Comparative Empirical Analysis of Biomimetic Curvy Legged Bipedal Robot with Linear Legged Bipedal Robot.- Energy based Approach for Robot Trajectory Selection in Task Space.- A novel collision avoidance system for two-wheeler vehicles with an automatic gradual brake mechanism.- Development of a Digital Twin Interface for a Collaborative Robot.- Fixed-Time Information Detection based Secondary Control Strategy for Low Voltage Autonomous Microgrid.- Approximation of Standalone Boost-Converter Enabled Hybrid Solar-Photovoltaic Controller System.- Trajectory Tracking with RBF Network Estimator and Dynamic Adaptive SMC Controller for RobotManipulator.- Simplified Current Control Method for FOC of Permanent Magnet Synchronous Motor.- Reference spectrum tracking for circadian entrainment.- Error Minimization Based Order Diminution of Interconnected Wind Turbine Generator.- AR and IoT Integrated Machine Environment (AIIME).- Development of affordable smart and secure multilayer locker system for domestic applications.- IoT and ML-based personalised healthcare system for heart patients.