Subhra Kanti Das

Work place: Robotics & Automation, CSIR-CMERI, M G Avenue, Durgapur, WB, INDIA, PIN-713209

E-mail: subhrakanti.das82@gmail.com

Website:

Research Interests: Process Control System, Computer Architecture and Organization, Software Engineering, Software Deployment, Software Construction, Software

Biography

Subhra Kanti Das (1982,-) male, West Bengal, India, Scientist, received the Bachelor of Engineering in Computer Science and Engineering from University of Kalyani, West Bengal, India in 2004. He is a PhD scholar at department of CSE in University of Jadavpur, West Bengal, India. His research interests include probabilistic measures towards navigation and localization of underwater mobile robotic systems, and application of AI techniques in development of control software architecture. He is the recipient of Young Engineer Award from Institution of Engineers India (IEI) in 2011.

Author Articles
Stochastic Characterization of a MEMs based Inertial Navigation Sensor using Interval Methods

By Subhra Kanti Das Dibyendu Pal Virendra Kumar S. Nandy Kumardeb Banerjee Chandan Mazumdar

DOI: https://doi.org/10.5815/ijigsp.2015.07.04, Pub. Date: 8 Jun. 2015

The aim here remains to introduce effectiveness of interval methods in analyzing dynamic uncertainties for marine navigational sensors. The present work has been carried out with an integrated sensor suite consisting of a low cost MEMs inertial sensor, GPS receiver of moderate accuracy, Doppler velocity profiler and a magnetic fluxgate compass. Error bounds for all the sensors have been translated into guaranteed intervals. GPS based position intervals are fed into a forward-backward propagation method in order to estimate interval valued inertial data. Dynamic noise margins are finally computed from comparisons between the estimated and measured inertial quantities It has been found that the intervals as estimated by proposed approach are supersets of 95% confidence levels of dynamic errors of accelerations. This indicates a significant drift of dynamic error in accelerations which may not be clearly defined using stationary error bounds. On the other side bounds of non-stationary error for rate gyroscope are found to be in consistence with the intervals as predicted using stationary noise coefficients. The guaranteed intervals estimated by the proposed forward backward contractor, are close to 95% confidence levels of stationary errors computed over the sampling period.

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Formulation of FISPLAN: A Fuzzy Logic based Reactive Planner for AUVs towards Situation Aware Control

By Subhra Kanti Das Dibyendu Pal

DOI: https://doi.org/10.5815/ijisa.2013.09.06, Pub. Date: 8 Aug. 2013

The paper presents a detailed discussion on the structural organisation of a Fuzzy Inference System Planner (FISPLAN) for Autonomous Underwater Vehicles (AUVs), including elaboration of membership functions for the inputs as well as outputs. The inference mechanism is detailed with discussions on the rule base, which in essence incorporates the planning logic. In order to assess the effectiveness of the planner as a means of reactive escape under critical situations, a case study is studied with reference to a state of the art AUV. An approximate subsea current model is developed from field observations, and residual energy is estimated by referring to a typical Lithium-polymer cell discharge characteristic together with data recorded in actual field trials. Situations are simulated by considering different combinations of sea-currents as well as status of resident energy. Results reveal that the simulated system, by virtue of the planner, is capable of perceiving situations, thereby realizing their imminence and making a decisive action thereupon. In concise, the fuzzy planner may be considered to provide human-like perception of situations on the basis of crisp observations. Furthermore dynamics of the system are modelled with actual parameters, and subsequently controller responses for pitching and velocity correction are illustrated. Choice of planning interval is also expressed as a function of the controllers' response.

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