RITU MAITY

@cttc.gov.in

Senior Engineer
CTTC,Bhubaneswar



              

https://researchid.co/ritu1991

RESEARCH INTERESTS

Mechanical design, drone design, machine learning, advance manufacturing

9

Scopus Publications

68

Scholar Citations

4

Scholar h-index

3

Scholar i10-index

Scopus Publications


  • Autonomous Vehicle Utilizing Deep Learning Methods
    Sresthasa Mohanty, Ritu Maity, and Satya Ranjan Pattanaik
    IEEE
    In today’s fast-paced world, individuals are constantly seeking ways to optimize their time and safety, especially during commutes and travel. Time management, traffic congestion, and safety are critical aspects of driving that have driven researchers to develop autonomous vehicles. A critical challenge in developing autonomous vehicles is achieving reliable lateral motion control. This paper addresses this issue by leveraging the deep learning techniques, and specifically explores the benefits of the NVIDIA Udacity car simulator. Our approach involves training a convolutional neural network (CNN) model to simulate the human driving behavior by utilizing a dataset of images and corresponding steering angles recorded during manual driving sessions in the simulator. It also emphasizes the importance of preprocessing the visual data to enhance the accuracy of the steering predictions. Our model is capable of managing complex driving scenarios within a simulated environment without the risks associated with real-world testing. A Mean Squared Error of 0.0123422 and an R-squared value of 0.8587687 suggest that our model is highly effective at navigating the car across different unfamiliar tracks.

  • A hybrid reinforcement learning and PSO approach for route discovery of flying robots
    Ritu Maity, Ruby Mishra, Prasant Kumar Pattnaik, and Nguyen Thi Dieu Linh
    IGI Global
    Route discovery for flying robots is one of the major concerns while developing an autonomous aerial vehicle. Once a path planning algorithm is built and the flying robot reaches the destination point from the target point successfully, it is again important for the flying robot to come back to its original position and that is done through route discovery algorithms. Reinforcement learning is one of the popular machine learning methods in which the flying robot has to interact with the environment and learn by exploring the possibilities and maximum reward point method, without the requirement of a large amount of prior training data. Particle swarm optimization is an artificial intelligence inspired algorithm which finds optimal solution in a multi-dimensional space. This chapter has discussed a random exploration reinforcement learning approach combined with PSO algorithm that has been used to discover the optimum path for a flying robot to return from the destination point to the target point after it had traversed its best path from an already defined swarm intelligence technique. PSO+Reinforcement Learning (RL-PSO) is an optimization technique that combines the global search capability of PSO with the exploitation and exploration strategy of RL. Here higher reward points were assigned to the already defined best path obtained from the path planning technique, so that while returning from the destination point it will try to find the route with the highest reward point. With several iterations, it will optimize and find the best route for backpropagation. The algorithm is built using a python environment and the convergence result with the number of iterations has been validated.

  • Detection of damaged inserts of cutting tools using deep learning
    Ritu Maity
    IGI Global
    Industrial manufacturing has become increasingly mechanized in recent years. The manufacturing productivity and costs of products are significantly impacted by machine cutting tools, which are a crucial component of industrial production. Tool breakage frequently happens suddenly and without warning in a practical manufacturing process, leading to an unusually unbalanced ratio of tool breakage samples to normal samples. Considering the need of current scenario of development of smart system in production units, the authors have proposed a deep learning-based model for prediction of damaged inserts which can give accurate results as compared to traditional techniques and manual inspection methods. The real time data of damaged tool and undamaged tools were collected, and the model training was done to predict defective inserts with high accuracy.

  • Flying robot path planning techniques and its trends
    Ritu Maity, Ruby Mishra, and Prasant Kumar Pattnaik
    Elsevier BV

  • CRITIQUE OF DESIGN CHALLENGE OF FLYING ROBOTS
    Ritu Maity, Ruby Mishra, and Prasant Kumar Pattnaik
    National Taiwan University
    Flying robots popularly known as drones or UAVs are emerging technologies of the current era. A significant amount of research work has been undertaken in this area in the last few years. Considering the current scenario where aerial vehicles are taking a major part of the market it is important to have an effective and robust design of flying robots. This paper aims to examine the categories of flying robots based on the features that include a range from petite to large and its body structure, wing designs, tail design, propulsion system, and gripper mechanisms along with the associated materials and manufacturing techniques. Again the work is intended to review the respective challenges faced by each category. Mostly the challenges faced by flying robots are design challenges, material selection, and fabrication challenges which are discussed in the paper. In this paper, we have summarized various designs of flying robots developed to date as well as we have focused on major features to be taken care of while designing flying robots. This paper has tried to focus on different design aspects and challenges faced by flying robots so that further research can be carried out to develop effective flying robots in the future.

  • Design and Analysis of Hybrid Fixed-Wing Type Flying Robot
    Ritu Maity, Ruby Mishra, Prashant Kumar Patnaik, and Mangal Sain
    Hindawi Limited
    With the advent of disruptive technologies, unmanned aerial vehicles have seen substantial growth over the past few years. The market for flying robots is increasing drastically, and they are getting used in various sectors. This paper is aimed at discussing the novel design of a hybrid fixed-wing type flying robot in which both fixed-wing and rotary-wing concepts are combined so that stable flight with vertical takeoff can be possible. Our design proposes a compact structure that can be efficiently used in indoor applications. We have also discussed its structural analysis, the model’s stability, the CFD analysis, and the vibrational analysis of the designed structure. The objective is to design an effective compact flying robot system that will be used for medical applications and need to carry a payload of a minimum of 2 kg with good aerodynamic performance. The aerodynamic model required for a hybrid fixed-wing type flying robot has been developed, and the static stability of the model has been evaluated in the paper.

  • A Review of Flying Robot Applications in Healthcare
    Ritu Maity, Ruby Mishra, and Prasant Kumar Pattnaik
    Springer Singapore

  • An Approach for Detection of Dust on Solar Panels Using CNN from RGB Dust Image to Predict Power Loss
    Ritu Maity, Md. Shamaun Alam, and Asutosh Pati
    Springer International Publishing

RECENT SCHOLAR PUBLICATIONS

  • Analysis of Path Finding Techniques for Flying Robots through Intelligent Decision-Making Algorithms in Quantum Inspired Computing Environment
    R Maity, R Mishra, PK Pattnaik
    Wireless Personal Communications 135 (3), 1561-1580 2024

  • Intelligent door unlock system using AI MediaPipe
    C Dutta, R Maity
    International Journal of Data Informatics and Intelligent Computing 3 (1), 36-43 2024

  • Autonomous Vehicle Utilizing Deep Learning Methods
    RMSRP S. Mohanty
    2024 International Conference on Intelligent Computing and Sustainable 2024

  • Selection of sustainable material for the construction of UAV aerodynamic wing using MCDM technique
    R Maity, R Mishra, PK Pattnaik, A Pandey
    Materials today: proceedings 2023

  • BAT inspired regression model for prediction of power loss in solar pane
    R Maity
    Journal of Artificial Intelligence and Systems 5, 125-138 2023

  • A Hybrid Reinforcement Learning and PSO Approach for Route Discovery of Flying Robots
    R Maity, R Mishra, PK Pattnaik, NTD Linh
    Risk Detection and Cyber Security for the Success of Contemporary Computing 2023

  • Detection of Damaged Inserts of Cutting Tools Using Deep Learning
    R Maity
    Sustainable Science and Intelligent Technologies for Societal Development 2023

  • Flying robot path planning techniques and its trends
    R Maity, R Mishra, PK Pattnaik
    Materials Today: Proceedings 80, 2187-2192 2023

  • Critique of design challenge of flying robots
    R Maity, R Mishra, PK Pattnaik
    Biomedical Engineering: Applications, Basis and Communications 34 (06), 2230002 2022

  • Automatic face detection attendance system
    R Maity
     2022

  • Design and Analysis of Hybrid Fixed‐Wing Type Flying Robot
    R Maity, R Mishra, PK Patnaik, M Sain
    Wireless Communications and Mobile Computing 2022 (1), 3978898 2022

  • A review of flying robot applications in healthcare
    R Maity, R Mishra, PK Pattnaik
    Smart Healthcare Analytics: State of the Art, 103-111 2022

  • An approach for detection of dust on solar panels using CNN from RGB dust image to predict power loss
    R Maity, M Shamaun Alam, A Pati
    Cognitive Computing in Human Cognition: Perspectives and Applications, 41-48 2020

MOST CITED SCHOLAR PUBLICATIONS

  • A review of flying robot applications in healthcare
    R Maity, R Mishra, PK Pattnaik
    Smart Healthcare Analytics: State of the Art, 103-111 2022
    Citations: 18

  • An approach for detection of dust on solar panels using CNN from RGB dust image to predict power loss
    R Maity, M Shamaun Alam, A Pati
    Cognitive Computing in Human Cognition: Perspectives and Applications, 41-48 2020
    Citations: 18

  • Flying robot path planning techniques and its trends
    R Maity, R Mishra, PK Pattnaik
    Materials Today: Proceedings 80, 2187-2192 2023
    Citations: 15

  • Selection of sustainable material for the construction of UAV aerodynamic wing using MCDM technique
    R Maity, R Mishra, PK Pattnaik, A Pandey
    Materials today: proceedings 2023
    Citations: 8

  • Design and Analysis of Hybrid Fixed‐Wing Type Flying Robot
    R Maity, R Mishra, PK Patnaik, M Sain
    Wireless Communications and Mobile Computing 2022 (1), 3978898 2022
    Citations: 4

  • Intelligent door unlock system using AI MediaPipe
    C Dutta, R Maity
    International Journal of Data Informatics and Intelligent Computing 3 (1), 36-43 2024
    Citations: 2

  • Critique of design challenge of flying robots
    R Maity, R Mishra, PK Pattnaik
    Biomedical Engineering: Applications, Basis and Communications 34 (06), 2230002 2022
    Citations: 2

  • Analysis of Path Finding Techniques for Flying Robots through Intelligent Decision-Making Algorithms in Quantum Inspired Computing Environment
    R Maity, R Mishra, PK Pattnaik
    Wireless Personal Communications 135 (3), 1561-1580 2024
    Citations: 1