RITU MAITY
@cttc.gov.in
Senior Engineer
CTTC,Bhubaneswar
RESEARCH INTERESTS
Mechanical design, drone design, machine learning, advance manufacturing
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
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.
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.
Ritu Maity, Ruby Mishra, and Prasant Kumar Pattnaik
Elsevier BV
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.
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.
Ritu Maity, Ruby Mishra, and Prasant Kumar Pattnaik
Springer Singapore
Ritu Maity, Md. Shamaun Alam, and Asutosh Pati
Springer International Publishing