P
Prabakaran Veerajagadheswar
Researcher at Singapore University of Technology and Design
Publications - 21
Citations - 310
Prabakaran Veerajagadheswar is an academic researcher from Singapore University of Technology and Design. The author has contributed to research in topics: Robot & Motion planning. The author has an hindex of 7, co-authored 16 publications receiving 154 citations. Previous affiliations of Prabakaran Veerajagadheswar include National University of Singapore.
Papers
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Journal ArticleDOI
Complete Path Planning for a Tetris-Inspired Self-Reconfigurable Robot by the Genetic Algorithm of the Traveling Salesman Problem
Anh Vu Le,Manimuthu Arunmozhi,Prabakaran Veerajagadheswar,Ping-Cheng Ku,Tran Hoang Quang Minh,Vinu Sivanantham,Rajesh Elara Mohan +6 more
TL;DR: This paper proposes a navigation strategy that accomplishes complete path planning for a Tetris-inspired hinge-based self-reconfigurable robot (hTetro), and proposes a genetic algorithm (GA) as a strong candidate to solve the waypoint sequencing problem (TSP).
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Coverage Path Planning for Decomposition Reconfigurable Grid-Maps Using Deep Reinforcement Learning Based Travelling Salesman Problem
Phone Thiha Kyaw,Aung Paing,Theint Theint Thu,Rajesh Elara Mohan,Anh Vu Le,Prabakaran Veerajagadheswar +5 more
TL;DR: In this article, the authors proposed a novel approach to solve the coverage path planning problem in large complex environments based on the Travelling Salesman Problem (TSP) and Deep Reinforcement Learning (DRL) leveraging the grid-based maps.
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A Self-Organizing Fuzzy Logic Classifier for Benchmarking Robot-Aided Blasting of Ship Hulls
M. A. Viraj J. Muthugala,Anh Vu Le,Eduardo Sanchez Cruz,Mohan Rajesh Elara,Prabakaran Veerajagadheswar,Madhu Kumar +5 more
TL;DR: A novel robotic system that can synthesize a benchmarking map for a previously blasted ship hull, using a Self-Organizing Fuzzy logic (SOF) classifier to benchmark the blasting quality of a ship hull similar to blasting quality categorization done by human experts is proposed.
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Reinforcement learning-based optimal complete water-blasting for autonomous ship hull corrosion cleaning system
Anh Vu Le,Anh Vu Le,Phone Thiha Kyaw,Phone Thiha Kyaw,Prabakaran Veerajagadheswar,M. A. Viraj J. Muthugala,Mohan Rajesh Elara,Madhu Kumar,Nguyen Huu Khanh Nhan +8 more
TL;DR: A complete waypoint path planning (CWPP) to re-blast the self-synthesizing deep convolutional neural network (DCNN) based corrosion heatmap by initial-blasting is proposed for a novel robot platform named Hornbill with the adhesion mechanism by permanent magnetic, self-localization by sensor fusion to navigate smoothly on a vertical surface.
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A Tiling-Theoretic Approach to Efficient Area Coverage in a Tetris-Inspired Floor Cleaning Robot
TL;DR: An innovative application of the polyomino tiling theory is applied to Tetris-inspired reconfigurable robotic cleaning device as a means of solving the area coverage problem.