Browsing by Author "Padman, A."

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    A realistic simulation platform for multi-quadcopter search using downward facing cameras
    (Elsevier Ltd, 2019) D’Souza, J.M.; Guruprasad, K.R.; Padman, A.
    This paper presents a cross platform simulation environment, in a hybrid centralized-decentralized architecture, for multi-quadcopter search problem developed using MATLAB and Gazebo simulator in Robot Operating System (ROS) environment. Multiple quadcopters equipped with downward facing camera are deployed in a search area to gather information such as presence of targets of interest. Search is modeled as reducing uncertainty density, a metric of lack of information about the presence (or absence) of the targets of interest. The simulation platform developed will be a very useful tool for conducting realistic simulation experiments to validate the proposed search strategy and to make a comparative study of its performance in terms of time for the search process, with parameters such as camera search effectiveness models, sensor range, the number of robots, to decide on the parameters best suited for a given situation. We provide simulation results demonstrating the proposed search strategy using the developed simulation environment. © 2019
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    Simultaneous exploration and coverage by a mobile robot
    (2020) Mohammad, Minhaz, Falaki, P.M.; Padman, A.; Nair, V.G.; Guruprasad, K.R.
    In this paper, we propose a problem of simultaneous exploration and coverage for a mobile robot, combining the problems of area coverage with exploration and mapping. The primary task here is to completely cover an initially unknown region. Here we combine the advantages of online and off-line coverage path planning algorithms by using the exploration as an aid. The robots perform intermittent exploration during coverage in order to update the map of the environment, which in turn is used to generate the coverage path. We illustrate and demonstrate the problem using the off-line version of Spanning Tree Coverage algorithm with a frontier-based exploration strategy. The simulation results demonstrate that the robot successfully achieves complete and non-repetitive coverage. � 2020, Springer Nature Singapore Pte Ltd.
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    Simultaneous exploration and coverage by a mobile robot
    (Springer Verlag service@springer.de, 2020) Mohammad Minhaz Falaki, P.M.; Padman, A.; Nair, V.G.; Guruprasad, K.R.
    In this paper, we propose a problem of simultaneous exploration and coverage for a mobile robot, combining the problems of area coverage with exploration and mapping. The primary task here is to completely cover an initially unknown region. Here we combine the advantages of online and off-line coverage path planning algorithms by using the exploration as an aid. The robots perform intermittent exploration during coverage in order to update the map of the environment, which in turn is used to generate the coverage path. We illustrate and demonstrate the problem using the off-line version of Spanning Tree Coverage algorithm with a frontier-based exploration strategy. The simulation results demonstrate that the robot successfully achieves complete and non-repetitive coverage. © 2020, Springer Nature Singapore Pte Ltd.