Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
4 results
Search Results
Item 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. © 2019Item GeoDesic-VPC: Spatial partitioning for multi-robot coverage problem(Acta Press journals@actapress.com, 2020) Nair, V.G.; Guruprasad, K.R.In this paper, we address a problem of area coverage using multiple cooperating robots using a “partition and cover" approach, where the area of interest is decomposed into as many cells as the robots, and each robot is assigned the task of covering a cell. While the most partitioning approaches used in the literature in the context of a robotic coverage problem may result in topologically disconnected cells in the presence of obstacles leading to incomplete coverage, we propose to use geodesic distance-based generalization of the Voronoi partition, ensuring that each cell that is allotted for a robot for coverage is a topologically connected region, and hence, achieving a complete coverage. The proposed multi-robot coverage strategy is demonstrated with simulation in MATLAB and V-rep simulator, using two single-robot coverage algorithms reported in the literature, namely boustrophedon decomposition-based coverage and spanning tree-based coverage algorithms. © 2020 SAE International. All rights reserved.Item GM-VPC: An Algorithm for Multi-robot Coverage of Known Spaces Using Generalized Voronoi Partition(Cambridge University Press, 2020) Nair, V.G.; Guruprasad, K.R.SUMMARY In this paper we address the problem of coverage path planning (CPP) for multiple cooperating mobile robots. We use a 'partition and cover' approach using Voronoi partition to achieve natural passive cooperation between robots to avoid task duplicity. We combine two generalizations of Voronoi partition, namely geodesic-distance-based Voronoi partition and Manhattan-distance-based Voronoi partition, to address contiguity of partition in the presence of obstacles and to avoid partition-boundary-induced coverage gap. The region is divided into 2D×2D grids, where D is the size of the robot footprint. Individual robots can use any of the single-robot CPP algorithms. We show that with the proposed Geodesic-Manhattan Voronoi-partition-based coverage (GM-VPC), a complete and non-overlapping coverage can be achieved at grid level provided that the underlying single-robot CPP algorithm has similar property.We demonstrated using two representative single-robot coverage strategies, namely Boustrophedon-decomposition-based coverage and Spanning Tree coverage, first based on so-called exact cellular decomposition and second based on approximate cellular decomposition, that the proposed partitioning scheme completely eliminates coverage gaps and coverage overlaps. Simulation experiments using Matlab and V-rep robot simulator and experiments with Fire Bird V mobile robot are carried out to validate the proposed coverage strategy. © © Cambridge University Press 2019.Item MR-SimExCoverage: Multi-robot Simultaneous Exploration and Coverage(Elsevier Ltd, 2020) Nair, V.G.; Guruprasad, K.R.In this paper, we present a novel problem of simultaneous exploration and area coverage by multiple cooperating mobile robots. As the robots cover an initially unknown region, they perform intermittent exploration of the region and build a map, which in turn is used to plan the coverage path. We use a Voronoi partition based multi-robot coverage strategy using the Manhattan distance metric to solve the coverage problem and a frontier based exploration strategy for exploration mapping. We provide results of simulation using Matlab/V-rep environments to demonstrate the proposed multi-robot simultaneous exploration and coverage (MR-SimExCoverage) problem using the spanning tree based coverage (STC) algorithm. © 2020 Elsevier Ltd