Faculty Publications
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Publications by NITK Faculty
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Item Distributed, complete, multi-robot coverage of initially unknown environments using repartitioning(International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) info@ifaamas.org, 2014) Hungerford, K.; Dasgupta, P.; Guruprasad, K.R.We consider the problem of coverage path planning by multiple robots in an environment where the location and geometry of obstacles are initially unknown to the robots. We propose a novel algorithm where the robots initially partition the environment using Voronoi partitioning. Each robot then uses an auction-based algorithm to reallocate inaccessible portions of its initial Voronoi cell to robots in neighboring Voronoi cells so that each robot is responsible for covering a set of contiguous connected regions. We have verified the performance of our algorithm on e-puck robots within the Webots simulator in different environments with different obstacle geometries and shown that it performs complete, non-overlapping coverage. © © 2014, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.Item Automated multi-agent search using centroidal Voronoi configuration(2011) Guruprasad, K.R.; Ghose, D.This paper addresses the problem of automated multiagent search in an unknown environment. Autonomous agents equipped with sensors carry out a search operation in a search space, where the uncertainty, or lack of information about the environment, is known a priori as an uncertainty density distribution function. The agents are deployed in the search space to maximize single step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for the proposed sequential deploy and search strategy. It is shown that with the proposed control law the agent trajectories converge in a globally asymptotic manner to the centroidal Voronoi configuration. Simulation experiments are provided to validate the strategy. © 2010 IEEE.Item Performance of a class of multi-robot deploy and search strategies based on centroidal voronoi configurations(2013) Guruprasad, K.R.; Ghose, D.This article considers a class of deploy and search strategies for multi-robot systems and evaluates their performance. The application framework used is deployment of a system of autonomous mobile robots equipped with required sensors in a search space to gather information. The lack of information about the search space is modelled as an uncertainty density distribution. The agents are deployed to maximise single-step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for sequential deploy and search (SDS) and combined deploy and search (CDS) strategies. Completeness results are provided for both search strategies. The deployment strategy is analysed in the presence of constraints on robot speed and limit on sensor range for the convergence of trajectories with corresponding control laws responsible for the motion of robots. SDS and CDS strategies are compared with standard greedy and random search strategies on the basis of time taken to achieve reduction in the uncertainty density below a desired level. The simulation experiments reveal several important issues related to the dependence of the relative performances of the search strategies on parameters such as the number of robots, speed of robots and their sensor range limits. © 2013 Taylor & Francis Group, LLC.Item Heterogeneous locational optimisation using a generalised Voronoi partition(2013) Guruprasad, K.R.; Ghose, D.In this paper a generalisation of the Voronoi partition is used for locational optimisation of facilities having different service capabilities and limited range or reach. The facilities can be stationary, such as base stations in a cellular network, hospitals, schools, etc., or mobile units, such as multiple unmanned aerial vehicles, automated guided vehicles, etc., carrying sensors, or mobile units carrying relief personnel and materials. An objective function for optimal deployment of the facilities is formulated, and its critical points are determined. The locally optimal deployment is shown to be a generalised centroidal Voronoi configuration in which the facilities are located at the centroids of the corresponding generalised Voronoi cells. The problem is formulated for more general mobile facilities, and formal results on the stability, convergence and spatial distribution of the proposed control laws responsible for the motion of the agents carrying facilities, under some constraints on the agents speed and limit on the sensor range, are provided. The theoretical results are supported with illustrative simulation results. © 2013 Taylor & Francis Group, LLC.Item Effectiveness-based Voronoi partition: A new tool for solving a class of location optimization problems(2013) Guruprasad, K.R.In this article we provide a framework for optimal placement or deployment of facilities in a region of interest. We present a generalization of Voronoi partition, where functions modeling the effectiveness of facilities are used in the place of the usual distance measure used in the standard Voronoi partition and its variations. We illustrate the usefulness of the generalization in designing strategies for optimal deployment of multiple vehicles equipped with sensors, optimal placement of base stations in a cellular network design problem, and locational optimization of power plants. © 2012 Springer-Verlag.Item 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