Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item 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.Item Manhattan distance based Voronoi partitioning for efficient multi-robot coverage(Springer Verlag service@springer.de, 2020) Nair, V.G.; Guruprasad, K.R.In this paper we address the problem of area coverage using multiple cooperating robots. One of the main concerns of using multiple robots is of avoiding repetitive coverage apart from complete coverage of the given area. Partitioning the area to be covered into cells and allotting one each cell to each of the robots for coverage is a simple and elegant solution for this problem. However, the spacial partitioning may lead to additional problems leading to either incomplete coverage or coverage overlap near the partition boundary. We propose a manhattan distance based Voronoi partitioning scheme of 2 D× 2 D gridded region, where D is the size of the robot footprint. We show that the proposed partitioning scheme completely eliminates coverage gaps and coverage overlap using illustrative results. © 2020, Springer Nature Singapore Pte Ltd.Item Multi-robot coverage using Voronoi partitioning based on geodesic distance(Springer Verlag service@springer.de, 2020) Nair, V.G.; Guruprasad, K.R.In this paper we propose Geodesic-VPC, a “partition†and “cover†strategy for a multi-robot system using Voronoi partitioning based on geodesic distance metric in the place of the usual Euclidean distance. Each robot is responsible for covering the corresponding geodesic-Voronoi cell using a single-robot coverage strategy. The proposed partitioning scheme ensures that Voronoi cells are contiguous even in the presence of obstacles. We demonstrate that if the single-robot coverage strategy is capable of providing a complete and non-repetitive coverage, then the proposed Geodesic-VPC strategy provides a complete and non-repetitive coverage. We use spanning tree-based coverage algorithm as the underlying single-robot coverage strategy for the purpose of demonstration, though any existing single-robot coverage algorithm can be used. © 2020, Springer Nature Singapore Pte Ltd.Item Application of Coverage Path Planning Algorithm for Milling Operations(Springer, 2020) Kalburgi, S.; Nair, V.G.; Guruprasad, K.R.In this paper, we present an algorithm for automatic tool path generation for milling operations, where, the ‘cutter’ needs to pass through all the region that is required to be removed, without any gaps. We demonstrate the possibility of using mobile robot coverage path planning (CPP) algorithms for such applications. In the place of the robot footprint size that is used in a mobile robot CPP algorithm, here we use the size (diameter) of the tool as basis for the tool path generation. Here, we use a spanning tree-based competitive and truly complete robot coverage path planning algorithm, which is based on the approximate cellular decomposition. The proposed algorithm is first tested in V-Rep simulation environment with an arbitrary work piece and then real-time experiments were carried out on a CNC machine to demonstrate the proposed algorithm. © 2020, Springer Nature Singapore Pte Ltd.