Browsing by Author "Guruprasad, K.R."

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2D-VPC: An Efficient Coverage Algorithm for Multiple Autonomous Vehicles
(Institute of Control, Robotics and Systems, 2021) Nair, V.G.; Guruprasad, K.R.
In this paper, we address a problem of multi-robotic coverage, where an area of interest is covered by multiple sensors, each mounted on an autonomous vehicle such as an aerial or a ground mobile robot. The area of interest is first decomposed into grids of equal size and then partitioned into Voronoi cells. Each robot/sensor is assigned the task of covering the corresponding Voronoi cell. We propose an optimal gridding size and partitioning methodology that eliminate the coverage inefficiencies induced by the partitioning process. We carried out experiments using multiple quadcopters and mobile robots to demonstrate and validate the proposed multi-sensor coverage strategy. © 2021, ICROS, KIEE and Springer.
3D printable modules for manually reconfigurable manipulator with desired D-H parameters
(2020) Marebal, D.; Guruprasad, K.R.
Modular robots are designed to increase the utilization of robots by modularizing their architecture. We discuss manually reconfigurable manipulators, where a manipulator of desired kinematic configuration is built by assembling the available modules. In the case of a serial-link manipulator with revolute joints, the joint angle is a variable. Out of the remaining three D-H parameters, namely, link-length, link-offset and link-twist, the twist angle influences the workspace the most. This work proposes a conceptual design and fabrication of individual modules which can be assembled to obtain a modular manipulator with desired kinematic configuration in terms of twist angles between any two consecutive joints. We also discuss possible provisions for length adjustment of a link. Designed modules are fabricated using 3D printer. As we focus on manually reconfigurable manipulators, simplicity of individual modules, in terms design, fabrication, and assembly, has been given higher priority, in contrast to similar designs available in the literature. � 2020, Springer Nature Singapore Pte Ltd.
3D printable modules for manually reconfigurable manipulator with desired D-H parameters
(Springer Verlag service@springer.de, 2020) Marebal, D.; Guruprasad, K.R.
Modular robots are designed to increase the utilization of robots by modularizing their architecture. We discuss manually reconfigurable manipulators, where a manipulator of desired kinematic configuration is built by assembling the available modules. In the case of a serial-link manipulator with revolute joints, the joint angle is a variable. Out of the remaining three D-H parameters, namely, link-length, link-offset and link-twist, the twist angle influences the workspace the most. This work proposes a conceptual design and fabrication of individual modules which can be assembled to obtain a modular manipulator with desired kinematic configuration in terms of twist angles between any two consecutive joints. We also discuss possible provisions for length adjustment of a link. Designed modules are fabricated using 3D printer. As we focus on manually reconfigurable manipulators, simplicity of individual modules, in terms design, fabrication, and assembly, has been given higher priority, in contrast to similar designs available in the literature. Â© 2020, Springer Nature Singapore Pte Ltd.
A distributed algorithm for computation of exact Voronoi cell in a multi-robotic system
(2012) Guruprasad, K.R.; Dasgupta, P.
In this paper we propose an algorithm for distributed computation of Voronoi cell in a multi-robotic system. Each of the robots is assumed to know its own position and position of all other robots. The robots compute their Voronoi cells based only on this positional information, without any additional communication and cooperation with other robots. Â© 2012 IEEE.
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
A repartitioning algorithm to guarantee complete, non-overlapping planar coverage with multiple robots
(Springer Verlag service@springer.de, 2016) Hungerford, K.; Dasgupta, P.; Guruprasad, K.R.
We consider the problem of coverage path planning in an initially unknown or partially known planar environment using multiple robots. Previously, Voronoi partitioning has been proposed as a suitable technique for coverage path planning where the free space in the environment is partitioned into non-overlapping regions called Voronoi cells based on the initial positions of the robots, and one robot is allocated to perform coverage in each region. However, a crucial problem arises if such a partitioning scheme is used in an environment where the location of obstacles is not known a prioriâ€”while performing coverage, a robot might perceive an obstacle that occludes its access to portions of its Voronoi cell and this obstacle might prevent the robot from completely covering its allocated region. This would either result in portions of the environment remaining uncovered or requires additional path planning by robots to cover the disconnected regions. To address this problem, we propose a novel algorithm that allows robots to coordinate the coverage of inaccessible portions of their Voronoi cell with robots in neighboring Voronoi cells so that they can repartition the initial Voronoi cells and cover a set of contiguous, connected regions. We have proved analytically that our proposed algorithm guarantees complete, non-overlapping coverage. We have also quantified the performance of our algorithm on e-puck robots within the Webots simulator in different environments with different obstacle geometries and shown that it successfully performs complete, non-overlapping coverage. Â© Springer Japan 2016.
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 â€˜cutterâ€™ 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. Â© 2020, Springer Nature Singapore Pte Ltd.
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.
Centroidal voronoi partitioning using virtual nodes for multirobot coverage
(Science Publishing Corporation Inc ijet@sciencepubco.com, 2018) Nair, V.G.; Guruprasad, K.R.
This paper addresses the problem of Voronoi partitioning using Centroidal Voronoi configuration for a multi-robotic coverage strategy known as Voronoi Partition based Coverage (VPC) algorithm. In VPC, the area to be covered is divided into Voronoi cells and each robot covers the corresponding cell. We use the concept of Centroidal Voronoi Configuration (CVC) to achieve a more uniform load distribution among the robots in terms of the area covered. Instead of the robots moving physically into the CVC, we introduce a concept of virtual nodes, which are deployed into CVC. Once the Voronoi partition is created based on the virtual nods, the robots cover the corresponding Voronoi cells. A gradient based control law has been used for deployment of the virtual nodes. Simulation results are provided to demonstrate the proposed deployment and partitioning scheme. © 2016 Authors.
CPC Algorithm: Exact Area Coverage by a Mobile Robot Using Approximate Cellular Decomposition
(Cambridge University Press, 2021) Guruprasad, K.R.; Ranjitha, T.D.
A new coverage path planning (CPP) algorithm, namely cell permeability-based coverage (CPC) algorithm, is proposed in this paper. Unlike the most CPP algorithms using approximate cellular decomposition, the proposed algorithm achieves exact coverage with lower coverage overlap compared to that with the existing algorithms. Apart from a formal analysis of the algorithm, the performance of the proposed algorithm is compared with two representative approximate cellular decomposition-based coverage algorithms reported in the literature. Results of demonstrative experiments on a TurtleBot mobile robot within the robot operating system/Gazebo environment and on a Fire Bird V robot are also provided. © 2021 Cambridge University Press. All rights reserved.
Deploy and search strategy for multi-agent systems using Voronoi partitions
(2007) Guruprasad, K.R.; Ghose, D.
In this paper we analyze a deploy and search strategy for multi-agent systems. Mobile agents equipped with sensors carry out search operation in the search space. The lack of information about the search space is modeled as an uncertainty density distribution over the space, and is assumed to be known to the agents a priori. In each step, the agents deploy themselves in an optimal way so as to maximize per step reduction in the uncertainty density. We analyze the proposed strategy for convergence and spatial distributedness. The control law moving the agents has been analyzed for stability and convergence using LaSalle's invariance principle, and for spatial distributedness under a few realistic constraints on the control input such as constant speed, limit on maximum speed, and also sensor range limits. The simulation experiments show that the strategy successfully reduces the average uncertainty density below the required level. � 2007 IEEE.
Deploy and search strategy for multi-agent systems using Voronoi partitions
(2007) Guruprasad, K.R.; Ghose, D.
In this paper we analyze a deploy and search strategy for multi-agent systems. Mobile agents equipped with sensors carry out search operation in the search space. The lack of information about the search space is modeled as an uncertainty density distribution over the space, and is assumed to be known to the agents a priori. In each step, the agents deploy themselves in an optimal way so as to maximize per step reduction in the uncertainty density. We analyze the proposed strategy for convergence and spatial distributedness. The control law moving the agents has been analyzed for stability and convergence using LaSalle's invariance principle, and for spatial distributedness under a few realistic constraints on the control input such as constant speed, limit on maximum speed, and also sensor range limits. The simulation experiments show that the strategy successfully reduces the average uncertainty density below the required level. Â© 2007 IEEE.
A distributed algorithm for computation of exact Voronoi cell in a multi-robotic system
(2012) Guruprasad, K.R.; Dasgupta, P.
In this paper we propose an algorithm for distributed computation of Voronoi cell in a multi-robotic system. Each of the robots is assumed to know its own position and position of all other robots. The robots compute their Voronoi cells based only on this positional information, without any additional communication and cooperation with other robots. � 2012 IEEE.
Distributed Voronoi partitioning for multi-robot systems with limited range sensors
(2012) Guruprasad, K.R.; Dasgupta, P.
We consider the problem of distributed partitioning of an environment by a set of robots so that each robot performs its operations in the region within the corresponding cell. Voronoi partitioning is one of the most attractive techniques that has been used to solve this problem. It has been used in several distributed multi-robotic system and sensor network applications, such as sensor coverage, search and rescue, and coverage path planning. For a truly distributed implementation of such problems, each robot should be able to compute the corresponding Voronoi cell in a distributed manner. Further, in a practical application, the robots' sensors may have limited range, thus each robot may operate within a portion of its Voronoi cell constrained by the sensor range. We describe a distributed algorithm for computation of this range constrained Voronoi cell where each robot independently constructs chords corresponding to other robots that are within a distance of twice its sensor circle radius. A robot then uses a simple and fast technique to remove inessential chords to calculate the vertices of its Voronoi cell. We prove completeness and correctness of the proposed algorithm, and also provide the upper and lower bounds on the computational complexity of our algorithm. The theoretical results are validated with the help of experiments to show that for different values of sensor ranges, our proposed algorithm incurs a time complexity that is significantly lower than that of the existing full Voronoi partition computation algorithm. The maximum number of steps required by our algorithm is also shown to be within a constant times the lower bound given by the number of neighbors of each node. � 2012 IEEE.
Distributed Voronoi partitioning for multi-robot systems with limited range sensors
(2012) Guruprasad, K.R.; Dasgupta, P.
We consider the problem of distributed partitioning of an environment by a set of robots so that each robot performs its operations in the region within the corresponding cell. Voronoi partitioning is one of the most attractive techniques that has been used to solve this problem. It has been used in several distributed multi-robotic system and sensor network applications, such as sensor coverage, search and rescue, and coverage path planning. For a truly distributed implementation of such problems, each robot should be able to compute the corresponding Voronoi cell in a distributed manner. Further, in a practical application, the robots' sensors may have limited range, thus each robot may operate within a portion of its Voronoi cell constrained by the sensor range. We describe a distributed algorithm for computation of this range constrained Voronoi cell where each robot independently constructs chords corresponding to other robots that are within a distance of twice its sensor circle radius. A robot then uses a simple and fast technique to remove inessential chords to calculate the vertices of its Voronoi cell. We prove completeness and correctness of the proposed algorithm, and also provide the upper and lower bounds on the computational complexity of our algorithm. The theoretical results are validated with the help of experiments to show that for different values of sensor ranges, our proposed algorithm incurs a time complexity that is significantly lower than that of the existing full Voronoi partition computation algorithm. The maximum number of steps required by our algorithm is also shown to be within a constant times the lower bound given by the number of neighbors of each node. Â© 2012 IEEE.
Distributed, complete, multi-robot coverage of initially unknown environments using repartitioning
(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. Copyright � 2014, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
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. Â© Â© 2014, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
Effectiveness of a Camera as a UAV Mounted Search Sensor for Target Detection: An Experimental Investigation
(Institute of Control, Robotics and Systems, 2021) D’Souza, J.M.; Velpula, V.V.; Guruprasad, K.R.
In this paper, we consider a problem of autonomous search using single or multiple Unmanned Ariel Vehicles (UAVs) mounted with downward-facing cameras. A model of the effectiveness of the search sensor, camera, in this case, is essential for developing strategies for optimal deployment and path planning of UAVs for efficient search. The probability of detection of a target of interest as a function of its distance from the point directly below the camera is used to model the search effectiveness. We carried out experiments and obtained a search effectiveness model for a camera in the laboratory environment using ArUco markers and triangular shapes as targets. © 2021, ICROS, KIEE and Springer.
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.
Egress: An online path planning algorithm for boundary exploration
(2012) Guruprasad, K.R.; Dasgupta, P.
We consider the problem of navigating a mobile robot that is located at any arbitrary point within a bounded environment, to a point on the environment's outer boundary and then, using the robot to explore the perimeter of the boundary. The environment can have obstacles in it and the location and size of these obstacles are not provided a priori to the robot. We present an online path planning algorithm to solve this problem that requires very simple behaviors and computation on the robot. We analytically prove that by using our algorithm, the robot is guaranteed to reach and explore the outer boundary of the environment within a finite time. � 2012 IEEE.