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R. RAJENDRA,P. S. Guruprasad,K. BHARGAVA,P. SIVA KOTA REDDY 장전수학회 2021 Proceedings of the Jangjeon mathematical society Vol.24 No.2
In this paper, we present a new representation of partitions of positive integers using labeled trees. Labeled trees representing a partition of an integer n is called a partition-tree of n. We discuss some results involving partition-trees, energy of an integer with respect to partition-trees, and gracefulness of the default labeling of partition trees.
On Certain New Modular Relations for the Rogers-Ramanujan type functions of order Twelve
K. R. Vasuki,P. S. Guruprasad 장전수학회 2010 Advanced Studies in Contemporary Mathematics Vol.20 No.3
In this paper, we define the Rogers-Ramanujan type functions M(q) and N(q) of order twelve and obtain some modular relations involving these identities, which are analogues to Ramanujan’s well known forty identities for Rogers-Ramanujan functions. Further, we establish certain color partition identities from them.
Model-based, Distributed, and Cooperative Control of Planar Serial-link Manipulators
S. Soumya,K. R. Guruprasad 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.2
In this paper, we propose a novel distributed control scheme for a planar serial-link manipulator with revolute joints. The control scheme is based on the conventional model-based nonlinear control scheme that achieves linearization by feedback. A dedicated controller controls each joint of the manipulator, as in the case of the decentralized manipulator control scheme. However, in the proposed control scheme, the joint-level controllers communicate and cooperate to account for the nonlinear dynamic coupling between the links. The proposed control scheme can achieve the performance level of that of the model-based nonlinear control scheme, and at the same time, reduce the computational lead-time by distributing the computational load associated with the control law among the joint-level controllers. We design a distributed cooperative control law for a three-link planar manipulator and demonstrate its trajectory tracking performance using simulation experiments.
2D-VPC: An Efficient Coverage Algorithm for Multiple Autonomous Vehicles
Vishnu G. Nair,K. R. Guruprasad 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.8
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.
Jeane Marina D’Souza,Venkat Varun Velpula,K. R. Guruprasad 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.7
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.
Vishnu G. Nair,Adarsh Rag S.,Jayalakshmi K. P.,Dileep M. V.,K. R. Guruprasad 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.7
In this paper, a dynamic workspace allocation methodology for coverage path planning using multiple robots in the presence of obstacles is presented. The entire workspace is initially partitioned using the Manhattan Voronoi partitioning method, without considering the obstacles present, and the robots execute Multi-Robot Simultaneous Exploration and Coverage (MRSimExCoverage) using the Spanning Tree Coverage (STC) algorithm and cover the workspace. A dynamic workspace re-allocation strategy to optimize the area covered by each robot, whenever obstacles are detected, so as to avoid certain obstacle-induced coverage issues is studied. Simulation experiments within the Matlab/V-rep environment are used to demonstrate and validate the performance of the proposed algorithm. Though the authors used the STC algorithm for path planning for demonstration, any suitable coverage algorithm may be used.