CPC Algorithm: Exact Area Coverage by a Mobile Robot Using Approximate Cellular Decomposition

Robotica ◽

10.1017/s026357472000096x ◽

2020 ◽

pp. 1-22

Author(s):

K. R. Guruprasad ◽

T. D. Ranjitha

Keyword(s):

Operating System ◽

Path Planning ◽

Mobile Robot ◽

Formal Analysis ◽

Area Coverage ◽

Cell Permeability ◽

Cellular Decomposition ◽

Robot Operating System ◽

Coverage Path Planning

SUMMARY 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.

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Path planning for car like mobile robot using robot operating system

2018 National Power Engineering Conference (NPEC) ◽

10.1109/npec.2018.8476806 ◽

2018 ◽

Author(s):

S. Julius Fusic ◽

M. Karlmarx ◽

I. Leando ◽

K. Hariharan

Keyword(s):

Operating System ◽

Path Planning ◽

Mobile Robot ◽

Robot Operating System

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Hardware in the Loop Topology for an Omnidirectional Mobile Robot Using Matlab in a Robot Operating System Environment

Symmetry ◽

10.3390/sym13060969 ◽

2021 ◽

Vol 13 (6) ◽

pp. 969

Author(s):

Constantin-Catalin Dosoftei ◽

Alexandru-Tudor Popovici ◽

Petru-Razvan Sacaleanu ◽

Paul-Marcelin Gherghel ◽

Cristina Budaciu

Keyword(s):

Operating System ◽

Path Planning ◽

Mobile Robot ◽

Autonomous Navigation ◽

Vertical Axis ◽

Hardware In The Loop ◽

Robot Operating System ◽

System Nodes ◽

Navigation Software ◽

Time Autonomous

The symmetry of the omnidirectional robot motion abilities around its central vertical axis is an important advantage regarding its driveability for the flexible interoperation with fixed conveyor systems. The paper illustrates a Hardware in the Loop architectural approach for integrated development of an Ominidirectional Mobile Robot that is designed to serve in a dynamic logistic environment. Such logistic environments require complex algorithms for autonomous navigation between different warehouse locations, that can be efficiently developed using Robot Operating System nodes. Implementing path planning nodes benefits from using Matlab-Simulink, which provides a large selection of algorithms that are easily integrated and customized. The proposed solution is deployed for validation on a NVIDIA Jetson Nano, the embedded computer hosted locally on the robot, that runs the autonomous navigation software. The proposed solution permits the live connection to the omnidirectional prototype platform, allowing to deploy algorithms and acquire data for debugging the location, path planning and the mapping information during real time autonomous navigation experiments, very useful in validating different strategies.

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Robot Operating System Based Path Planning

Intelligent Data Communication Technologies and Internet of Things - Lecture Notes on Data Engineering and Communications Technologies ◽

10.1007/978-3-030-34080-3_83 ◽

2019 ◽

pp. 748-755

Author(s):

Ashwin Vasudevan ◽

Ajith Kumar ◽

Nrithya Theetharapan ◽

N. S. Bhuvaneswari

Keyword(s):

Operating System ◽

Path Planning ◽

Robot Operating System

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Implementation of Robot Operating System in Beaglebone Black based Mobile Robot for Obstacle Avoidance Application

International Journal on Advanced Science Engineering and Information Technology ◽

10.18517/ijaseit.7.6.3221 ◽

2017 ◽

Vol 7 (6) ◽

pp. 2213

Author(s):

Mohamad Fauzi Zakaria ◽

Joo Chin Shing ◽

Mohd Razali Md Tomari

Keyword(s):

Operating System ◽

Mobile Robot ◽

Obstacle Avoidance ◽

Robot Operating System

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Global Path Planning for Full-Area Coverage Robotic Systems by Employing an Active Genetic Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.328-330.1881 ◽

2011 ◽

Vol 328-330 ◽

pp. 1881-1886

Author(s):

Cen Zeng ◽

Qiang Zhang ◽

Xiao Peng Wei

Keyword(s):

Genetic Algorithm ◽

Path Planning ◽

High Performance ◽

Search Space ◽

Area Coverage ◽

Robotic Systems ◽

Genetic Operators ◽

A Algorithm ◽

Coverage Path Planning ◽

Search Spaces

Genetic algorithm (GA), a kind of global and probabilistic optimization algorithms with high performance, have been paid broad attentions by researchers world wide and plentiful achievements have been made.This paper presents a algorithm to develop the path planning into a given search space using GA in the order of full-area coverage and the obstacle avoiding automatically. Specific genetic operators (such as selection, crossover, mutation) are introduced, and especially the handling of exceptional situations is described in detail. After that, an active genetic algorithm is introduced which allows to overcome the drawbacks of the earlier version of Full-area coverage path planning algorithms.The comparison between some of the well-known algorithms and genetic algorithm is demonstrated in this paper. our path-planning genetic algorithm yields the best performance on the flexibility and the coverage. This meets the needs of polygon obstacles. For full-area coverage path-planning, a genotype that is able to address the more complicated search spaces.

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