Navigation control of the Khepera IV model with OpenCV in V-REP simulator

Farías, Gonzalo; Torres, Enrique; Fábregas, Ernesto; Vargas, Héctor; Dormido-Canto, S.; Dormido, Sebastián

doi:10.1109/ica-acca.2018.8609740

Cited by 5 publications

(8 citation statements)

References 13 publications

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“…This work is based on a previous work of the authors presented in [ 38 ]. The robot control algorithm must be able to calculate the corresponding speeds that allow the robot to turn in the correct direction depending on the arrow detected.…”

Section: Resultsmentioning

confidence: 99%

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A Distributed Vision-Based Navigation System for Khepera IV Mobile Robots

Farías

Fábregas

Torres

et al. 2020

Sensors

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This work presents the development and implementation of a distributed navigation system based on object recognition algorithms. The main goal is to introduce advanced algorithms for image processing and artificial intelligence techniques for teaching control of mobile robots. The autonomous system consists of a wheeled mobile robot with an integrated color camera. The robot navigates through a laboratory scenario where the track and several traffic signals must be detected and recognized by using the images acquired with its on-board camera. The images are sent to a computer server that performs a computer vision algorithm to recognize the objects. The computer calculates the corresponding speeds of the robot according to the object detected. The speeds are sent back to the robot, which acts to carry out the corresponding manoeuvre. Three different algorithms have been tested in simulation and a practical mobile robot laboratory. The results show an average of 84% success rate for object recognition in experiments with the real mobile robot platform.

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Section: Resultsmentioning

confidence: 99%

“…In which students can experiment with their own controllers in order to incorporate these concepts in the teaching of robot control. In this sense, experiments on position control, obstacle avoidance, among others, have been implemented with very good results, for example [ 35 , 36 , 37 , 38 ].…”

Section: Introductionmentioning

confidence: 99%

A Distributed Vision-Based Navigation System for Khepera IV Mobile Robots

Farías

Fábregas

Torres

et al. 2020

Sensors

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“…On the other hand, an exciting trajectory can also be created via V-Rep. Using the Gazebo [30] package which works under ROS, the system can submit the exciting trajectory into the Matlab script [31], [28]. Gen2 and LWR4+ exist in the V-Rep library that has been used for the simulation.…”

Section: ) V-rep Planningmentioning

confidence: 99%

Identifying Dynamic Parameters With a Novel Software Design for the M-DOF Collaborative Robot

Ayvaci

Szulczyński

2022

IEEE Access

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The primary goal of this project is to develop a general identification method via software that can be applied to collaborative robots. To achieve this, collaborative ultralight robots Kinova Gen2 and Kuka LWR4+ with seven degrees of freedom (M-DOF) were used. Specifically, the "recursive Newton-Euler" formulation was used to provide a set of parameters that could describe the body structure and to create a general symbolic representation for collaborative robots. For parameter estimation "Least-Squares" method was used. Besides, trajectories generated with random numbers cannot give very consistent results; hence, verified trajectories were used. To verify the trajectories, real robots were simulated with V-Rep before being executed. Because when untested trajectories are first tested on robots, undesirable results may occur. Therefore, the created trajectories were first simulated with V-Rep, and the chance of damaging the robot was eliminated. After being satisfied with the simulation results and being sure that any trajectories may be harmful to the robots, the trajectories were executed on the real robot. This method not only provides great convenience in terms of parameter estimation, robot health, and saving time, but also increased the consistency of our results. During the execution of real robots, data were collected by ROS in realtime. The algorithms have been coded via Matlab, and ROS packages via Python. Matlab, ROS, V-Rep were work together in harmony under Ubuntu operating system. The identification methods were modeled, implemented, tested, and validated successfully. The results for both robots are given in this article.

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“…This work is based on a previous work of the authors presented in [31]. The robot control algorithm must be able to calculate the corresponding speeds that allow the robot to turn in the correct direction depending on the arrow detected.…”

Section: Experiments 1: Object Detection By Image Processingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Distributed Vision-Based Navigation System for Khepera IV Mobile Robots

Farías¹,

Fábregas²,

Torres³

et al. 2020

Preprint

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This work presents the development and implementation of a distributed navigation system based on computer vision. The autonomous system consists of a wheeled mobile robot with an integrated colour camera. The robot navigates through a laboratory scenario where the track and several traffic signals must be detected and recognized by using the images acquired with its on-board camera. The images are sent to a computer server that processes them and calculates the corresponding speeds of the robot using a cascade of trained classifiers. These speeds are sent back to the robot, which acts to carry out the corresponding manoeuvre. The classifier cascade should be trained before experimentation with two sets of positive and negative images. The number of images in these sets should be considered to limit the training stage time and avoid overtraining the system.

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Navigation control of the Khepera IV model with OpenCV in V-REP simulator

Cited by 5 publications

References 13 publications

A Distributed Vision-Based Navigation System for Khepera IV Mobile Robots

A Distributed Vision-Based Navigation System for Khepera IV Mobile Robots

Identifying Dynamic Parameters With a Novel Software Design for the M-DOF Collaborative Robot

A Distributed Vision-Based Navigation System for Khepera IV Mobile Robots

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