Mobile Robots Navigation Modeling in Known 2d Environment Based on Petri Nets

Bartkevičius, S.; Fiodorova, O.; Knyš, A.; Dervinienė, Alma; Dervinis, Gintaras; Raudonis, Vidas; Lipnickas, Arūnas; Baranauskas, V.; Šarkauskas, K.; Balaševičius, Leonas

doi:10.1080/10798587.2016.1264695

Cited by 4 publications

(7 citation statements)

References 7 publications

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“…In this case, solving mobile robot navigation problems can be transferred to a supervisory system. The supervisor-based system is solving mobile robots' navigation problems and searches for the shortest path using colored Petri nets [14,15] in a virtual environment. All parties of the virtual system are functioning asynchronously.…”

Section: Cocoon Collision Rules For Conflict Preventionmentioning

confidence: 99%

“…Software "CentaurusCPN" is enabled to solve mobile robot path planning tasks [15]. The calculated path is the shortest according to its length in the current situation, but collisions between robots are not taken into account in work [15]. Authors had to modify the structure of dynamic region description when "cocoons" were started to apply.…”

Section: Algorithm Of Collision Avoidance and Experimentsmentioning

confidence: 99%

“…The motion trajectory of one mobile robot is designed to avoid a potential collision with static obstacles (columns, walls, partitions) when the environment is known. These types of collisions are addressed through vector marks [14,15], which determine the shortest possible path of the robot trajectories. Dynamic obstacles, which can vary in size and location, can appear when more than one robot is used in the same known environment.…”

Section: Introductionmentioning

confidence: 99%

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Mobile Robots’ Collision Prediction Based on Virtual Cocoons

Baranauskas¹,

Jakas²,

Šarkauskas³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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The research work presents a collision prediction method of mobile robots. The authors of the work use so-called, virtual cocoons to evaluate the collision criteria of two robots. The idea, mathematical representation of the calculations and experimental simulations are presented in the paper work. A virtual model of the industrial process with moving mobile robots was created. Obstacle avoidance was not solved here. The authors of the article were working on collision avoidance problem solving between moving robots. Theoretical approach presents mathematical calculations and dependences of path angles of mobile robots. Experimental simulations, using the software Centaurus CPN, based on colored Petri nets, has shown, that the possible conflict can be predicted in advance using calculations of the angle of movement of two possibly colliding cocoons. Authors of the paper presents and explains experimental simulations, where robots are moving in different path angles, which intersects each other. Proposed collision avoidance algorithm solves collision avoidance task using several possibilities. Software Centaurus CPN gives possibility to stop simulation of manufacturing process in the place where it finds possible collision between two cocoons. In order to check correctness of proposed collision prediction and avoidance algorithm, further simulation is done step by step, while situation is solved. Simulated manufacturing process is continued till new possible collision is obtained.

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Section: Cocoon Collision Rules For Conflict Preventionmentioning

confidence: 99%

Section: Algorithm Of Collision Avoidance and Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mobile Robots’ Collision Prediction Based on Virtual Cocoons

Baranauskas¹,

Jakas²,

Šarkauskas³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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“…With adjusted parameters, the experiments showed that the reconstruction of the 50% data set provided the same amount of details as the original one. Some wearable devices and autonomous robots mounted 3D laser sensors have been used for navigation in outdoor environments [70] or simultaneous localization and mapping (SLAM)-driven robotic mapping in indoor environments [71][72][73][74][75]. Conventionally, MLS have been used for mapping buildings and roofs [58,[76][77][78].…”

Section: Building Information Modelingmentioning

confidence: 99%

A Survey of Mobile Laser Scanning Applications and Key Techniques over Urban Areas

et al. 2019

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Urban planning and management need accurate three-dimensional (3D) data such as light detection and ranging (LiDAR) point clouds. The mobile laser scanning (MLS) data, with up to millimeter-level accuracy and point density of a few thousand points/m2, have gained increasing attention in urban applications. Substantial research has been conducted in the past decade. This paper conducted a comprehensive survey of urban applications and key techniques based on MLS point clouds. We first introduce the key characteristics of MLS systems and the corresponding point clouds, and present the challenges and opportunities of using the data. Next, we summarize the current applications of using MLS over urban areas, including transportation infrastructure mapping, building information modeling, utility surveying and mapping, vegetation inventory, and autonomous vehicle driving. Then, we review common key issues for processing and analyzing MLS point clouds, including classification methods, object recognition, data registration, data fusion, and 3D city modeling. Finally, we discuss the future prospects for MLS technology and urban applications.

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“…The job is to check the next free position on each iteration and minimize objective function based on Euclidean distances. Petri nets are used for obstacle avoidance as presented in [4]. The supervised system is used for obstacle avoidance in known environment.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Robot Navigation in Known Environment

Kosser,

Kumar

2023

IJRTE

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Autonomous robot navigation is one of the challenging researched topic in robotics. A secure and optimal path in known environment is required for any mobile robot navigation for navigation purpose. In this work, a Simulink model is proposed based on Pure Pursuit and path following controllers for solving the problem of mobile robot navigation in a known environment is presented. Pure Pursuit controller is used to find the linear and angular velocities of the robot. Moreover, (x, y) coordinate position of robot and waypoints are input to the pure pursuit block. Velocity commands are sent to drive robot on the given path. The main aim of the proposed mod el is to find the obstacle free path for the mobile robot navigation. However, the robot is to navigate from start to target location without hitting obstacles. For experimental results, Turtle Bot Gazebo simulator is used. "Robotic system Toolbox" of the MATLAB is used to program the navigation process.

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Mobile Robots Navigation Modeling in Known 2d Environment Based on Petri Nets

Cited by 4 publications

References 7 publications

Mobile Robots’ Collision Prediction Based on Virtual Cocoons

Mobile Robots’ Collision Prediction Based on Virtual Cocoons

A Survey of Mobile Laser Scanning Applications and Key Techniques over Urban Areas

Autonomous Robot Navigation in Known Environment

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