scholarly journals Autonomous navigation and mapping in a simulated environment

2021 ◽  
Author(s):  
Benjamin Christie ◽  
Osama Ennasr ◽  
Garry Glaspell
Keyword(s):  
Operating System ◽  
Autonomous Navigation ◽  
Three Dimensional ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Robot Operating System ◽  
Simulated Environment ◽  
Localization And Mapping ◽  
Environment Exploration ◽  
Rgbd Cameras

Unknown Environment Exploration (UEE) with an Unmanned Ground Vehicle (UGV) is extremely challenging. This report investigates a frontier exploration approach, in simulation, that leverages Simultaneous Localization And Mapping (SLAM) to efficiently explore unknown areas by finding navigable routes. The solution utilizes a diverse sensor payload that includes wheel encoders, three-dimensional (3-D) LIDAR, and Red, Green, Blue and Depth (RGBD) cameras. The main goal of this effort is to leverage frontier-based exploration with a UGV to produce a 3-D map (up to 10 cm resolution). The solution provided leverages the Robot Operating System (ROS).

An architecture for multi-robot localization and mapping in the Gazebo/Robot Operating System simulation environment

SIMULATION ◽  
2017 ◽  
Vol 93 (9) ◽  
pp. 771-780 ◽  
Author(s):  
Erkan Uslu ◽  
Furkan Çakmak ◽  
Nihal Altuntaş ◽  
Salih Marangoz ◽  
Mehmet Fatih Amasyalı ◽  
...  
Keyword(s):  
Operating System ◽  
Three Dimensional ◽  
Simulation Environment ◽  
Urban Search And Rescue ◽  
Mapping Algorithms ◽  
Robot Operating System ◽  
Mapping Algorithm ◽  
Localization And Mapping ◽  
Dimensional Simulation ◽  
Multi Robot

Robots are an important part of urban search and rescue tasks. World wide attention has been given to developing capable physical platforms that would be beneficial for rescue teams. It is evident that use of multi-robots increases the effectiveness of these systems. The Robot Operating System (ROS) is becoming a standard platform for the robotics research community for both physical robots and simulation environments. Gazebo, with connectivity to the ROS, is a three-dimensional simulation environment that is also becoming a standard. Several simultaneous localization and mapping algorithms are implemented in the ROS; however, there is no multi-robot mapping implementation. In this work, two multi-robot mapping algorithm implementations are presented, namely multi-robot gMapping and multi-robot Hector Mapping. The multi-robot implementations are tested in the Gazebo simulation environment. Also, in order to achieve a more realistic simulation, every incremental robot movement is modeled with rotational and translational noise.

scholarly journals Mapping and Navigation for Indoor Robots under ROS: An Experimental Analysis

2019 ◽  
Author(s):  
Bruno M. F. da Silva ◽  
Rodrigo S. Xavier ◽  
Luiz M. G. Gonçalves
Keyword(s):  
Operating System ◽  
Experimental Analysis ◽  
Autonomous Navigation ◽  
Robot Navigation ◽  
Simultaneous Localization And Mapping ◽  
Indoor Environments ◽  
Robot Operating System ◽  
Localization And Mapping ◽  
Application Requirements

Since it was proposed, the Robot Operating System (ROS) has fostered solutions for various problems in robotics in the form of ROS packages. One of these problems is Simultaneous Localization and Mapping (SLAM), a problem solved by computing the robot pose and a map of its environment of operation at the same time. The increasingly availability of robot kits ready to be programmed and also of RGB-D sensors often pose the question of which SLAM package should be used given the application requirements. When the SLAM subsystem must deliver estimates for robot navigation, as is the case of applications involving autonomous navigation, this question is even more relevant. This work introduces an experimental analysis of GMapping and RTAB-Map, two ROS compatible SLAM packages, regarding their SLAM accuracy, quality of produced maps and use of produced maps in navigation tasks. Our analysis aims ground robots equipped with RGB-D sensors for indoor environments and is supported by experiments conducted on datasets from simulation, benchmarks and from our own robot.

A Study of Autonomous Navigation of a Robot Model based on SLAM, ROS, and Kinect

2018 ◽  
Vol 7 (3.33) ◽  
pp. 28
Author(s):  
Asilbek Ganiev ◽  
Kang Hee Lee
Keyword(s):  
Operating System ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Autonomous Navigation ◽  
Simultaneous Localization And Mapping ◽  
Target Point ◽  
Robot Operating System ◽  
Model Based ◽  
Localization And Mapping ◽  
Starting Point

In this paper, we used a robot operating system (ROS) that is designed to work with mobile robots. ROS provides us with simultaneous localization and mapping of the environment, and here it is used to autonomously navigate a mobile robot simulator between specified points. Also, when the mobile robot automatically navigates between the starting point and the target point, it bypasses obstacles; and if necessary, sets a new path of the route to reach the goal point.  

scholarly journals Collaborative Pursuit-Evasion Strategy of UAV/UGV Heterogeneous System in Complex Three-Dimensional Polygonal Environment

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xiao Liang ◽  
Honglun Wang ◽  
Haitao Luo
Keyword(s):  
Visual Field ◽  
Heterogeneous System ◽  
Three Dimensional ◽  
Unmanned Ground Vehicle ◽  
Worst Case ◽  
Ground Vehicle ◽  
Pursuit Evasion ◽  
Evasion Game ◽  
Evasion Strategy ◽  
Aerial Vehicle

The UAV/UGV heterogeneous system combines the air superiority of UAV (unmanned aerial vehicle) and the ground superiority of UGV (unmanned ground vehicle). The system can complete a series of complex tasks and one of them is pursuit-evasion decision, so a collaborative strategy of UAV/UGV heterogeneous system is proposed to derive a pursuit-evasion game in complex three-dimensional (3D) polygonal environment, which is large enough but with boundary. Firstly, the system and task hypothesis are introduced. Then, an improved boundary value problem (BVP) is used to unify the terrain data of decision and path planning. Under the condition that the evader knows the position of collaborative pursuers at any time but pursuers just have a line-of-sight view, a worst case is analyzed and the strategy between the evader and pursuers is studied. According to the state of evader, the strategy of collaborative pursuers is discussed in three situations: evader is in the visual field of pursuers, evader just disappears from the visual field of pursuers, and the position of evader is completely unknown to pursuers. The simulation results show that the strategy does not guarantee that the pursuers will win the game in complex 3D polygonal environment, but it is optimal in the worst case.

Mobile Robot Decision-Making Based on Offline Simulation for Navigation over Uneven Terrain

2018 ◽  
Vol 30 (4) ◽  
pp. 671-682
Author(s):  
Yuichi Kobayashi ◽  
Masato Kondo ◽  
Yuji Hiramatsu ◽  
Hokuto Fujii ◽  
Tsuyoshi Kamiya ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Path Selection ◽  
Outdoor Environment ◽  
Selection Strategy ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Uneven Terrain ◽  
Simulated Environment ◽  
Terrain Features ◽  
Selection Of

This paper presents an action decision framework for an autonomous mobile robot or an unmanned ground vehicle (UGV) to navigate an unknown environment. It is difficult for a UGV without global map information to decide which path to travel when it comes to a fork. However, locally observed terrain features can enable the UGV if it can utilize its past experience. The proposed path selection method utilizes correlations between features of the local terrain obtained by its laser range finder and the values of paths obtained through offline simulation using global path planning. During navigation, the UGV estimates the values of each path at a fork based on the correlation between the terrain feature and the value. It was confirmed that the proposed method allows the selection of paths that are more effective compared with a simple path selection strategy with which the UGV selects the closer path to the goal. The proposed method was evaluated in both a simulated environment and a real outdoor environment.

scholarly journals Gerak Robot Berkaki Dua menggunakan ROS dan RViz sebagai Visualisasi Interaktif

2021 ◽  
Vol 9 (1) ◽  
pp. 43
Author(s):  
ADI SUCIPTO ◽  
RADEN SANGGAR DEWANTO ◽  
DADET PRAMADIHANTO
Keyword(s):  
Operating System ◽  
Success Rate ◽  
Operating Systems ◽  
Three Dimensional ◽  
Biped Robot ◽  
Sensor Data ◽  
Average Error ◽  
Robot Operating System ◽  
Robot Technology ◽  
The Right

ABSTRAKPengembangan sistem operasi pada bidang robotika telah menjadi fokus utama pada era ini. Salah satu perkembangan sistem operasi pada teknologi robot saat ini adalah Robot Operating System (ROS) dengan RViz. ROS merupakan sistem operasi berbasis library dan beberapa tools untuk mengembangkan suatu program pada robot, sedangkan RViz merupakan visualisasi tiga dimensi yang dapat digunakan untuk memvisualisasikan robot dan data sensor dynamixel. Pada Penelitian kali ini, peneliti membuat simulasi beberapa gerakan yang dilakukan pada RViz dan kemudian diimplementasikan pada robot. Tingkat keberhasilan dari perencanaan gerakan ini memiliki rata rata error sebesar 1.8%. Gerakan condong ke kiri memiliki rata-rata error sebesar 0.83%. Gerakan condong ke kanan memiliki rata-rata error sebesar 0.84%. Gerakan mengangkat satu kaki memiliki rata-rata error sebesar 1.71%. Gerakan kaki kanan ke depan memiliki rata-rata error sebesar 3.83%.Kata kunci: Robot Berkaki Dua, Robot Operating System (ROS), RViz (rosvisualization), Dynamixel Controller, Data Sensor Dynamixel. ABSTRACTThe development of operating systems in the field of robotics has become the main focus of this era. One of the operating system developments in robot technology today is the Robot Operating System (ROS) with RViz. ROS is a library-based operating system and several tools for developing a program on robots, while RVIZ is a three-dimensional visualization that can be used to visualize robots and dynamixel sensor data. In this study, researchers made a simulation of some of the movements carried out on RViz and then implemented on robots. The success rate of planning this movement has an average error of 1.8%. Leaning to the left has an average error of 0.83%. Leaning to the right has an average error of 0.84%. One leg lift has an average error of 1.71%. The movement of the right foot forward has an average error of 3.83%.Keywords: Biped Robot, Robot Operating System (ROS), RViz (Ros-Visualization), Dynamixel Controller, Sensor Dynamixel Data.

scholarly journals Implementation and Reconfiguration of Robot Operating System on Human Follower Transporter Robot

2015 ◽  
Vol 9 (2) ◽  
pp. 59
Author(s):  
Addythia Saphala ◽  
Prianggada Indra Tanaya
Keyword(s):  
Operating System ◽  
Mobile Robot ◽  
Navigation System ◽  
Robot Navigation ◽  
Simultaneous Localization And Mapping ◽  
Kinect Sensor ◽  
Operation System ◽  
Robot Operating System ◽  
Localization And Mapping

Robotic Operation System (ROS) is an im- portant platform to develop robot applications. One area of applications is for development of a Human Follower Transporter Robot (HFTR), which  can  be  considered  as a custom mobile robot utilizing differential driver steering method and equipped with Kinect sensor. This study discusses the development of the robot navigation system by implementing Simultaneous Localization and Mapping (SLAM).

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