A high fidelity simulator for a quadrotor UAV using ROS and Gazebo

Zhang, Mengmi; Qin, Hailong; Lan, Menglu; Lin, Jiaxin; Wang, Shuai; Liu, Kaijun; Lin, Feng; Chen, Ben M.

doi:10.1109/iecon.2015.7392534

Cited by 27 publications

(18 citation statements)

References 8 publications

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“…In order to evaluate the E 2 SP-LCA algorithm, we divided the validation into two phases: the first one was performed with the support of the simulation environment Gazebo [11] [12] and the second one in a mixed environment composed by a real multirotor UAV in an outdoor scenario and a simulated obstacle and LiDAR sensor. Both approaches were implemented to validate the robustness of the E 2 SP-LCA algorithm into different scenarios and in the particular case of the second test, also to ensure that the first tests of the algorithm were performed without risking a UAV with higher payload and more costly sensors like the LiDAR Velodyne VLP-16.…”

Section: Implementation and Resultsmentioning

confidence: 99%

Collision avoidance for safe structure inspection with multirotor UAV

Azevedo

Oliveira

Dias

et al. 2017

2017 European Conference on Mobile Robots (ECMR)

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The multirotor UAVs are being integrated into a wide range of application scenarios due to maneuverability in 3D, versatility and reasonable payload of sensors. One of the application scenarios is the inspection of structures where the human intervention is difficult or unsafe and the UAV can provide an improvement of the collected data. At the same time introduce challenges due to low altitude missions and also the fact of being manually operated without line of sight. In order to overcome these issues, this paper presents a LiDAR-based realtime collision avoidance algorithm, denoted by Escape Elliptical Search Point with the ability to be integrated into autonomous and manned modes of operation. The algorithm was validated in a simulation environment developed in Gazebo and also in a mixed environment composed by a real robot in an outdoor scenario and simulated obstacle and LiDAR.

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Section: Implementation and Resultsmentioning

confidence: 99%

Collision avoidance for safe structure inspection with multirotor UAV

Azevedo

Oliveira

Dias

et al. 2017

2017 European Conference on Mobile Robots (ECMR)

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“…The presented work motivates as to think about identifying much realistic consumption model by considering the wave effect and the non-linear drag impact to be represented in further papers. Our approach can be exploited with different unmanned vehicles type such as aerial drones or under water drones by integrating the power model into their corresponding simulators given in [27,28,29].…”

Section: Discussionmentioning

confidence: 99%

“…Fortunately, ROS and Gazebo-based robot simulators are free and open source platforms, which help researchers to simulate their applications especially those for unmanned robots. Among the most robust and high-fidelity Gazebo-based simulators that exist we find the Unmanned Ground Vehicle simulator [27], Unmanned Underwater Vehicles UUV simulator [28], Unmanned Aerial Vehicle UAV simulator [29] and finally the Unmanned Surface Vehicle USV simulator [1]. The latter is our case of study simulator since it is a recent and robust ROS and Gazebo-based package [30].…”

Section: Related Workmentioning

confidence: 99%

Unmanned surface vehicle energy consumption modelling under various realistic disturbances integrated into simulation environment

et al. 2021

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“…Some UAV SLAM and navigation simulations have previously been proposed. Zhang et al [2] proposed a quadrotor UAV simulator integrated with a hierarchical navigation system. Under this approach, the UAV is equipped with two laser scanners and one monocular camera.…”

Section: Uav Slam and Navigation Simulationsmentioning

confidence: 99%

“…The simulation used in the visual simultaneous localization and mapping (vSLAM) study simplified the dynamic model of the UAV; the navigation-oriented simulation environment contained 3D information about the environment, but it neglected the features of 3D objects. Some simulation tools [2,3] achieve autonomous navigation to a certain degree, but their flexibility is limited, and their source codes have not been released. Thus, the motivation of this work is to construct an end-to-end simulation (E2ES) environment for research and education purposes.…”

Section: Introductionmentioning

confidence: 99%

An End-to-End UAV Simulation Platform for Visual SLAM and Navigation

et al. 2022

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Visual simultaneous localization and mapping (v-SLAM) and navigation of unmanned aerial vehicles (UAVs) are receiving increasing attention in both research and education. However, extensive physical testing can be expensive and time-consuming due to safety precautions, battery constraints, and the complexity of hardware setups. For the efficient development of navigation algorithms and autonomous systems, as well as for education purposes, the ROS-Gazebo-PX4 simulator was customized in-depth, integrated into our previous released research works, and provided as an end-to-end simulation (E2ES) solution for UAV, v-SLAM, and navigation applications. Unlike most other similar works, which can only stimulate certain parts of the navigation algorithms, the E2ES platform simulates all of the localization, mapping, and path-planning kits in one simulator. The navigation stack performs well in the E2ES test bench with the absolute pose errors of 0.3 m (translation) and 0.9 degree (rotation), respectively, for an 83 m length trajectory. Moreover, the E2ES provides an out-of-box, click-and-fly autonomy in UAV navigation. The project source code is opened for the benefit of the research community.

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A high fidelity simulator for a quadrotor UAV using ROS and Gazebo

Cited by 27 publications

References 8 publications

Collision avoidance for safe structure inspection with multirotor UAV

Collision avoidance for safe structure inspection with multirotor UAV

Unmanned surface vehicle energy consumption modelling under various realistic disturbances integrated into simulation environment

An End-to-End UAV Simulation Platform for Visual SLAM and Navigation

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