OpenUAV Cloud Testbed: a Collaborative Design Studio for Field Robotics

Anand, Harish; Rees, Stephen A.; Chen, Zhiang; Jose, Ashwin; Bearman, Sarah Kate; Antervedi, Prasad; Das, Jnaneshwar

doi:10.48550/arxiv.1910.00739

Cited by 3 publications

(5 citation statements)

References 18 publications

(25 reference statements)

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“…NS-3 is one of the commonly used simulation tools in the network field and it is useful for simulations of packet delivery in virtual environments for Wi-Fi wireless communications. For instance, this tool has been utilized to verify video transmission in UAV systems and build virtual network environments for supporting simulations of swarm UAVs [22,23]. However, it cannot visualize the flight of UAV or evaluate the performance of the application.…”

Section: Background and Related Workmentioning

confidence: 99%

Advanced Co-Simulation Platform for UAV Simulations Under Virtual Wireless Network Environments

Cho

Kim

et al. 2022

IEEE Access

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In this paper, we propose an advanced co-simulation platform that performs the unmanned aerial vehicle (UAV) simulation and the wireless network simulation concurrently. As UAV-based applications become more advanced and complicated and the commands and data transmitted between UAV and ground control station significantly increase, it is vital to safely and robustly transmit the packets carrying commands and data in a wireless network environment. However, the conventional UAV simulation platforms do not take into account the wireless network conditions encountered in the real-world flight so they cannot sufficiently simulate packet transmission. To address this issue, co-simulation platforms have been developed to verify UAV-based applications under a virtual wireless network environment. However, they still cannot effectively support the co-simulation needed to develop the UAV-based applications. In this paper, we have derived a list of improvements to the conventional co-simulation platform based on analysis of the conventional ones. Based on these improvements, we have developed an advanced co-simulation platform consisting of a UAV simulation part, a wireless network simulation part, and an integration part. In this platform, a two-channel approach was introduced to parallelize the synchronization required for performing the UAV simulation and the wireless network simulation simultaneously. The experimental results carried out on three test scenarios demonstrate that the proposed platform accurately performs cosimulation by efficient interoperation of its three parts and by remarkable reduction of the processing time delay, and that it is extendible due to its modularized software architecture.

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Section: Background and Related Workmentioning

confidence: 99%

Advanced Co-Simulation Platform for UAV Simulations Under Virtual Wireless Network Environments

Cho

Kim

et al. 2022

IEEE Access

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“…OpenUAV: This testbed allows for testing of "swarms" of UAVs using integration with the Gazebo simulation system. OpenUAV also supports a containerized desktop environment and mission planning software [2]. OpenUAV also features remote desktop accessibility.…”

Section: Related Workmentioning

confidence: 99%

Autonomous Environment Generator for UAV-Based Simulation

et al. 2021

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The increased demand for Unmanned Aerial Vehicles (UAV) has also led to higher demand for realistic and efficient UAV testing environments. The current use of simulated environments has been shown to be a relatively inexpensive, safe, and repeatable way to evaluate UAVs before real-world use. However, the use of generic environments and manually-created custom scenarios leaves more to be desired. In this paper, we propose a new testbed that utilizes machine learning algorithms to procedurally generate, scale, and place 3D models to create a realistic environment. These environments are additionally based on satellite images, thus providing users with a more robust example of real-world UAV deployment. Although certain graphical improvements could be made, this paper serves as a proof of concept for an novel autonomous and relatively-large scale environment generator. Such a testbed could allow for preliminary operational planning and testing worldwide, without the need for on-site evaluation or data collection in the future.

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“…A combination of two 2.1 GHz 16 core processors, two NVIDIA GeForce RTX 2080ti, 2 TB SSD, and 10 TB HDD forms our server's hardware framework. A total of 107 containers were created during the CPS Challenge period [7]. A simulation session consists of a Lubuntu desktop equipped with widely used robotics software, that is accessible through a web URL.…”

Section: B System Descriptionmentioning

confidence: 99%

“…2 shows the OpenUAV platform's architecture that enabled a virtual competition during the pandemic. Further details on the architecture and implementation can be found on the OpenUAV paper [7].…”

Section: B System Descriptionmentioning

confidence: 99%

“…OpenUAV, a web-based robotics simulation software that enables students and researchers to run robotic simulations on the cloud, provided easy access to sUAS algorithm development and experiments, despite the pandemic [7]. It also allowed students from various countries to interact Authors are with the School of Earth and Space Exploration, Tempe, Arizona dpmick, snandan3, hanand4, jdas5@asu.edu, Stephen is a staff at Vanderbilt University, Nashville, Tennessee stephen.a.rees@vanderbilt.edu, and Srikar is with the Dept.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robotics During a Pandemic: The 2020 NSF CPS Virtual Challenge -- SoilScope, Mars Edition

Mick¹,

Siddarth²,

Nandan³

et al. 2021

Preprint

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Remote sample recovery is a rapidly evolving application of Small Unmanned Aircraft Systems (sUAS) for planetary sciences and space exploration. Development of cyberphysical systems (CPS) for autonomous deployment and recovery of sensor probes for sample caching is already in progress with NASA's MARS 2020 mission. To challenge student teams to develop autonomy for sample recovery settings, the 2020 NSF CPS Challenge was positioned around the launch of the MARS 2020 rover and sUAS duo. This paper discusses perception and trajectory planning for sample recovery by sUAS in a simulation environment. Out of a total of five teams that participated, the results of the top two teams have been discussed. The OpenUAV cloud simulation framework deployed on the Cyber-Physical Systems Virtual Organization (CPS-VO) allowed the teams to work remotely over a month during the COVID-19 pandemic to develop and simulate autonomous exploration algorithms. Remote simulation enabled teams across the globe to collaborate in experiments. The two teams approached the task of probe search, probe recovery, and landing on a moving target differently. This paper is a summary of teams' insights and lessons learned, as they chose from a wide range of perception sensors and algorithms.Web page: https://cps-vo.org/group/CPSchallenge

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OpenUAV Cloud Testbed: a Collaborative Design Studio for Field Robotics

Cited by 3 publications

References 18 publications

Advanced Co-Simulation Platform for UAV Simulations Under Virtual Wireless Network Environments

Advanced Co-Simulation Platform for UAV Simulations Under Virtual Wireless Network Environments

Autonomous Environment Generator for UAV-Based Simulation

Robotics During a Pandemic: The 2020 NSF CPS Virtual Challenge -- SoilScope, Mars Edition

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