ROS middle-layer integration into Unity3D as an interface option for propulsion drive simulations of autonomous vehicles

Proceedings of the Estonian Academy of Sciences

Anton Rassõlkin¹  Viktor Rjabtšikov²  Sergei Jegorov³  Vladimir Kuts³ 

[1] Corresponding author, [e-mail];Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia, Department of Electrical Engineering and Automation, Aalto University, P.O. Box 15500, FI-00076 Aalto, Finland;Department of Mechanical and Industrial Engineering, School of Engineering, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia;

关键词: ros;    autonomous vehicles;    propulsion drives;    digital twins;    simulations.;   

DOI  :  10.3176/proc.2021.4.04

来源: DOAJ

【 摘 要 】

As autonomous vehicle development continues at growing speeds, so does the need to optimize, diagnose, and test various elements of autonomous systems under different conditions. Since such processes should be carried out in parallel, it may result in bottlenecks in development and increased complexity. The trend for Digital Twins offers a promising option for the diagnosis and testing to be carried out separately from the physical devices, incl. autonomous vehicles in the virtual world. The idea of intercommunication between virtual and physical twins provides possibilities to estimate risks, drawbacks, physical damages to the vehicle’s drive systems, and the physical vehicleʼs critical conditions. Although providing communications between these systems arises at the speed that will be adequate to represent the physical vehicle in the virtual world correctly, it is still a trendy topic. This paper aims to demonstrate the enhancement of communications by using the Robot Operating System (ROS) as a middleware interface between two twinning systems by the example of the autonomous vehicleʼs propulsion drive. Data gathered from the physical and virtual worlds can be exchanged in the middle to allow for continuous training and optimization of the propulsion drive model, which would lead to more efficient path planning and energy-efficient drive of the autonomous vehicle itself. Additionally, a comparative analysis of ROS and its next version ROS2 is provided, discussing their differences and outlining drawbacks.

【 授权许可】

Unknown