IROS 2020poster12 citations

SynChrono: A Scalable, Physics-Based Simulation Platform For Testing Groups of Autonomous Vehicles and/or Robots

Jay Taves, Asher Elmquist, Aaron Young, Radu Serban, Dan Negrut

Abstract

This contribution is concerned with the topic of using simulation to understand the behavior of groups of mutually interacting autonomous vehicles (AVs) or robots engaged in traffic/maneuvers that involve coordinated operation. We outline the structure of a multi-agent simulator called SYN-CHRONO and provide results pertaining to its scalability and ability to run real-time scenarios with humans in the loop. SYN-CHRONO is a scalable multi-agent, high-fidelity environment whose purpose is that of testing AV and robot control strategies. Four main components make up the core of the simulation platform: a physics-based dynamics engine that can simulate rigid and compliant systems, fluid-solid interactions, and deformable terrains; a module that provides sensing simulation; an agent-to-agent communication server; dynamic virtual worlds, which host the interacting agents operating in a coordinated scenario. The platform provides a virtual proving ground that can be used to answer questions such as "what will an AV do when it skids on a patch of ice and moves one way while facing the other way?"; "is a new agent-control strategy robust enough to handle unforeseen circumstances?"; and "what is the effect of a loss of communication between agents engaged in a coordinated maneuver?". Full videos based on work in the paper are available at https://tinyurl.com/ChronoIROS2020 and additional descriptions on the particular version of software used is available at https://github.com/uwsbel/publications-data/tree/master/2020/IROS.

BibTeX
@inproceedings{iros2020_synchronoascalab,
  title = {SynChrono: A Scalable, Physics-Based Simulation Platform For Testing Groups of Autonomous Vehicles and/or Robots},
  author = {Jay Taves and Asher Elmquist and Aaron Young and Radu Serban and Dan Negrut},
  booktitle = {IROS 2020},
  year = {2020}
}