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

Jay Taves, Asher Elmquist, Aaron J. Young, Radu Serban, Dan Negruţ

Year
2020
Citations
6

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.

Keywords

Physics engineScalabilityComputer scienceRobotDistributed computingSoftwareFidelityDynamical simulationHost (biology)Virtual machine

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