Several SBEL-ites presented Chrono-related tutorials at the 2020 edition of the Machine-Ground Interaction Consortium (MaGIC). Asher Elmquist presented on Chrono::Sensor Jay Taves and Aaron Young presented on SynChrono Luning Fang presented on Chrono::Granular Radu Serban …
News
Two SBEL Students Win Poster Prize at MaGIC 2020
At the 2020 edition of the Machine-Ground Interaction Consortium (MaGIC), two SBEL students won a prize for the posters they presented on lab research. Alex Pletta won 1st prize with a poster on advanced control …
Chrono::GPU, Modeling and Simulation of Granular Dynamics using GPU Computing
Modeling granular system of large degree of freedom poses high computation cost. Chrono::GPU is designed to simulate granular material via the framework of Discrete Element Method (DEM) to produce realistic results. The physics-based features include …
SynChrono poster accepted to SC20
A SynChrono reinforcement learning poster was recently accepted for presentation at the SC20 supercomputing conference. The poster highlights machine-learning work with a convoy of autonomous vehicles operating cohesively on deformable off-road terrain. Several pieces of …
Chrono Integration with Cognitive Systems Lab Driving Simulator
SBEL has partnered with the Cognitive Systems Lab (CSL) and Professor Sue Ahn’s lab on an NSF-sponsored project to better understand traffic flows in the context of human takeover from autonomous vehicles. For research on …
Modeling Multiphase Flows with Incompressible SPH on GPU
Incompressible multiphase flows with complex interface geometries are involved in many industrial and environmental applications. In contrast to the widely-used Eulerian approaches, as a Lagrangian method, SPH handles the interface representation naturally without the need …
Learned behavior on hilly off-road terrain
Drawing on Chrono::Vehicle, Chrono::Sensor, PyChrono and GymChrono, SBEL recently presented exciting off-road research at the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS). Aaron and Simone used GymChrono and PyChrono to train humvees to drive …
SynChrono Moves Off-Road
The SynChrono autonomous vehicle simulation platform has recently added support for SCM deformable terrain, allowing vehicles to operate in time coherent off-road environments. The first video shown below is a proof of concept where a …
Chrono::Sensor – modeling and simulating virtual sensors for robots and autonomous vehicles
Chrono::Sensor is a specialized module in Project Chrono for the modeling and simulation of sensors within a Chrono simulation. This simulation module is in development with current support for simulation of camera, lidar, GPS, and …
Synchrono: A Multi-Agent Simulation Framework for Robotics and Autonomous Vehicle Applications
SynChrono is a framework in which dynamic multi-agent simulations can be conducted to understand agent interplay and develop control algorithms in a safe and flexible environment. To create a virtual proving grounds for autonomous vehicles …