Title
Performance comparison of physics engines to accelerate house-collapsing simulations
Abstract
House-collapsing simulation is an effective method for acquiring structural data regarding collapsed houses with the aim of understanding the properties of destroyed or disordered structures for designing and operating urban search and rescue (USAR) robots. The purpose of this study is to find an appropriate configuration of computer hardware and software that can accelerate house-collapsing simulations. This study compares the performances of three major physics engines, namely PhysX, Bullet Physics Library, and Open Dynamics Engine (ODE), on four computers equipped with different CPU and GPU configurations with respect to a sample structure, including a large number of rigid bodies combined with joint elements. Results of the experiments show that multi-threaded processing on PhysX has the best performance among the engines tested, and the use of multiple CPU and GPU configurations does not contribute to the acceleration of collapsing simulations for joint-connected rigid body structures in any of the evaluated versions of the physics engines. Based on the results, an existing simulation system for collapsing processes has been improved and can successfully speed up the process of collapsing simulations to approximately four times as fast as our previous system. To achieve greater speeds and larger-scale simulations, up-to-date physics engine technologies must be continuously examined and adopted for practical use in house-collapsing simulations.
Year
DOI
Venue
2016
10.1109/SSRR.2016.7784327
2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)
Keywords
Field
DocType
Collapsed house,simulation,physics engine,gareki
Urban search and rescue,Effective method,Simulation,Physics engine,Computer science,Rigid body,Software,Acceleration,Robot,Speedup
Conference
ISSN
ISBN
Citations 
2374-3247
978-1-5090-4350-7
1
PageRank 
References 
Authors
0.38
0
3
Name
Order
Citations
PageRank
Takuto Hamano110.38
Masahiko Onosato255.33
Fumiki Tanaka3146.82