Multi-Joint dynamics with Contact (MuJoCo).We evaluated the most widely-used physics engines for robotics and machine learning applications. Please read this page for more backgrounds. In the benchmark tests, we investigated different characteristics of the contact model and multibody dynamics algorithms that each physics engine applies. Most state-of-the-art physics engines, therefore, adopt linear complex algorithms that solve the problem in an efficient manner. Moreover, physics engine requires efficient multibody dynamics implementation to be used for complex robot systems.įor robotic articulated systems that have multiple joints and links, solving the multibody dynamics is considerably expensive as $n$ links have $O(n^3)$ complexity. To make the problem tractable, physics engines approximate the contact problem as a relaxed problem that enables using efficient solving methods.Įach method has different characteristics, but some of them significantly sacrifice the accuracy of the contact solution that leads to the poor reality of the simulation.
Solving contact dynamics is NP-hard problem due to its non-convexity and discontinuity. Our primary goal is to aid robotics researchers to select the best physics engine for their applications.Ĭontact and Multibody Dynamics of Physics Engines In this project, we seek to provide an comprehensive evaluation of the accuracy and the speed of contact simulation on the most widely-used physics engines for various situation scenes from single-bodies with a limited number of contacts to complex articulated robotic systems with PD control input.
#Webots physics simulator
Many rigid body simulation tools that simulate contact dynamics has been introduced to the robotics society, yet the field is fragmented without strong dominance.įor robotics researchers, it is challenging to find and select the best simulator suits to their robotics tasks among numerous options. It is natural to pursue the realistic and efficient contact simulation for legged robotics research, which enables the successful control of robot locomotion strategy or end-to-end training. Notably, the motion of legged robots is highly dependent on the contact force generated by a feet-terrain interaction that drives the entire body.
#Webots physics software
SimBenchmark | Physics engine benchmark for robotics applications: RaiSim vs.
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