google-deepmind/mujoco is a general-purpose physics simulator that handles articulated structures and contact dynamics (contact dynamics, the influence that forces arising from contact have on the motion of an articulated body). It is an engine that computes and reproduces situations in which an articulated body and its surrounding environment physically act on each other. The most recent release on record is 3.16.0. However, the changelog for this version is not in the given record, so what was added cannot be confirmed.
The README describes MuJoCo as a general-purpose physics engine maintained by Google DeepMind. It says the project supports research and development that simulates articulated structures interacting with their environment — as in robotics, biomechanics, graphics, animation and machine learning — quickly and accurately. It provides a performance-oriented C API and runtime simulation modules, and its built-in XML compiler uses preallocated low-level data structures. It also provides a native GUI rendered with OpenGL, Python bindings, and a Unity game engine plugin. The primary language is C++, the license is Apache-2.0, and the GitHub star count is 15781, with the repository creation date recorded as August 27, 2021.
However, the momentum score in the research record is 5.2 out of 10, a middling level, and the novelty, technology and quality scores are not listed. The given information contains no performance figures backing the fast and accurate simulation the README describes, nor any comparison results against other physics engines. Because the evidence is that thin, it is closer to a project worth checking as a candidate for work that requires joint contact simulation than one to adopt right away.