Sebastiano Mandalà

MuJoCo 4.0 from Google DeepMind is the first major version of the physics engine since 3.0, three years ago. Its headline feature, speculative contacts, keeps thin and fast objects from passing through each other, which allows much larger timesteps. The problem • Collision detection checks geom poses only at discrete timesteps. A thin or fast object can move further than its own thickness in one step and tunnel through, so the usual fixes are a smaller timestep or an inflated margin. How it works • Speculative contacts: each fast-moving geom is swept forward through the step to find when it would hit something. The solver gets a contact like any other that stops the motion at the surface, with no sub-stepping. • Deformables are now solved implicitly together with rigid bodies, joints and tendons, which keeps cables, cloth and shells stable at 5-10x larger timesteps. New are penetration-free cloth and elastic rods with bending and twist. • Plasticity: wires, clay, folded paper and metal foil now keep their dents and creases. Does it pay off? • In the team's tests, an arm catches a 0.7 mm playing card falling at over 2 m/s with a 16 ms timestep every time, where discrete collision detection misses it above 8 ms. • Humanoid stair climbing and thin-object grasping run 6 to 9 times faster, because they can use larger timesteps. Also in 4.0 • MuJoCo Studio, a new viewer SDK with physically based rendering. The same tools run in a browser tab with nothing to install. • MuJoCo Playground 1.0 ships alongside. Caveats • The speedups and timestep factors are the team's own measurements, without benchmark details in the announcement. • Speculative contacts predict motion from pre-step velocities, so a slow geom pushed across an obstacle within one step can still tunnel. They cover convex primitives and meshes on CPU. Heightfields, SDFs, flexes, MJX and MuJoCo Warp are listed as coming next. • Breaking changes: composite bodies, the cable and shell plugins and flexvert equalities are removed, Python 3.10 is dropped, and 3.x installs need a pip uninstall first. By @yuvaltassa and the Google DeepMind Robotics Simulation Team.