Multibody Dynamics

The field models interconnected bodies—from robot arms and closed-chain mechanisms to cables and spacecraft—to predict motion, forces, and actuator loads. Common approaches include Lagrangian and Newton–Euler equations, Featherstone’s recursive algorithms, and constrained solvers for joint loops and contact; differentiable simulators and learned graph models extend these tools to optimization and data-driven prediction. Work spans contact-rich robot control, GPU-batched simulation, and comparisons with physical robot or mechanism measurements. A central challenge is balancing physical fidelity, especially for friction and changing contacts, with the speed and reliable gradients needed for large-scale learning and control.