Centroidal Dynamic

Centroidal dynamics simplifies robot motion planning by representing the complex, multi-body system as a single rigid body, focusing on the robot's center of mass and momentum. Current research emphasizes efficient algorithms, such as model predictive control (MPC) and quadratic programming (QP), to generate dynamically feasible trajectories for legged robots, often incorporating Spring-Loaded Inverted Pendulum (SLIP) models or full centroidal dynamics. This approach improves computational speed and robustness for tasks like walking, jumping, and even acrobatic maneuvers, impacting the development of more agile and adaptable robots in various applications.