  Legged robot locomotion requires the planning of stable reference
trajectories, especially while traversing uneven terrain. The proposed
trajectory optimization framework is capable of generating dynamically stable
base and footstep trajectories for multiple steps. The locomotion task can be
defined with contact locations, base motion or both, making the algorithm
suitable for multiple scenarios (e.g., presence of moving obstacles). The
planner uses a simplified momentum-based task space model for the robot
dynamics, allowing computation times that are fast enough for online
replanning.This fast planning capabilitiy also enables the quadruped to
accommodate for drift and environmental changes. The algorithm is tested on
simulation and a real robot across multiple scenarios, which includes uneven
terrain, stairs and moving obstacles. The results show that the planner is
capable of generating stable trajectories in the real robot even when a box of
15 cm height is placed in front of its path at the last moment.
