  Online planning of whole-body motions for legged robots is challenging due to
the inherent nonlinearity in the robot dynamics. In this work, we propose a
nonlinear MPC framework, the BiConMP which can generate whole body trajectories
online by efficiently exploiting the structure of the robot dynamics. BiConMP
is used to generate various cyclic gaits on a real quadruped robot and its
performance is evaluated on different terrain, countering unforeseen pushes and
transitioning online between different gaits. Further, the ability of BiConMP
to generate non-trivial acyclic whole-body dynamic motions on the robot is
presented. The same approach is also used to generate various dynamic motions
in MPC on a humanoid robot (Talos) and another quadruped robot (AnYmal) in
simulation. Finally, an extensive empirical analysis on the effects of planning
horizon and frequency on the nonlinear MPC framework is reported and discussed.
