  Contact-implicit trajectory optimization offers an appealing method of
automatically generating complex and contact-rich behaviors for robot
manipulation and locomotion. The scalability of such techniques has been
limited, however, by the challenge of ensuring both numerical reliability and
physical realism. In this paper, we present preliminary results suggesting that
the Iterative Linear Quadratic Regulator (iLQR) algorithm together with the
recently proposed pressure-field-based hydroelastic contact model enables
reliable and physically realistic trajectory optimization through contact. We
use this approach to synthesize contact-rich behaviors like quadruped
locomotion and whole-arm manipulation. Furthermore, open-loop playback on a
Kinova Gen3 robot arm demonstrates the physical accuracy of the whole-arm
manipulation trajectories. Code is available at https://bit.ly/ilqr_hc and
videos can be found at https://youtu.be/IqxJKbM8_ms.
