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Contact-implicit trajectory optimization offers an appealing method ofautomatically generating complex and contact-rich behaviors for robotmanipulation and locomotion. The scalability of such techniques has beenlimited, however, by the challenge of ensuring both numerical reliability andphysical realism. In this paper, we present preliminary results suggesting thatthe Iterative Linear Quadratic Regulator (iLQR) algorithm together with therecently proposed pressure-field-based hydroelastic contact model enablesreliable and physically realistic trajectory optimization through contact. Weuse this approach to synthesize contact-rich behaviors like quadrupedlocomotion and whole-arm manipulation. Furthermore, open-loop playback on aKinova Gen3 robot arm demonstrates the physical accuracy of the whole-armmanipulation trajectories. Code is available at https://bit.ly/ilqr_hc andvideos can be found at https://youtu.be/IqxJKbM8_ms.

Contact-Implicit Trajectory Optimization with Hydroelastic Contact and iLQR