Prashanth Ravichandar

Preferenced Oracle Guided Multi-mode Policies for Dynamic Bipedal Loco-Manipulation

Dynamic loco-manipulation calls for effective whole-body control and contact-rich interactions with the object and the environment. Existing learning-based control synthesis relies on training low-level skill policies and explicitly switching with a high-level policy or a hand-designed finite state