In a world designed for legs, quadrupeds, bipeds, and humanoids have the opportunity to
impact emerging robotics applications from logistics, to agriculture, to home assistance. The …

The empirical success of reinforcement learning (RL) in contact-rich manipulation leaves
much to be understood from a model-based perspective, where the key difficulties are often …

This paper presents a contact-implicit model predictive control (MPC) framework for the real-
time discovery of multi-contact motions, without predefined contact mode sequences or …

Robots must make and break contact with the environment to perform useful tasks, but
planning and control through contact remains a formidable challenge. In this work, we …

This paper presents a contact-implicit model predictive control (MPC) framework for the real-
time discovery of multi-contact motions, without predefined contact mode sequences or …

Contact-implicit trajectory optimization offers an appealing method of automatically
generating complex and contact-rich behaviors for robot manipulation and locomotion. The …

Avoiding obstacles in the perceived world has been the classical approach to autonomous
mobile robot navigation. However, this usually leads to unnatural and inefficient motions that …

Nuclear energy will play a critical role in meeting clean energy targets worldwide. However,
nuclear environments are dangerous for humans to operate in due to the presence of highly …

We present a contact-implicit planning approach that can generate contact-interaction
trajectories for non-prehensile manipulation problems without tuning or a tailored initial …

The locomotion performance of the current legged miniature robots remains inferior
compared to even the most simple insects. The inferiority has led researchers to utilize …