In this article, we present a general approach for controlling robotic systems that make and
break contact with their environments. Contact-implicit model predictive control (CI-MPC) …

Hybrid dynamical systems, ie, systems that have both continuous and discrete states, are
ubiquitous in engineering but are difficult to work with due to their discontinuous transitions …

Cooperative trajectory planning of connected autonomous vehicles (CAVs) generally admits
strong nonlinearity and non-convexity, rendering great difficulties in finding the optimal …

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 …

Legged robots in general, and quadrupedal structures in particular, have demonstrated high
potential as a means of locomotion, possessing the ability to carry out tasks that traditional …

Specialized motions such as jumping are often achieved on quadruped robots by solving a
trajectory optimization problem once and executing the trajectory using a tracking controller …

In order to perform highly dynamic and agile maneuvers, legged robots typically spend time
in underactuated domains (eg with feet off the ground) where the system has limited …

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 …

This work addresses the problem of optimally steering the state covariance of a linear
stochastic system from an initial to a target, subject to hybrid transitions. The nonlinear and …