7 accepted papers
We present a learning algorithm for training a single policy that imitates multiple gaits of a walking robot. To achieve this, we use and extend MPC-Net, which is an Imitation Learning approach guided by Model Predictive Control (MPC). The strategy of MPC-Net differs from many other approaches since…
We present an Imitation Learning approach for the control of dynamical systems with a known model. Our policy search method is guided by solutions from Model Predictive Control (MPC). Typical policy search methods of this kind minimize a distance metric between the guiding demonstrations and the lea
We present a reformulation of a contact-implicit optimization (CIO) approach that computes optimal trajectories for rigid-body systems in contact-rich settings. A hard-contact model is assumed, and the unilateral constraints are imposed in the form of complementarity conditions. Newton's impact law…
Locomotion planning for legged systems requires reasoning about suitable contact schedules. The contact sequence and timings constitute a hybrid dynamical system and prescribe a subset of achievable motions. State-of-the-art approaches cast motion planning as an optimal control problem. In order to…
The dynamics of legged systems are characterized by under-actuation, instability, and contact state switching. We present a trajectory optimization method for generating physically consistent motions under these conditions. By integrating a custom solver for hard contact forces in the system dynamic
We present a contact invariant trajectory optimization formulation to synthesize motions for legged robotic systems. The method is capable of finding optimal trajectories subject to whole-body dynamics with hard contacts. Contact switches are determined automatically. We make use of concepts from bi
In this letter, we present a whole-body nonlinear model predictive control approach for rigid body systems subject to contacts. We use a full-dynamic system model which also includes explicit contact dynamics. Therefore, contact locations, sequences, and timings are not prespecified but optimized by