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 …

We introduce Pinocchio, an open-source software framework that implements rigid body
dynamics algorithms and their analytical derivatives. Pinocchio does not only include …

Locomotion of legged robots on arbitrary terrain using multiple contacts is yet an open
problem. To tackle it, a common approach is to rely on reduced template models (eg, the …

In this article, we present an intrinsically stable Model Predictive Control (IS-MPC)
framework for humanoid gait generation that incorporates a stability constraint in the …

A common strategy to generate efficient locomotion movements is to split the problem into
two consecutive steps: the first one generates the contact sequence together with the …

In this paper, we propose a deep neural network that predicts the feasibility of a mixed-
integer program from visual input for robot manipulation planning. Integrating learning into …

In this paper, we propose a deep convolutional recurrent neural network that predicts action
sequences for task and motion planning (TAMP) from an initial scene image. Typical TAMP …

In this article, we propose deep visual reasoning, which is a convolutional recurrent neural
network that predicts discrete action sequences from an initial scene image for sequential …

Capturability analysis of the linear inverted pendulum (LIP) model enabled walking with
constrained height based on the capture point. In this paper, we generalize this analysis to …

Motion planning in multicontact scenarios has recently gathered interest within the legged
robotics community, however actuator force/torque limits are rarely considered. We believe …