No abstract

This paper presents a momentum-based control framework for floating-base robots and its application to the humanoid robot “Atlas”. At the heart of the control framework lies a quadratic program that reconciles motion tasks expressed as constraints on the joint acceleration vector with the limitations due to unilateral ground contact and force-limited grasping. We elaborate on necessary adaptations required to move from simulation to real hardware and present results for walking across rough terrain, basic manipulation, and multi-contact balancing on sloped surfaces (the latter in simulation only). The presented control framework was used to secure second place in both the DARPA Robotics Challenge Trials in December 2013 and the Finals in June 2015.

Fig. 1: The torque-controlled humanoid robot TORO and its development stages from 2010 (DLR Biped [1]) to 2014.Abstract-This paper gives an overview on the torquecontrolled humanoid robot TORO, which has evolved from the former DLR Biped. In particular, we describe its mechanical design and dimensioning, its sensors, electronics and computer hardware. Additionally, we give a short introduction to the walking and multi-contact balancing strategies used for TORO.

In this paper, we extend the Divergent Component of Motion (DCM, also called 'Capture Point') to 3D. We introduce the "Enhanced Centroidal Moment Pivot point" (eCMP) and the "Virtual Repellent Point" (VRP), which allow for the encoding of both direction and magnitude of the external (e.g. leg) forces and the total force (i.e. external forces plus gravity) acting on the robot. Based on eCMP, VRP and DCM, we present a method for real-time planning and control of DCM trajectories in 3D. We address the problem of underactuation and propose methods to guarantee feasibility of the finally commanded forces. The capabilities of the proposed control framework are verified in simulations.

This paper builds up on the Capture Point concept and exploits the simple form of the dynamical equations of the Linear Inverted Pendulum model when formulated in terms of the center of mass and the Capture Point. The presented methods include (i) the derivation of a Capture Point (CP) control principle based on the natural dynamics of the linear inverted pendulum (LIP), which stabilizes the walking robot and motivates (ii) the design of a CP tracking and a CP endof-step controller. The exponential stability of the CP control law is proven. Tilting is avoided by proper projection of the commanded zero moment point. The robustness of the derived control algorithms is analyzed analytically and verified in simulation and experiments.