This paper discusses the actuator-level control of Valkyrie, a new humanoid robot designed by NASA's Johnson Space Center in collaboration with several external partners. Several topics pertaining to Valkyrie's series elastic actuators are presented including control architecture, controller design, and implementation in hardware. A decentralized approach is taken in controlling Valkyrie's many series elastic degrees of freedom. By conceptually decoupling actuator dynamics from robot limb dynamics, the problem of controlling a highly complex system is simplified and the controller development process is streamlined compared to other approaches. This hierarchical control abstraction is realized by leveraging disturbance observers in the robot's joint-level torque controllers. A novel analysis technique is applied to understand the ability of a disturbance observer to attenuate the effects of unmodeled dynamics. The performance of this control approach is demonstrated in two ways. First, torque tracking performance of a single Valkyrie actuator is characterized in terms of controllable torque resolution, tracking error, bandwidth, and power consumption. Second, tests are performed on Valkyrie's arm, a serial chain of actuators, to demonstrate the robot's ability to accurately track torques with the presented decentralized control approach. C 2015 Wiley Periodicals, Inc.

In December 2013, 16 teams from around the world gathered at Homestead Speedway near Miami, FL to participate in the DARPA Robotics Challenge (DRC) Trials, an aggressive robotics competition partly inspired by the aftermath of the Fukushima Daiichi reactor incident. While the focus of the DRC Trials is to advance robotics for use in austere and inhospitable environments, the objectives of the DRC are to progress the areas of supervised autonomy and mobile manipulation for everyday robotics. NASA's Johnson Space Center led a team comprised of numerous partners to develop Valkyrie, NASA's first bipedal humanoid robot. Valkyrie is a 44 degree‐of‐freedom, series elastic actuator‐based robot that draws upon over 18 years of humanoid robotics design heritage. Valkyrie's application intent is aimed at not only responding to events like Fukushima, but also advancing human spaceflight endeavors in extraterrestrial planetary settings. This paper presents a brief system overview, detailing Valkyrie's mechatronic subsystems, followed by a summarization of the inverse kinematics‐based walking algorithm employed at the Trials. Next, the software and control architectures are highlighted along with a description of the operator interface tools. Finally, some closing remarks are given about the competition, and a vision of future work is provided.

The fidelity with which series elastic actuators (SEAs) render desired impedances is important. Numerous approaches to SEA impedance control have been developed under the premise that high-precision actuator torque control is a prerequisite. Indeed, the design of an inner torque compensator has a significant impact on actuator impedance rendering. The disturbance observer (DOB) based torque control implemented in NASA's Valkyrie robot is considered here and a mathematical model of this torque control, cascaded with an outer impedance compensator, is constructed. While previous work has examined the impact a disturbance observer has on torque control performance, little has been done regarding DOBs and impedance rendering accuracy. Both simulation and a series of experiments are used to demonstrate the significant improvements possible in an SEA's ability to render desired dynamic behaviors when utilizing a DOB. Actuator transparency at low impedances is improved, closed loop hysteresis is reduced, and the actuator's dynamic response to both commands and interaction torques more faithfully matches that of the desired model. All of this is achieved by leveraging DOB based control rather than increasing compensator gains, thus making improved SEA impedance control easier to achieve in practice.

This paper presents a method for embedded motor control based upon rapidly exponentially stabilizing control Lyapunov functions (RES-CLFs) implemented through Quadratic Programs (QPs). This will give guaranteed exponential convergence via an optimal nonsmooth nonlinear embedded level controller that provides the minimal control effort necessary to achieve the desired convergence in torque. Utilizing this novel control methodology, we are able to formally establish that the dynamics of series elastic systems can be approximated by rigid system models. Importantly, the RES-CLF based QP is presented in a way that will allow for its real-time implementation at the embedded level via a closed form solution to a QP; the end result is a nonlinear optimal controller able to run at over 5 kHz. To demonstrate this, simulation and experimental results are presented showing the performance of the embedded controller. 53rd IEEE Conference on Decision and Control