Nicholas Paine

Time delay is a common phenomenon in robotic systems due to computational requirements and communication properties between or within high-level and low-level controllers as well as the physical constraints of the actuator and sensor. It is widely believed that delays are harmful for robotic systems in terms of stability and performance; however, we propose a different view that the time delay of the system may in some cases benefit system stability and performance. Therefore, in this paper, we discuss the influences of the displacement-feedback delay (single delay) and both displacement and velocity feedback delays (double delays) on robotic actuator systems by using the cluster treatment of characteristic roots (CTCR) methodology. Hence, we can ascertain the exact stability interval for single-delay systems and the rigorous stability region for double-delay systems. The influences of controller gains and the filtering frequency on the stability of the system are discussed. Based on the stability information coupled with the dominant root distribution, we propose one nonconventional rule which suggests increasing time delay to certain time windows to obtain the optimal system performance. The computation results are also verified on an actuator testbed.

This paper presents an in-depth system-level experimental analysis comparing air-cooled and liquid-cooled commercial off-the-shelf (COTS) electric motors. Typically, liquid-cooled electric motors are reserved for large, expensive, high-end applications where the design of the motor’s electromagnetic components are closely coupled to its cooling system. By applying liquid cooling to a pre-existing motor design, this work helps bring the performance advantages of liquid cooling to smaller scale and lower cost applications. Prior work in this area gives little insight to designers of such systems. Conversely, this work aims to improve the understanding of liquid-cooled COTS motors by reporting empirically-observed factors of improvement for motor current, torque, output power and system efficiency. These measurements are obtained using a new liquid-cooled motor housing design that improves the ease of maintenance and component reuse compared to existing work. It is confirmed that datasheet motor thermal properties may serve as a reasonable guide for anticipating continuous torque performance, but may over-specify continuous power output. For the motor used in this test, continuous torque output is increased by a factor of 2.58, matching to within 9% of expected datasheet values. Continuous power output is increased by a factor of two with only 2.2% reduced efficiency compared to air-cooling.

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.

Robotic control systems are increasingly relying on distributed feedback controllers to tackle complex sensing and decision problems such as those found in highly articulated human-centered robots. These demands come at the cost of a growing computational burden and, as a result, larger controller latencies. To maximize robustness to mechanical disturbances by maximizing control feedback gains, this paper emphasizes the necessity for compromise between high- and low-level feedback control effort in distributed controllers. Specifically, the effect of distributed impedance controllers is studied where damping feedback effort is executed in close proximity to the control plant and stiffness feedback effort is executed in a latency-prone centralized control process. A central observation is that the stability of high impedance distributed controllers is very sensitive to damping feedback delay but much less to stiffness feedback delay. This study pursues a detailed analysis of this observation that leads to a physical understanding of the disparity. Then a practical controller breakdown gain rule is derived to aim at enabling control designers to consider the benefits of implementing their control applications in a distributed fashion. These considerations are further validated through the analysis, simulation and experimental testing on high performance actuators and on an omnidirectional mobile base.

This paper introduces a simple and effective method for selecting the maximum feedback gains in PD-type controllers applied to actuators where feedback delay and derivative signal filtering are present. The method provides the maximum feedback parameters that satisfy a phase margin criteria, producing a closed-loop system with high stability and a dynamic response with near-minimum settling time. Our approach is unique in that it simultaneously possesses: (1) a model of real-world performance-limiting factors (i.e., filtering and delay), (2) the ability to meet performance and stability criteria, and (3) the simplicity of a single closed-form expression. A central focus of our approach is the characterization of system stability through exhaustive searches of the feedback parameter space. Using this search-based method, we locate a set of maximum feedback parameters based on a phase margin criteria. We then fit continuous equations to this data and obtain a closed-form expression which matches the sampled data to within 2–4% error for the majority of the parameter space. We apply our feedback parameter selection method to two real-world actuators with widely differing system properties and show that our method successfully produces the maximum achievable nonoscillating impedance response.