Online Gain Adaptation of Whole-Body Control for Legged Robots with Unknown Disturbances

This paper proposes an online gain adaptation approach to enhance the robustness of whole-body control (WBC) framework for legged robots under unknown external force disturbances. Without properly accounting for external forces, the closed-loop control system incorporating WBC may become unstable, and therefore the desired task goals may not be achievable. To study the effects of external disturbances, we analyze the behavior of our current WBC framework via the use of both full-body and centroidal dynamics. In turn, we propose a way to adapt feedback gains for stabilizing the controlled system automatically. Based on model approximations and stability theory, we propose three conditions to ensure that the adjusted gains are suitable for stabilizing a robot under WBC. The proposed approach has four contributions. We make it possible to estimate the unknown disturbances without force/torque sensors. We then compute adaptive gains based on theoretic stability analysis incorporating the unknown forces at the joint actuation level. We demonstrate that the proposed method reduces task tracking errors under the effect of external forces on the robot. In addition, the proposed method is easy-to-use without further modifications of the controllers and task specifications. The resulting gain adaptation process is able to run in real-time. Finally, we verify the effectiveness of our method both in simulations and experiments using the bipedal robot Draco2 and the humanoid robot Valkyrie.

Impaired Sensorimotor Adaption in Schizophrenia in Comparison to Age-Matched and Elderly Controls

<b><i>Background:</i></b> The “cognitive dysmetria hypothesis” of schizophrenia proposes a disrupted communication between the cerebellum and cerebral cortex, resulting in sensorimotor and cognitive symptoms. Sensorimotor adaptation relies strongly on the function of the cerebellum. <b><i>Objectives:</i></b> This study investigated whether sensorimotor adaptation is reduced in schizophrenia compared with age-matched and elderly healthy controls. <b><i>Methods:</i></b> Twenty-nine stably treated patients with schizophrenia, 30 age-matched, and 30 elderly controls were tested in three motor adaptation tasks in which visual movement feedback was unexpectedly altered. In the “rotation adaptation task” the perturbation consisted of a rotation (30° clockwise), in the “gain adaptation task” the extent of the movement feedback was reduced (by a factor of 0.7) and in the “vertical reversal task,” up- and downward pen movements were reversed by 180°. <b><i>Results:</i></b> Patients with schizophrenia adapted to the perturbations, but their movement times and errors were substantially larger than controls. Unexpectedly, the magnitude of adaptation was significantly smaller in schizophrenia than elderly participants. The impairment already occurred during the first adaptation trials, pointing to a decline in explicit strategy use. Additionally, post-adaptation aftereffects provided strong evidence for impaired implicit adaptation learning. Both negative and positive schizophrenia symptom severities were correlated with indices of the amount of adaptation and its aftereffects. <b><i>Conclusions:</i></b> Both explicit and implicit components of sensorimotor adaptation learning were reduced in patients with schizophrenia, adding to the evidence for a role of the cerebellum in the pathophysiology of schizophrenia. Elderly individuals outperformed schizophrenia patients in the adaptation learning tasks.

'Lose-to-gain' adaptation to genome decay in the structure of the smallest eukaryotic ribosomes

The evolution of microbial parasites involves the interplay of two opposing forces. On the one hand, the pressure to survive drives parasites to improve through Darwinian natural selection. On the other, frequent genetic drifts result in genome decay, an evolutionary process in which an ever-increasing burden of deleterious mutations leads to gene loss and gradual genome reduction. Here, seeking to understand how this interplay occurs at the scale of individual macromolecules, we describe cryo-EM and evolutionary analyses of ribosomes from Encephalitozoon cuniculi, a eukaryote with one of the most reduced genomes in nature. We show that E. cuniculi ribosomes, the smallest eukaryotic cytoplasmic ribosomes to be structurally characterized, employ unparalleled structural innovations that allow extreme rRNA reduction without loss of ribosome integrity. These innovations include the evolution of previously unknown rRNA features such as molten rRNA linkers and bulgeless rRNA. Furthermore, we show that E. cuniculi ribosomes withstand the loss of rRNA and protein segments by evolving a unique ability to effectively trap small molecules and use them as ribosomal building-blocks and structural mimics of degenerated rRNA and protein segments. Overall, our work reveals a recurrent evolutionary pattern, which we term 'lose-to-gain' evolution, where it is only through the loss of rRNA and protein segments that E. cuniculi ribosomes evolve their major innovations. Our study shows that the molecular structures of intracellular parasites long viewed as reduced, degenerated, and suffering from various debilitating mutations instead possess an array of systematically overlooked and extraordinary structural features. These features allow them to not only adapt to molecular reduction but evolve new activities that parasites can possibly use to their advantage.

Moving-horizon-estimator-integrated adaptive hierarchical sliding mode control for flexible hypersonic vehicles considering aeroservoelastic effect

In order to solve the attitude control problem of flexible hypersonic vehicles with consideration of aeroservoelastic effect, uncertainty and external disturbance, a novel moving-horizon-estimator-integrated adaptive hierarchical sliding mode control scheme is presented in this paper. First, the measurement model considering flexibility is established and the influence of aeroservoelastic effect on system stability is analyzed. Then moving horizon estimator is developed to reconstruct full state information from sensor measurements, while sliding mode disturbance observer and gain adaptation law is proposed to enhance the robustness and attenuate the chattering. Via combining moving horizon estimator, sliding mode disturbance observer, gain adaptation law and baseline hierarchical sliding mode controller, the moving-horizon-estimator-integrated adaptive hierarchical sliding mode control scheme that is able to achieve the control objective of both precise attitude control and active flexible vibration suppression is developed. Finally, Lyapunov theory is used to prove the stability of the proposed control scheme, and the numerical simulations are carried out, which further verify the effectiveness of the proposed control scheme against aeroservoelastic effect, uncertainty and external disturbance.

Tuning movement for sensing in an uncertain world

While animals track or search for targets, sensory organs make small unexplained movements on top of the primary task-related motions. While multiple theories for these movements exist—in that they support infotaxis, gain adaptation, spectral whitening, and high-pass filtering—predicted trajectories show poor fit to measured trajectories. We propose a new theory for these movements called energy-constrained proportional betting, where the probability of moving to a location is proportional to an expectation of how informative it will be balanced against the movement’s predicted energetic cost. Trajectories generated in this way show good agreement with measured trajectories of fish tracking an object using electrosense, a mammal and an insect localizing an odor source, and a moth tracking a flower using vision. Our theory unifies the metabolic cost of motion with information theory. It predicts sense organ movements in animals and can prescribe sensor motion for robots to enhance performance.

Mutations in PB2 and HA enhanced pathogenicity of H4N6 avian influenza virus in mice

The H4 subtype avian influenza virus (AIV) continues to circulate in both wild birds and poultry, and occasionally infects mammals (e.g. pigs). H4-specific antibodies have also been detected in poultry farm workers, which suggests that H4 AIV poses a potential threat to public health. However, the molecular mechanism by which H4 AIVs could gain adaptation to mammals and whether this has occurred remain largely unknown. To better understand this mechanism, an avirulent H4N6 strain (A/mallard/Beijing/21/2011, BJ21) was serially passaged in mice and mutations were characterized after passaging. A virulent mouse-adapted strain was generated after 12 passages, which was tentatively designated BJ21-MA. The BJ21-MA strain replicated more efficiently than the parental BJ21, both in vivo and in vitro. Molecular analysis of BJ21-MA identified four mutations, located in proteins PB2 (E158K and E627K) and HA (L331I and G453R, H3 numbering). Further studies showed that the introduction of E158K and/or E627K substitutions into PB2 significantly increased polymerase activity, which led to the enhanced replication and virulence of BJ21-MA. Although individual L331I or G453R substitutions in HA did not change the pathogenicity of BJ21 in mice, both mutations significantly enhanced virulence. In conclusion, our data presented in this study demonstrate that avian H4 virus can adapt to mammals by point mutations in PB2 or HA, which consequently poses a potential threat to public health.