A Model Predictive Capture Point Control Framework for Robust Humanoid Balancing via Ankle, Hip, and Stepping Strategies

The robust balancing capability of humanoid robots against disturbances has been considered as one of the crucial requirements for their practical mobility in real-world environments. In particular, many studies have been devoted to the efficient implementation of the three balance strategies, inspired by human balance strategies involving ankle, hip, and stepping strategies, to endow humanoid robots with human-level balancing capability. In this paper, a robust balance control framework for humanoid robots is proposed. Firstly, a novel Model Predictive Control (MPC) framework is proposed for Capture Point (CP) tracking control, enabling the integration of ankle, hip, and stepping strategies within a single framework. Additionally, a variable weighting method is introduced that adjusts the weighting parameters of the Centroidal Angular Momentum (CAM) damping control over the time horizon of MPC to improve the balancing performance. Secondly, a hierarchical structure of the MPC and a stepping controller was proposed, allowing for the step time optimization. The robust balancing performance of the proposed method is validated through extensive simulations and real robot experiments. Furthermore, a superior balancing performance is demonstrated, particularly in the presence of disturbances, compared to a state-of-the-art Quadratic Programming (QP)-based CP controller that employs the ankle, hip, and stepping strategies. The supplementary video is available at https://youtu.be/CrD75UbYzdcComment: 19 pages,13 figure

Proprioceptive External Torque Learning for Floating Base Robot and its Applications to Humanoid Locomotion

The estimation of external joint torque and contact wrench is essential for achieving stable locomotion of humanoids and safety-oriented robots. Although the contact wrench on the foot of humanoids can be measured using a force-torque sensor (FTS), FTS increases the cost, inertia, complexity, and failure possibility of the system. This paper introduces a method for learning external joint torque solely using proprioceptive sensors (encoders and IMUs) for a floating base robot. For learning, the GRU network is used and random walking data is collected. Real robot experiments demonstrate that the network can estimate the external torque and contact wrench with significantly smaller errors compared to the model-based method, momentum observer (MOB) with friction modeling. The study also validates that the estimated contact wrench can be utilized for zero moment point (ZMP) feedback control, enabling stable walking. Moreover, even when the robot's feet and the inertia of the upper body are changed, the trained network shows consistent performance with a model-based calibration. This result demonstrates the possibility of removing FTS on the robot, which reduces the disadvantages of hardware sensors. The summary video is available at https://youtu.be/gT1D4tOiKpo.Comment: Accepted by 2023 IROS conferenc

Solid State Polymerization of Biodegradable Poly(butylene sebacate-co-terephthalate): A Rapid, Facile Method for Property Enhancement

Poly(butylene sebacate-co-terephthalate) (PBSeT) has generated attention as a promising biopolymer for preparing bioplastics. However, there are limited studies on the synthesis of PBSeT, impeding its commercialization. Herein, with a view to addressing this challenge, biodegradable PBSeT was modified using solid state polymerization (SSP) with various ranges of time and temperature. The SSP used three different temperatures below the melting temperature of PBSeT. The polymerization degree of SSP was investigated using Fourier-transform infrared spectroscopy. The changes in the rheological properties of PBSeT after SSP were investigated using a rheometer and an Ubbelodhe viscometer. Differential scanning calorimetry and X-ray diffraction showed that the crystallinity of PBSeT was higher after SSP. The investigation revealed that after SSP for 40 min at 90 °C, PBSeT exhibited higher intrinsic viscosity (increased from 0.47 to 0.53 dL/g), crystallinity, and complex viscosity than PBSeT polymerized at other temperatures. However, a high SSP processing time resulted in a decrease in these values. In this experiment, SSP was most effectively performed in the temperature range closest to the melting temperature of PBSeT. This indicates that SSP could be a facile and rapid method for improving the crystallinity and thermal stability of synthesized PBSeT

MicroRNA miR-274-5p Suppresses <i>Found-in-Neurons</i> Associated with Melanotic Mass Formation and Developmental Growth in <i>Drosophila</i>

The hematopoietic system plays a crucial role in immune defense response and normal development, and it is regulated by various factors from other tissues. The dysregulation of hematopoiesis is associated with melanotic mass formation; however, the molecular mechanisms underlying this process are poorly understood. Here, we observed that the overexpression of miR-274 in the fat body resulted in the formation of melanotic masses. Moreover, abnormal activation of the JNK and JAK/STAT signaling pathways was linked to these consequences. In addition to this defect, miR-274 overexpression in the larval fat body decreased the total tissue size, leading to a reduction in body weight. miR-274-5p was found to directly suppress the expression of found-in-neurons (fne), which encodes an RNA-binding protein. Similar to the effects of miR-274 overexpression, fne depletion led to melanotic mass formation and growth reduction. Collectively, miR-274 plays a regulatory role in the fne–JNK signaling axis in melanotic mass formation and growth control