From Knowing to Doing: Learning Diverse Motor Skills through Instruction Learning

Recent years have witnessed many successful trials in the robot learning field. For contact-rich robotic tasks, it is challenging to learn coordinated motor skills by reinforcement learning. Imitation learning solves this problem by using a mimic reward to encourage the robot to track a given reference trajectory. However, imitation learning is not so efficient and may constrain the learned motion. In this paper, we propose instruction learning, which is inspired by the human learning process and is highly efficient, flexible, and versatile for robot motion learning. Instead of using a reference signal in the reward, instruction learning applies a reference signal directly as a feedforward action, and it is combined with a feedback action learned by reinforcement learning to control the robot. Besides, we propose the action bounding technique and remove the mimic reward, which is shown to be crucial for efficient and flexible learning. We compare the performance of instruction learning with imitation learning, indicating that instruction learning can greatly speed up the training process and guarantee learning the desired motion correctly. The effectiveness of instruction learning is validated through a bunch of motion learning examples for a biped robot and a quadruped robot, where skills can be learned typically within several million steps. Besides, we also conduct sim-to-real transfer and online learning experiments on a real quadruped robot. Instruction learning has shown great merits and potential, making it a promising alternative for imitation learning

Quadruped robot traversing 3D complex environments with limited perception

Traversing 3-D complex environments has always been a significant challenge for legged locomotion. Existing methods typically rely on external sensors such as vision and lidar to preemptively react to obstacles by acquiring environmental information. However, in scenarios like nighttime or dense forests, external sensors often fail to function properly, necessitating robots to rely on proprioceptive sensors to perceive diverse obstacles in the environment and respond promptly. This task is undeniably challenging. Our research finds that methods based on collision detection can enhance a robot's perception of environmental obstacles. In this work, we propose an end-to-end learning-based quadruped robot motion controller that relies solely on proprioceptive sensing. This controller can accurately detect, localize, and agilely respond to collisions in unknown and complex 3D environments, thereby improving the robot's traversability in complex environments. We demonstrate in both simulation and real-world experiments that our method enables quadruped robots to successfully traverse challenging obstacles in various complex environments.Comment: 10 pages, 8 figures,submitted to iros202

Towards Efficient Communications in Federated Learning: A Contemporary Survey

In the traditional distributed machine learning scenario, the user's private data is transmitted between nodes and a central server, which results in great potential privacy risks. In order to balance the issues of data privacy and joint training of models, federated learning (FL) is proposed as a special distributed machine learning with a privacy protection mechanism, which can realize multi-party collaborative computing without revealing the original data. However, in practice, FL faces many challenging communication problems. This review aims to clarify the relationship between these communication problems, and focus on systematically analyzing the research progress of FL communication work from three perspectives: communication efficiency, communication environment, and communication resource allocation. Firstly, we sort out the current challenges existing in the communications of FL. Secondly, we have compiled articles related to FL communications, and then describe the development trend of the entire field guided by the logical relationship between them. Finally, we point out the future research directions for communications in FL

Visual-tactile Fusion for Transparent Object Grasping in Complex Backgrounds

The accurate detection and grasping of transparent objects are challenging but of significance to robots. Here, a visual-tactile fusion framework for transparent object grasping under complex backgrounds and variant light conditions is proposed, including the grasping position detection, tactile calibration, and visual-tactile fusion based classification. First, a multi-scene synthetic grasping dataset generation method with a Gaussian distribution based data annotation is proposed. Besides, a novel grasping network named TGCNN is proposed for grasping position detection, showing good results in both synthetic and real scenes. In tactile calibration, inspired by human grasping, a fully convolutional network based tactile feature extraction method and a central location based adaptive grasping strategy are designed, improving the success rate by 36.7% compared to direct grasping. Furthermore, a visual-tactile fusion method is proposed for transparent objects classification, which improves the classification accuracy by 34%. The proposed framework synergizes the advantages of vision and touch, and greatly improves the grasping efficiency of transparent objects.Comment: Publishe

A noise-resistant and annotation-free supervoxel-based algorithm for rapid segmentation of multiphase X-ray images

This study introduces a three-dimensional supervoxel segmentation method to accurately separate solid and fluid phases in X-ray images of porous materials, with applications in energy research. Compared with intelligent segmentation algorithms requiring model training, the proposed method operates as a ready-to-use solution with significantly enhanced efficiency. When benchmarked against conventional approaches such as watershed transformation, our technique demonstrates superior segmentation accuracy. Tested on porous rock and gas diffusion layers under varying wettability, it accurately quantifies fluid saturation, interfacial area, curvature, and contact angles—key parameters for enhanced oil recovery, CO2 storage, and hydrogen fuel cells. The proposed three-dimensional segmentation method is noise-resistant and annotation-free, improving both the accuracy and efficiency of segmenting diverse micro-structural material datasets and providing reliable measurements of their geometric characteristics.Document Type: Original articleCited as: Ye, S., Song, X., Ma, Z., Gao, Y., Zhu, L., Zhou, M., Xiao, L., Wen, G., Bijeljic, B., Blunt, M. J. A noise-resistant and annotation-free supervoxel-based algorithm for rapid segmentation of multiphase X-ray images. Advances in Geo-Energy Research, 2025, 16(1): 50-59. https://doi.org/10.46690/ager.2025.04.06

Structural Basis for Recognition of Human Enterovirus 71 by a Bivalent Broadly Neutralizing Monoclonal Antibody

Enterovirus 71 (EV71) is the main pathogen responsible for hand, foot and mouth disease with severe neurological complications and even death in young children. We have recently identified a highly potent anti-EV71 neutralizing monoclonal antibody, termed D5. Here we investigated the structural basis for recognition of EV71 by the antibody D5. Four three-dimensional structures of EV71 particles in complex with IgG or Fab of D5 were reconstructed by cryo-electron microscopy (cryo-EM) single particle analysis all at subnanometer resolutions. The most critical EV71 mature virion-Fab structure was resolved to a resolution of 4.8 Å, which is rare in cryo-EM studies of virus-antibody complex so far. The structures reveal a bivalent binding pattern of D5 antibody across the icosahedral 2-fold axis on mature virion, suggesting that D5 binding may rigidify virions to prevent their conformational changes required for subsequent RNA release. Moreover, we also identified that the complementary determining region 3 (CDR3) of D5 heavy chain directly interacts with the extremely conserved VP1 GH-loop of EV71, which was validated by biochemical and virological assays. We further showed that D5 is indeed able to neutralize a variety of EV71 genotypes and strains. Moreover, D5 could potently confer protection in a mouse model of EV71 infection. Since the conserved VP1 GH-loop is involved in EV71 binding with its uncoating receptor, the scavenger receptor class B, member 2 (SCARB2), the broadly neutralizing ability of D5 might attribute to its inhibition of EV71 from binding SCARB2. Altogether, our results elucidate the structural basis for the binding and neutralization of EV71 by the broadly neutralizing antibody D5, thereby enhancing our understanding of antibody-based protection against EV71 infection. © 2016 Ye et al

Functional profile of perilesional gray matter in focal cortical dysplasia: an fMRI study

ObjectivesWe aim to investigate the functional profiles of perilesional gray matter (GM) in epileptic patients with focal cortical dysplasia (FCD) and to correlate these profiles with FCD II subtypes, surgical outcomes, and different antiseizure medications (ASMs) treatment response patterns.MethodsNine patients with drug-responsive epilepsy and 30 patients with drug-resistant epilepsy (11 were histologically confirmed FCD type IIa, 19 were FCD type IIb) were included. Individual-specific perilesional GM and contralateral homotopic GM layer masks were generated. These masks underwent a two-voxel (2 mm) dilation from the FCD lesion and contralateral homotopic region, resulting in 10 GM layers (20 mm). Layer 1, the innermost, progressed to Layer 10, the outermost. Amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) analyses were conducted to assess the functional characteristics of ipsilateral perilesional GM and contralateral homotopic GM.ResultsCompared to the contralateral homotopic GM, a significant reduction of ALFF was detected at ipsilateral perilesional GM layer 1 to 6 in FCD type IIa (after Bonferroni correction p < 0.005, paired t-test), whereas a significant decrease was observed at ipsilateral perilesional GM layer 1 to 2 in FCD type IIb (after Bonferroni correction p < 0.005, paired t-test). Additionally, a significant decrease of the ReHo was detected at ipsilateral perilesional GM layer 1 compared to the CHRs in FCD type IIb. Notably, complete resection of functional perilesional GM alterations did not correlate with surgical outcomes. Compared to the contralateral homotopic GM, a decreased ALFF in the ipsilateral perilesional GM layer was detected in drug-responsive patients, whereas decreased ALFF in the ipsilateral perilesional GM layer 1–6 and decreased ReHo at ipsilateral perilesional GM layer 1 were observed in drug-resistant patients (after Bonferroni correction p < 0.005, paired t-test).ConclusionOur findings indicate distinct functional profiles of perilesional GM based on FCD histological subtypes and ASMs’ response patterns. Importantly, our study illustrates that the identified functional alterations in perilesional GM may not provide sufficient evidence to determine the epileptogenic boundary required for surgical resection

Virus-Like Particles of SARS-Like Coronavirus Formed by Membrane Proteins from Different Origins Demonstrate Stimulating Activity in Human Dendritic Cells

The pathogenesis of SARS coronavirus (CoV) remains poorly understood. In the current study, two recombinant baculovirus were generated to express the spike (S) protein of SARS-like coronavirus (SL-CoV) isolated from bats (vAcBS) and the envelope (E) and membrane (M) proteins of SARS-CoV, respectively. Co-infection of insect cells with these two recombinant baculoviruses led to self-assembly of virus-like particles (BVLPs) as demonstrated by electron microscopy. Incorporation of S protein of vAcBS (BS) into VLPs was confirmed by western blot and immunogold labeling. Such BVLPs up-regulated the level of CD40, CD80, CD86, CD83, and enhanced the secretion of IL-6, IL-10 and TNF-α in immature dendritic cells (DCs). Immune responses were compared in immature DCs inoculated with BVLPs or with VLPs formed by S, E and M proteins of human SARS-CoV. BVLPs showed a stronger ability to stimulate DCs in terms of cytokine induction as evidenced by 2 to 6 fold higher production of IL-6 and TNF-α. Further study indicated that IFN-γ+ and IL-4+ populations in CD4+ T cells increased upon co-cultivation with DCs pre-exposed with BVLPs or SARS-CoV VLPs. The observed difference in DC-stimulating activity between BVLPs and SARS CoV VLPs was very likely due to the S protein. In agreement, SL-CoV S DNA vaccine evoked a more vigorous antibody response and a stronger T cell response than SARS-CoV S DNA in mice. Our data have demonstrated for the first time that SL-CoV VLPs formed by membrane proteins of different origins, one from SL-CoV isolated from bats (BS) and the other two from human SARS-CoV (E and M), activated immature DCs and enhanced the expression of co-stimulatory molecules and the secretion of cytokines. Finding in this study may provide important information for vaccine development as well as for understanding the pathogenesis of SARS-like CoV

A Distributed Agents QoS Routing Algorithm to Transmit Electrical Power Measuring Information in Last Mile Access Wireless Sensor Networks

Internet of Things or wireless sensor networks (WSNs) can be utilized in monitoring electrical power consumption. For electrical power application, the main issue is how to effectively apply self-organized WSNs technology to handle the last mile communication and supply the reliable, real-time transmission. For example, great number of renewable generators' instantaneous voltage and power parameters should be reported in real time to dispatching center, which is the primary guarantee to keep the power system's stability. In this paper, integrating traffic engineering and distributed agent technologies, a novel distributed agents QoS routing algorithm is proposed to transmit electrical information flows with multi-QoS constraints. The algorithm can explore fast forward path with multiagents and guarantee transmitting quality with smooth allocating different traffic. We also present the mathematical analysis to prove the algorithm's validity. Finally, in the computer simulation, the average end-to-end delay, routing overhead, and links' bandwidth occupation ratio are computed to evaluate the algorithm performance. Coincident results show that the new algorithm can provide short end-to-end transmission with optimal utilized communication resource. A health infrastructure with load balance can effectively avoid the potential congestion and has robust capability to bear abrupt strong traffic flows