There is a growing demand for the use of machine learning (ML) to derive fast-to-evaluate surrogate models of materials properties. In recent years, a broad array of materials property databases have ...emerged as part of a digital transformation of materials science. However, recent technological advances in ML are not fully exploited because of the insufficient volume and diversity of materials data. An ML framework called “transfer learning” has considerable potential to overcome the problem of limited amounts of materials data. Transfer learning relies on the concept that various property types, such as physical, chemical, electronic, thermodynamic, and mechanical properties, are physically interrelated. For a given target property to be predicted from a limited supply of training data, models of related proxy properties are pretrained using sufficient data; these models capture common features relevant to the target task. Repurposing of such machine-acquired features on the target task yields outstanding prediction performance even with exceedingly small data sets, as if highly experienced human experts can make rational inferences even for considerably less experienced tasks. In this study, to facilitate widespread use of transfer learning, we develop a pretrained model library called XenonPy.MDL. In this first release, the library comprises more than 140 000 pretrained models for various properties of small molecules, polymers, and inorganic crystalline materials. Along with these pretrained models, we describe some outstanding successes of transfer learning in different scenarios such as building models with only dozens of materials data, increasing the ability of extrapolative prediction through a strategic model transfer, and so on. Remarkably, transfer learning has autonomously identified rather nontrivial transferability across different properties transcending the different disciplines of materials science; for example, our analysis has revealed underlying bridges between small molecules and polymers and between organic and inorganic chemistry.
iQSPR is an inverse molecular design algorithm based on Bayesian inference that was developed in our previous study. Here, the algorithm is integrated in Python as a new module called iQSPR‐X in the ...all‐in‐one materials informatics platform XenonPy. Our new software provides a flexible, easy‐to‐use, and extensible platform for users to build customized molecular design algorithms using pre‐set modules and a pre‐trained model library in XenonPy. In this paper, we describe key features of iQSPR‐X and provide guidance on its use, illustrated by an application to a polymer design that targets a specific range of bandgap and dielectric constant.
This paper describes a gesture interface for a factory transfer robot. Our proposed interface used gesture recognition to recognize the pointing direction, instead of estimating the point as in ...conventional pointing gesture estimation. When the autonomous mobile robot (AMR) recognized the pointing direction, it performed position control based on the object recognition. The AMR traveled along our unique path to ensure that its camera detected the object to be referenced for position control. The experimental results confirmed that the position and angular errors of the AMR controlled with our interface were 0.058 m and 4.7° averaged over five subjects and two conditions, which were sufficiently accurate for transportation. A questionnaire showed that our interface was user-friendly compared with manual operation with a commercially available controller.
Safety–critical system is important in a human–robot collaborative environment. Control Barrier Functions (CBFs)-based methods have emerged as a practical tool for the safety–critical control of ...autonomous systems. The design of CBFs is difficult to tune. Also, once additional constraints are introduced, the quadratic programming may encounter infeasibility. This paper proposes a safety–critical controller based on a control barrier function using a quasi-saturation function. To avoid infeasibility, we propose to separate the tracking controller from the safety controller. To facilitate the design of the control barrier function, we also propose the control barrier function using the quasi-saturation function. Numerical simulations are presented to show the effectiveness of the proposed method.
In this paper, we describe a semi-automatic viewpoint moving system that employs a drone to provide visual assistance to the operator of a teleoperated robot. The objective of this system is to ...improve the operational efficiency and reduce the mental load of the operator. The operator changes the position of the drone through an interface to acquire the optimal assist image for teleoperation. We confirmed through an evaluation experiment that, in comparison with our previous study in which the final positions of the drone were determined in advance, the proposed method improves the operational accuracy and reduces the mental load of the operator.
The purpose of this research is to develop a VR simulator that can safely train wheelie, which is a stepping technique for manual wheelchair users. The equation of motion of the wheelchair was shown, ...and the actual wheelchair motion was compared with the simulation results. A wheelchair simulator that moves using this equation of motion was constructed. The effectiveness of the simulator in wheelie training was evaluated by experiments. In the experiment, 20 subjects were divided into two groups of 10 subjects, and one group trained using a wheelchair simulator and did not practice the other group. After that, Subjects tried wheelie in a real wheelchair and we calculated the success rates. As a result, the average success rate of the group using the wheelchair simulator increased by about 48 points compared to the unused group. From the results, it was shown that the simulator developed in this study is effective for learning the wheelie motion.
A teleoperation system for a construction robot works effectively in a hazardous environment. However, it has problems with work precision and mental workload. In this study, a moving visual support ...system using a drone is developed to solve these operability problems. The usability of the system is confirmed through a subjective experiment.
This research develops a gravity compensation method that determines the mass of a task object easily and compensates for the external force caused by the task object when it is conveyed by a ...hydraulic teleoperation construction robot. Moreover, this study establishes a master–slave system for this robot; two joysticks act as the master, and an excavator with four links (fork glove, swing, boom, and arm) represents the slave. To compensate for the influence of gravity, a previous gravity compensation method is proposed and applied to the boom and arm. However, it is ineffective during the conveyance process especially when the task object is heavy because the driving force is influenced by gravity of the task object. Therefore, this research presents a gravity compensation method that can effectively determine the mass of a grasped object and compensate for the external force induced by its gravity, as verified through pressing, grasping, and conveying experiments.
Peptides with cell attachment activity are beneficial component of biomaterials for tissue engineering. Conformational structure is one of the important factors for the biological activities. The EF1 ...peptide (DYATLQLQEGRLHFMFDLG) derived from laminin promotes cell spreading and cell attachment activity mediated by α2β1 integrin. Although the sequence of the EF2 peptide (DFATVQLRNGFPYFSYDLG) is homologous sequence to that of EF1, EF2 does not promote cell attachment activity. To determine whether there are structural differences between EF1 and EF2, we performed replica exchange molecular dynamics (REMD) simulations and conventional molecular dynamics (MD) simulations. We found that EF1 and EF2 had β-sheet structure as a secondary structure around the global minimum. However, EF2 had variety of structures around the global minimum compared with EF1 and has easily escaped from the bottom of free energy. The structural fluctuation of the EF1 is smaller than that of the EF2. The structural variation of EF2 is related to these differences in the structural fluctuation and the number of the hydrogen bonds (H-bonds). From the analysis of H-bonds in the β-sheet, the number of H-bonds in EF1 is larger than that in EF2 in the time scale of the conventional MD simulation, suggesting that the formation of H-bonds is related to the differences in the structural fluctuation between EF1 and EF2. From the analysis of other non-covalent interactions in the amino acid sequences of EF1 and EF2, EF1 has three pairs of residues with hydrophobic interaction, and EF2 has two pairs. These results indicate that several non-covalent interactions are important for structural stabilization. Consequently, the structure of EF1 is stabilized by H-bonds and pairs of hydrophobic amino acids in the terminals. Hence, we propose that non-covalent interactions around N-terminal and C-terminal of the peptides are crucial for maintaining the β-sheet structure of the peptides.
•A human–robot interaction interface with force guidance is presented.•The 3D shape for task object is achieved using Power Crust algorithm.•The ground surface is calculated as an elevation map based ...on binocular vision.•The virtual attractive and repulsive forces are built based on the potential field.•The kinesthesis is transmitted to the operator by force feedback joysticks.
In order to improve operator performance and understanding within remote environment, a vision-based virtual forced guidance control methodology for tele-robotic system is presented. The remote operation of the construction robot is achieved by manipulating the graphic robot in a virtual environment. Based on binocular vision, the ground surface is modeled as an elevation map, and the task objects are recognized from video images and reconstructed using the Power Crust algorithm. The virtual guidance forces consisting of a pair of attractive force and repulsive force from the objects and obstacles are used to enhance the multi-task manipulation of the tele-robotic system.
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