In this paper, we present a biped walking trajectory generator based on the three-mass with angular momentum model using model predictive control. This approach aims to decrease the modeling error ...and decrease zero moment point (ZMP) horizon, so that high ZMP tracking accuracy and immediate generation are achieved. The contribution of this approach is the use of the three-mass with angular momentum model, the reduction of modeling error, and the enhancement of ZMP tracking performance and walking stability. This method allows online walking pattern modification, so that unexpected emergency can be dealt with by immediately changing trajectories. In addition, this proposed method is validated through numerical simulations, and the proof-of-concept experiments are conducted using an experimental robot developed in our laboratory.
In this paper, automated omnidirectional touch probe (ODTP) including adaptive tuning of the complex contour curve with optimal interpolation and motion planning based on a hybrid multiaxis robot ...(HMAR) with dual drive gantry-type machine (DDGM) are presented. It is called an "omnidirectional" because the 6-degrees of freedom ODTP in tool center point mode can always maintain normal direction towards the object contour curve. The new optimal solutions of the interpolation and motion planning are provided to tackle the small segments issues for a complex curvature object. We present an algorithm to maintain maximum acceleration, so that it generates smooth and efficient three-dimensional reverse object in a higher order complex contour trajectory composed of piecewise small segments. As a result, the constant moving speed is very important to certain applications, such as gluing, welding, and laser cutting, to preserve quality processing. The utilization of object symmetry, extension, and synthesis properties to simplify the process of performing reverse engineering is described. These methods reduce the time required for the touch probe to detect the points. The experimental implementation to demonstrate the success of this paper with video clip are presented.
The decision-making processes in an autonomous mechatronic system rely on data coming from multiple sensors. An optimal fusion of information from distributed multiple sensors requires robust fusion ...approaches. The science of multisensor fusion and integration (MFI) is formed to treat the information merging requirements. MFI aims to provide the system a more accurate perception enabling an optimal decision to be made. The wide application spectrum of MFI in mechatronic systems includes industrial automation, the development of intelligent robots, military applications, biomedical applications, and microelectromechanical systems (MEMS)/nanoelectromechanical systems (NEMS). This paper reviews the theories and approaches of MFI with its applications. Furthermore, sensor fusion methods at different levels, namely, estimation methods, classification methods and inference methods, are the most frequently used algorithms. Future perspectives of MFI deployment are included in the concluding remarks.
This paper proposes to develop a quasi-natural humanoid robot walking trajectory generator based on five-mass with angular momentum model using feedback-feedforward controller. This approach aims to ...minimize modeling error and improve the frequency characteristics from nonminimum phase properties so that walking performance and tracking accuracy are enhanced. This proposed model focuses on the angular momentum effects from arm and leg rotation to reduce modeling error to enhance walking performance. Based on pole-zero cancelation using series approximation method, it can overcome the sudden change of the natural zero-moment point reference due to the frequency characteristics in the nonminimum phase control system. The humanoid walking pattern generator is verified and demonstrated using a humanoid robot developed in our laboratory based on the proposed model.
The introduction of service robots in the public domain has introduced a paradigm shift in how robots are interacting with people, where robots must learn to autonomously interact with the untrained ...public instead of being directed by trained personnel. As an example, a hospital service robot is told to deliver medicine to Patient Two in Ward Three. Without awareness of what "Patient Two" or "Ward Three" is, a service robot must systematically explore the environment to perform this task, which requires a long time. The implementation of a Semantic Map allows for robots to perceive the environment similar to people by associating semantic information with spatial information found in geometric maps. Currently, many semantic mapping works provide insufficient or incorrect semantic-metric information to allow a service robot to function dynamically in human-centric environments. This paper proposes a semantic map with a hierarchical semantic organization structure based on a hybrid metric-topological map leveraging convolutional neural networks and spatial room segmentation methods. Our results are validated using multiple simulated and real environments on our lab's custom developed mobile service robot and demonstrate an application of semantic maps by providing only vocal commands. We show that this proposed method provides better capabilities in terms of semantic map labeling and retain multiple levels of semantic information.
The central issues for understanding iron (Fe)-based superconductors are the symmetry and structure of the superconducting gap. So far the experimental data and theoretical models have been highly ...controversial. Some experiments favor two or more constant or nearly constant gaps, others indicate strong anisotropy and yet others suggest gap zeros ('nodes'). A unique method for addressing this issue, and one of very few methods that are bulk and angle resolved, is measuring the electronic-specific heat in a rotating magnetic field. In this study, we present the first such measurement for an Fe-based high-Tc superconductor. We observed a fourfold oscillation of the specific heat as a function of the in-plane magnetic field direction. Our results are consistent with the expectations for an extended s-wave model, with a significant gap anisotropy on the electron pockets and the gap minima along the ΓM (Fe-Fe bond) direction.
The objective of this paper is to present the development of 3D digital manufacturing through synchronous 5-axes printing for greatly enhancing the strength of the printed parts. In traditional fused ...deposition manufacturing (FDM), which is one of the digital manufacturing technologies, the melted material is required to be extruded from the nozzle on the workspace platform with a fixed direction. The strength is restricted in the direction of perpendicular to the layers since the printing way is layer by layer. The poor adhesion between the layers becomes a weakness to resist external force, especially when the force exerted from different directions. In this paper, algorithms for synchronous five axes printing based on the surface printing trajectory has been proposed to overcome the lack of strength issue. A five axes synchronous 3D printing machine developed in our NTU Intelligent Robotics and Automation Lab enhances the strength of the printed parts by adding additional materials to the surface of the parts. Five axes printing can achieve the goal of printing in different orientations so that the strength of the printed parts is greatly enhanced in comparison with the printing in a fixed direction only. The five axes synchronous 3D printing has been successfully demonstrated in physical printing. The strength analysis of printed parts is also performed under the three-point bending test and the tensile test. It shows that the strength of the five axes printed sample is increased by nearly three times in the bending test and nearly two times stronger in the tensile test.
To screen compounds that can selectively inhibit uveal melanoma cells with splicing factor 3B subunit 1 (SF3B1) mutations in comparison with isogenic SF3B1 wild-type counterparts in a cell model of ...SF3B1 mutant allele knockout.
Principal component analysis was used to analyze transcriptome alternative splicing in TCGA cohorts of uveal melanoma with wild-type SF3B1 and SF3B1 mutations, and abnormal alternative splicing events derived from SF3B1 mutations were identified. The SF3B1 mutant allele in Mel202 cells was knocked out using CRISPR-Cas9 technology, and Sanger sequencing was used to verify the edited sequence. MTT and colony formation assays were used to assess the proliferation of Mel202 and Mut-KO cells. RT-PCR agarose electrophoresis combined with Sanger sequencing was used to determine alternative splicing events in Mel202 and Mut-KO cells. MTT assay was performed to screen the compounds that showed selective inhibitory effect against Mel202 cells with SF3B1 mutation.
Specific knockout of SF3B1 mutan
This paper presents the algorithm of human pose estimation in 3-D space using adaptive control law with point-cloud-based limb regression approach. The proposed approach is a data-driven method for ...3-D pose estimation of human. In addition, we exploit the inverse relationship between the estimated parameter and the pose of limb, proposing a hybrid scheme, the combination of indirect adaptive scheme in Cartesian coordinate, and indirect adaptive scheme in spherical space. The experimental results show the ability of error tolerance, even dealing with sparse, partial, and noisy limb data. The comparison of the ground truth is provided with the standard dataset. The computation speed is sufficient, as it is expected to be used in real-time applications or as the 3-D feature in other recognition frameworks. Finally, the proposed algorithm is demonstrated with the point cloud sensing in real scene and the experimental results are included in this paper.
The global positioning system (GPS) has become an essential tool for the high precision navigation and positioning. The quality of GPS positioning results mainly depends on the model’s formulations ...regarding GPS observations, including both a functional model, which describes the mathematical relationships between the GPS measurements and unknown parameters, and a stochastic model, which reflects the physical properties of the measurements. Over the past two decades, the functional models for GPS measurements have been investigated in considerable detail. However, the stochastic models of GPS observation data are simplified, assuming that all the GPS measurements have the same variance and are statistically independent. Such assumptions are unrealistic. Although a few studies of GPS stochastic models were performed, they are restricted to short baselines and short time session lengths. In this paper, the stochastic modeling for GPS long-baseline and zenith tropospheric delay (ZTD) estimates with a 24-h session is investigated using the residual-based and standard stochastic models. Results show that using the different stochastic modelling methods, the total differences can reach as much as 3–6
mm in the baseline component, especially in the height component, and 10
mm in the ZTD estimation. Any misspecification in the stochastic models will result in unreliable GPS baseline and ZTD estimations. Using the residual-based stochastic model, not only the precision of GPS baseline and ZTD estimation is obviously improved, but also the baseline and ZTD estimations are closer to the reference value.
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