34 research outputs found

    Modiff: Action-Conditioned 3D Motion Generation with Denoising Diffusion Probabilistic Models

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    Diffusion-based generative models have recently emerged as powerful solutions for high-quality synthesis in multiple domains. Leveraging the bidirectional Markov chains, diffusion probabilistic models generate samples by inferring the reversed Markov chain based on the learned distribution mapping at the forward diffusion process. In this work, we propose Modiff, a conditional paradigm that benefits from the denoising diffusion probabilistic model (DDPM) to tackle the problem of realistic and diverse action-conditioned 3D skeleton-based motion generation. We are a pioneering attempt that uses DDPM to synthesize a variable number of motion sequences conditioned on a categorical action. We evaluate our approach on the large-scale NTU RGB+D dataset and show improvements over state-of-the-art motion generation methods

    Functional and structural analysis of a novel splice site HMBS variant in a Chinese AIP patient

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    Background: Acute intermittent porphyria (AIP) is a rare metabolic disorder that results from mutations in the gene encoding hydroxymethylbilane synthase (HMBS), an enzyme involved in heme biosynthesis. AIP follows an autosomal dominant inheritance pattern, but most carriers are asymptomatic. The clinical manifestations of AIP include acute attacks of abdominal pain and neuropsychiatric disturbances. The pathogenicity of novel HMBS variants identified in Chinese patients has not been well established.Objective: The article aims to identify the pathogenic mutation in an AIP patient and prove its pathogenicity through in vitro experiments.Methods: A 22-year-old female diagnosed with AIP participated in the study. Variant screening of her HMBS gene was carried out through Sanger sequencing. To ascertain the consequences of the newly discovered variant, we conducted in vitro experimentation targeting HMBS gene expression and enzymatic function. Additionally, protein structure analysis was performed. Cycloheximide treatment and UPF1-specific siRNA knockdown were employed to assess the impact of the mutation on the mechanism of non-sense-mediated mRNA decay (NMD).Results: A novel splice site variant in the HMBS gene (c.648_651+1delCCAGG) was detected in the patient, which caused aberrant mRNA splicing. In vitro experiments demonstrated that this variant significantly decreased the expression of HMBS. Further investigation confirmed that this decrease was due to NMD. Additionally, structural analysis indicated that this variant would destabilize the HMBS protein and impair its catalytic activity. To gain a comprehensive understanding of HMBS mutations in the context of AIP, we conducted a literature search on PubMed using the keywords ‘HMBS’ and ‘Acute intermittent porphyria’ from 2013 to 2023. This search yielded 19 clinical case reports written in English, which collectively described 220 HMBS gene mutations worldwide.Conclusion: The study identified and proved the pathogenicity of a novel splice site HMBS variant for the first time. Our results elucidated the pathological mechanism by which this mutation causes AIP through reducing HMBS expression and activity. These findings provide theoretical guidance for the diagnosis, treatment and genetic counseling of AIP patients

    Robust Terminal Sliding Mode Control on SE(3) for Gough–Stewart Flight Simulator Motion Platform with Payload Uncertainty

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    This work proposes a robust terminal sliding mode control scheme on Lie group space SE(3) for Gough–Stewart flight simulator motion systems with payload uncertainty. A complete dynamic model with geometric mechanical structures and a computer dynamic model built in the MATLAB/Simulink package are briefly presented. The robust control strategy on the Lie group SE(3) is applied at the workspace level to counteract the effects of imperfect compensation due to model simplification and payload uncertainty in flight simulator application. With exponential coordinates for configuration error and adjoint operator on Lie algebra se(3), the robust control strategy is designed to guarantee almost global finite-time convergence over state space through the Lyapunov stability theory. Finally, a describing function and a step acceleration response to characterize the performance of a flight simulator motion base are employed to compare the robustness performance of the proposed controller on SE(3) with the conventional terminal sliding mode controller on Cartesian space. The comparison experimental results verify that the proposed controller on SE(3) provides better robustness than the conventional controller on Cartesian space, which means higher bandwidth in two degrees of freedom and faster response with smaller tracking error in six degrees of freedom

    Real-time kinematical optimal trajectory planning for haptic feedback manipulators

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    To obtain real-time haptic interactions in virtual cockpit systems (VCSs), a real-time trajectory planning method based on kinematical optimization for haptic feedback manipulators (HFMs) is presented in this paper. Firstly, the control panel area is extracted in the workspace of the HFM, in which the interacting point is located. Then a feasible interacting configuration is calculated as the objective configuration of the trajectory encoded by a parametric representation. The trajectory planning problem is formulated as a non-linear optimization problem based on kinematics, which is solved in real-time by finding a good initial solution with machine learning methods. Simulations show that trajectories with a compromise between safety and rapidity can be calculated in real-time by this method, which provides a basis for haptic interaction in VCSs

    Robust Terminal Sliding Mode Control on SE(3) for Gough–Stewart Flight Simulator Motion Platform with Payload Uncertainty

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    This work proposes a robust terminal sliding mode control scheme on Lie group space SE(3) for Gough–Stewart flight simulator motion systems with payload uncertainty. A complete dynamic model with geometric mechanical structures and a computer dynamic model built in the MATLAB/Simulink package are briefly presented. The robust control strategy on the Lie group SE(3) is applied at the workspace level to counteract the effects of imperfect compensation due to model simplification and payload uncertainty in flight simulator application. With exponential coordinates for configuration error and adjoint operator on Lie algebra se(3), the robust control strategy is designed to guarantee almost global finite-time convergence over state space through the Lyapunov stability theory. Finally, a describing function and a step acceleration response to characterize the performance of a flight simulator motion base are employed to compare the robustness performance of the proposed controller on SE(3) with the conventional terminal sliding mode controller on Cartesian space. The comparison experimental results verify that the proposed controller on SE(3) provides better robustness than the conventional controller on Cartesian space, which means higher bandwidth in two degrees of freedom and faster response with smaller tracking error in six degrees of freedom

    Workspace analysis for haptic feedback manipulator in virtual cockpit system

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    To obtain natural space experience of haptic interaction for users in virtual cockpit systems (VCS), a haptic feedback system and a workspace analysis framework for haptic feedback manipulator (HFM) are presented in this paper. Firstly, improving the classical three-dimensional workspace obtained by the Monte Carlo method, a novel workspace representation method, oriented workspace, is presented, which can indicate both the position and the orientation of the end-effector. Then, aimed at the characters of HFMs, the oriented workspace is divided into the effective workspace and the prohibited area by extracting the control panel area. At last, the effective workspace volume and the control panel area are calculated by the double-directed extremum method, with the accuracy improved by repeatedly adding and extracting boundary points. By simulation, the area in which interactions between the manipulator and users hand performed is determined and accordingly the effective workspace along with its boundary and volume are obtained in a relative high precision, which lay a basis for haptic interaction in VCS

    A Lie Group-Based Iterative Algorithm Framework for Numerically Solving Forward Kinematics of Gough–Stewart Platform

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    In this work, we began to take forward kinematics of the Gough–Stewart (G-S) platform as an unconstrained optimization problem on the Lie group-structured manifold SE(3) instead of simply relaxing its intrinsic orthogonal constraint when algorithms are updated on six-dimensional local flat Euclidean space or adding extra unit norm constraint when orientation parts are parametrized by a unit quaternion. With this thought in mind, we construct two kinds of iterative problem-solving algorithms (Gauss–Newton (G-N) and Levenberg–Marquardt (L-M)) with mathematical tools from the Lie group and Lie algebra. Finally, a case study for a general G-S platform was carried out to compare these two kinds of algorithms on SE(3) with corresponding algorithms that updated on six-dimensional flat Euclidean space or seven-dimensional quaternion-based parametrization Euclidean space. Experiment results demonstrate that those algorithms on SE(3) behave better than others in convergence performance especially when the initial guess selection is near to branch solutions

    Learning to Have a Civil Aircraft Take Off under Crosswind Conditions by Reinforcement Learning with Multimodal Data and Preprocessing Data

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    Autopilot technology in the field of aviation has developed over many years. However, it is difficult for an autopilot system to autonomously operate a civil aircraft under bad weather conditions. In this paper, we present a reinforcement learning (RL) algorithm using multimodal data and preprocessing data to have a civil aircraft take off autonomously under crosswind conditions. The multimodal data include the common flight status and visual information. The preprocessing is a new design that maps some flight data by nonlinear functions based on the general flight dynamics before these data are fed into the RL model. Extensive experiments under different crosswind conditions with a professional flight simulator demonstrate that the proposed method can effectively control a civil aircraft to take off under various crosswind conditions and achieve better performance than trials without visual information or preprocessing data
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