Defects arising from the 3D printing process of continuous fiber-reinforced thermoplastic composites primarily hinder their overall performance. These defects particularly include twisting, folding, and breakage of the fiber bundle, which are induced...
To improve the prediction reliability of model predictive control under model mismatch and environmental disturbances, this paper proposes a prediction-error-compensated MPC method with a forgetting factor for ship trajectory tracking and collision a...
For underwater gliders (UGs), high trajectory accuracy is an important factor in improving the observation of ocean phenomena. In this paper, a novel method of trajectory optimization is proposed to increase the trajectory accuracy of UGs, which is a...
To address the challenge of low computational efficiency in nonlinear Economic Model Predictive Control (EMPC) for large-scale systems such as wastewater treatment plants (WWTPs), this paper proposes a Trajectory Piecewise Linearization (TPWL)-based...
Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applicati...
Autonomous localization without local wireless facilities is proven as an efficient way for realizing location-based services in complex urban environments. The precision of the current map-matching algorithms is subject to the poor ability of integr...
In order to solve the problems of complex dynamic modeling and parameters identification of quadrotor formation cooperative trajectory tracking control, this paper proposes a data-driven model-free adaptive control method for quadrotor formation base...
In this paper, we introduce a control method for the linear quadratic tracking (LQT) problem with zero steady-state error. This is achieved by augmenting the original system with an additional state representing the integrated error between the refer...
The six-degree-of-freedom parallel robots is crucial for intelligent manufacturing, motion simulation, aerospace and other fields. Their trajectory performance level directly affects the reliable application of high-precision operation scenarios. How...
Intelligent manufacturing is the main direction of Industry 4.0, pointing towards the future development of manufacturing. The core component of intelligent manufacturing is the computer numerical control (CNC) system. Predicting and compensating for...
The CNC machine tool is the passive executor of machining code. It cannot predict the machining accuracy during machining. If the error is found to be out of tolerance after processing, it will not only scrap the parts, but also greatly affect the pr...
Mobile laser scanning (MLS) point cloud registration plays a critical role in mobile 3D mapping and inspection, but conventional point cloud registration methods for terrain LiDAR scanning (TLS) are not suitable for MLS. To cope with this challenge,...
Dynamic errors in robotic machining can degrade part quality, particularly in flexible platforms that are susceptible to both geometric and inertial disturbances. This work introduces a data-driven digital twin for pointwise prediction of circular tr...
The field of autonomous driving vehicles is growing and expanding rapidly. However, the control systems for autonomous driving vehicles still pose challenges, since vehicle speed and steering angle are always subject to strict constraints in vehicle...
Six degree-of-freedom (6-DOF) robotic manipulators have been increasingly adopted in various applications in industries due to various advantages, such as large operation space, more degrees of freedom, low cost, easy placement, and convenient progra...
The accuracy of the end-effector motion trajectory is a critical performance indicator for cable-driven parallel mechanisms. This study aims to address the problem of trajectory error during the end-effector motion in a cable-driven parallel mechanis...
Sensor alignment plays a key role in the accurate estimation of the ballistic trajectory. A sparse regularization-based sensor alignment method coupled with the selection of a regularization parameter is proposed in this paper. The sparse regularizat...
Multi-sensor data fusion is essential for accurate target tracking and trajectory reconstruction. However, common forms of systematic error in multi-sensor observations, including constant biases, linear drifts, and saturating exponential drifts, can...
Pedestrian trajectory prediction is crucial for developing collision avoidance algorithms in autonomous driving systems, aiming to predict the future movement of the detected pedestrians based on their past trajectories. The traditional methods for p...
Map matching of trajectory data has wide applications in path planning, traffic flow analysis, and intelligent driving. The process of map matching involves matching GPS trajectory points to roads in a roadway network, thereby converting a trajectory...
To address the difficulty of directly applying finite element simulation trajectories to actual spinning machines, as well as the discrepancy between simulation data and equipment execution in the spinning process, this paper proposes a trajectory ma...
Fiber-optic gyroscopes (FOGs)-based Measurement While Drilling system (MWD) is a newly developed instrument to survey the borehole trajectory continuously and in real time. However, because of the strong vibration while drilling, the measurement accu...
It is a challenging task to track objects moving along an unknown trajectory. Conventional model-based controllers require detailed knowledge of a robot’s kinematics and the target’s trajectory. Tracking precision heavily relies on kinema...
This paper investigates the accuracy of simulated long-duration super-pressure balloon trajectories in the lower stratosphere. The observed trajectories were made during the (tropical) Pre-Concordiasi and (polar) Concordiasi campaigns in 2010, while...
To autonomously dock LNG unloading arms under adverse sea states, this study formulates a dynamic docking process as a trajectory forecasting task. By integrating visual-perception-based spatial localization with trajectory acquisition and forecastin...
Driven by advancements in artificial intelligence technology, pedestrian trajectory prediction is shifting from traditional machine learning methods toward autonomous decision-making frameworks based on neural networks. However, the spatiotemporal un...
In addressing the challenges of trajectory prediction in multi-ship interaction scenarios and aiming to improve the accuracy of multi-ship trajectory prediction, this paper proposes a multi-ship trajectory prediction model, GL-STGCNN. The GL-STGCNN m...
This paper focuses on the trajectory planning and trajectory tracking control of articulated tracked vehicles (ATVs). It utilizes the path planning method based on the Hybrid A-star and the minimum snap smoothing method to obtain the feasible kinemat...
Trajectory prediction technology uses the trajectory data of historical ships to predict future ship trajectory, which has significant application value in the field of ship driving and ship management. With the popularization of Automatic Identifica...
Automatic Identification System (AIS) data-supported ship trajectory analysis consistently helps maritime regulations and practitioners make reasonable traffic controlling and management decisions. Significant attentions are paid to obtain an accurat...
This research presents a nonlinear adaptive fuzzy control method as an analytical design and a simple control structure for the trajectory tracking problem in wheeled mobile robots with skew symmetrical property. For this trajectory tracking problem...
The assessment of shoulder kinematics and kinetics are commonly undertaken biomechanically and clinically by using rigid-body models and experimental skin-marker trajectories. However, the accuracy of these trajectories is plagued by inherent skin-ba...
Simplifying trajectory data can improve the efficiency of trajectory data analysis and query and reduce the communication cost and computational overhead of trajectory data. In this paper, a real-time trajectory simplification algorithm (SSFI) based...
Measuring the similarity between a pair of trajectories is the basis of many spatiotemporal clustering methods and has wide applications in trajectory pattern mining. However, most measures of trajectory similarity in the literature are based on prec...
A novel variable structure controller based on sliding mode is developed for addressing the trajectory tracking challenge encountered by wheeled mobile robots. Firstly, the trajectory tracking error model under the global coordinate system is establi...
In this paper, a Gaussian process-based model predictive control (GP-MPC) method is proposed, which aims to enhance the trajectory tracking performance of autonomous underwater vehicles (AUVs). This method can compensate for internal errors and exter...
This study introduces a novel framework for defining screw trajectory that utilizes PointNet—a deep neural network trained on lumbar vertebrae point clouds—to improve the manual surgical planning procedures. The conventional architecture...
Ship trajectory prediction is a complex time series forecasting problem that necessitates models capable of accurately capturing both long-term trends and short-term fluctuations in vessel movements. While existing deep learning models excel in short...
The trajectory-tracking capability of autonomous mining trucks is critical for accomplishing transportation tasks efficiently. However, due to the diverse road surfaces and rugged terrains in open-pit mines, the existing vehicle dynamics models strug...
Accurate vessel trajectory prediction from Automatic Identification System (AIS) records is important for maritime traffic monitoring, route planning, and intelligent vessel traffic management. However, reliable prediction remains challenging for lon...
For the problem of large joint angular velocity and high input in the trajectory planning and control of robots, an explicit-time trajectory tracking for a state-constraint continuum free-floating space robot with smooth joint-path and low input is p...
Drilling trajectory control technology for near-horizontal directional drilling in coal mines is mainly determined empirically by manual skew data, and the empirical results are only qualitative and variable, meanwhile possessing great instability an...
This article examines the challenge of trajectory inference for an unknown system affected by external disturbances, with the objective of reconstructing the trajectory of a quadrotor using a reference model. The proposed methodology extends the Clos...
To improve the accuracy and real-time performance of trajectory tracking control for a four-wheel differential drive intelligent sweeping vehicle, a trajectory tracking control method based on an adaptive strong tracking extended Kalman filter (ASTEK...
To address the problem of low accuracy and efficiency in trajectory planning algorithms for interceptors facing multiple constraints during the midcourse guidance phase, an improved trajectory convex programming method based on the lateral distance d...
To improve the form accuracy of spherical surfaces generated by cup-wheel grinding, this paper presents a geometric modeling and error compensation method for concentric grinding of spherical surfaces. A cup-shaped arc grinding wheel, hereafter refer...
Trajectory prediction is an essential task in many applications, including autonomous driving, robotics, and surveillance systems. In this paper, we propose a novel trajectory prediction network, called TFBNet (trajectory feature-boosting network), t...
Predicting the future trajectories of multiple agents is essential for various applications in real life, such as surveillance systems, autonomous driving, and social robots. The trajectory prediction task is influenced by many factors, including ind...
Due to the growing interest using model predictive control (MPC), there are more and more researches about the applications of MPC on autonomous underwater vehicle (AUV), and these researches are mainly focused on simulation and simple application of...
To address the problem of model error and tracking dependence in the process of intelligent vehicle motion planning, an intelligent vehicle model transfer trajectory planning method based on deep reinforcement learning is proposed, which is able to o...
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