Search Results (2,884)

The coupling of topology transition with flexible deformation and rigid motion presents significant challenges in the dynamic modeling of flexible variable topology mechanisms. Existing dynamics models are mostly special-purpose models for their particular cases and thus struggle to completely depict the general topology transition characteristics. To address this gap, this paper proposes an analytical framework for the global dynamic modeling of flexible variable topology mechanisms, focusing on general cases. Initially, the flexible variable topology mechanisms are rigorously defined by the ordered triples and the general topology transition approaches are presented. A novel concept, the “basic flexible kinematic chain set”, is suggested, which can easily transform into the topology of each submechanism by slightly extending. Based on this concept, basic and conditional constraints are established. The continuous dynamic modeling method for each topology is developed using Jourdain’s principle and the Lagrange multiplier method. Additionally, three classes of constraints related to topology transition are identified, and their equations are formulated, elucidating the topology transition nature. Compatibility equations are proposed to define the new coordinate system for describing the deformation of flexible components after the topology transition. An impact dynamic equation is established to describe abrupt velocity change. Integrating compatibility and impact equations, a discontinuous dynamic modeling method for topology transition is developed. Finally, a flexible variable topology mechanism example is studied, and simulations and experiments are conducted to validate the proposed framework. This analytical framework is general-purpose and efficient, guiding the global dynamic modeling of various flexible variable topology mechanisms and the development of sophisticated control techniques. Full article

A virtual flight test is the process of flying an aircraft model inside a wind tunnel in a manner that replicates free-flight. In this paper, a 3-DOF aircraft-manipulator system is proposed that can be used for longitudinal dynamics virtual flight tests. The system consists of a two rotational degrees-of-freedom manipulator arm with an aircraft wind tunnel model attached to the third joint. This aircraft-manipulator system is constrained to operate for only the longitudinal motion of the aircraft. Thus, the manipulator controls the surge and heave of the aircraft whilst the pitch is free to rotate and can be actively controlled by means of an all-moving tailplane of the aircraft if required. In this initial study, a flight dynamics model of the aircraft is used to obtain dynamic response trajectories of the aircraft in free-flight. A model of the coupled aircraft-manipulator system developed using the Euler method is presented, and PID controllers are used to control the manipulator so that the aircraft follows the free-flight trajectory (with respect to the air). The inverse kinematics are used to produce the reference joint angles for the manipulator. The system is simulated in MATLAB/Simulink and a virtual flight test trajectory is compared with a free-flight test trajectory, demonstrating the potential of the proposed system for virtual flight tests. Full article

In this paper, the problem of preview optimal control for second-order nonlinear systems for marine vessels is discussed on a fully actuated dynamic model. First, starting from a kinematic and dynamic model of a three-degrees-of-freedom (DOF) marine vessel, we derive a fully actuated second-order dynamic model that involves only the ship’s position and yaw angle. Subsequently, through the higher-order systems methodology, the nonlinear terms in the system were eliminated, transforming the system into a one-order parameterized linear system. Next, we designed an internal model compensator for the reference signal and constructed a new augmented error system based on this compensator. Then, using optimal control theory, we designed the optimal preview controller for the parameterized linear system and the corresponding feedback parameter matrices, which led to the preview controller for the original second-order nonlinear system. Finally, a numerical simulation indicates that the controller designed in this paper is highly effective. Full article

Straw incorporation offers significant advantages in agricultural crop cultivation systems. Mechanized methods constitute the predominant approach, potentially reducing yield costs and enhancing operational efficiency. The imperative to enhance the quality of straw chopping within the field is of particular significance, as suboptimal chopping quality can engender a cascade of issues, particularly seeding blockages. The straw chopping pass rate (CPR) is a pivotal metric for assessing the quality of straw chopping. Therefore, enhancing the CPR during the straw chopping process is necessary. This study introduces a novel maize-straw-chopping device with the ground as its supporting base. This device facilitates the rapid vertical chopping of maize straw through a constant breath cam transmission mechanism. Critical parameters were determined to optimize the performance of the chopping device by establishing mathematical models and kinematic simulation analysis methods. With the help of Rocky 2022.R2 software, the influence of the rotational velocity of the draft, tractor velocity, and blade edge angles on the CPR during the operation of the device was analyzed. The Box–Behnken test methodology was used to carry out a three-factor, three-level orthogonal rotation test to obtain the optimal working parameter combination. The results indicated that the maximum CPR value was achieved with a draft rotational velocity of 245 rpm, a tractor velocity of 3.8 km/h, and a blade edge angle of 20.75°. Finally, field validation experiments were conducted under these optimized conditions, with the average CPR of maize straw reaching an impressive 91.45%. These findings have significant implications for enhancing crop production practices. Full article

High-strength steels such as Dual Phase (DP), Transformation-Induced Plasticity (TRIP), and Twinning-Induced Plasticity (TWIP) steels have gained importance in automotive applications due to the potential for weight reduction and increased performance in crash tests. However, as resistance increases, there is also an increase in springback due to residual stresses after the forming process. This is mainly because of the greater elastic region of these materials and other factors associated with strain hardening, such as the Bauschinger effect, that brings theory of kinematic hardening to mathematical modeling. This means that finite element software must consider these properties so that the simulation can accurately predict the behavior. Currently, this knowledge is still not widespread since it has never been used in conventional materials. Additionally, engineers and researchers use the Forming Limit Diagram (FLD) curve in their studies. However, it does not fully represent the actual failure limit of materials, especially in high-strength materials. Based on this, the Fracture Forming Limit Diagram (FFLD) curve has emerged, which proposes to resolve these limitations. Thus, this review aims to focus on how finite element methods consider all these factors in their modeling, especially when it comes to the responses of high-strength steels. Full article

The path planning of flexible needles in robotic puncturing presents challenges such as limited model accuracy and poor real-time performance, which affect both efficiency and accuracy in complex medical scenarios. To address these issues, this paper proposes a deep reinforcement learning-based path planning method for flexible needles in robotic puncturing. Firstly, we introduce a unicycle model to describe needle motion and design a hierarchical model to simulate layered tissue interactions with the needle. The forces exerted by tissues at different positions on the flexible needle are considered, achieving a combination of kinematic and mechanical models. Secondly, a deep reinforcement learning framework is built, integrating obstacle avoidance and target attraction to optimize path planning. The design of state features, the action space, and the reward function is tailored to enhance the model’s decision-making capabilities. Moreover, we incorporate a retraction mechanism to bolster the system’s adaptability and robustness in the dynamic context of surgical procedures. Finally, laparotomy simulation results validate the proposed method’s effectiveness and generalizability, demonstrating its superiority over current state-of-the-art techniques in robotic puncturing. Full article

This paper deals with the neural network identification-based model predictive heading control problem in a wave glider. First, based on a kinematic model of the wave glider subjected to external disturbance and system uncertainty, a state space model of the wave glider is established. Then, a neural network identification-based model predictive heading controller (NNI-MPHC) is designed for the wave glider. The heading controller mainly includes three components: a model predictive controller, a neural network-based model identifier, and a linear reduced-order extended state observer. Third, a design algorithm of the NNI-MPHC is presented. The algorithm is demonstrated through simulation, where the results show the following: (i) The designed NNI-MPHC is remarkably capable of guaranteeing the tracing effects of the wave glider. (ii) Comparing the NNI-MPHC and existing heading controllers, the former is better than the latter in terms of tracking accuracy and rapidity and robustness to model uncertainty and/or external disturbances. Full article

Currently, flexible robots, exemplified by parallel robots, play a crucial role in the automated packaging of agricultural products due to their rapid, accurate, and stable characteristics. This research systematically explores trajectory planning strategies for parallel robots in the high-speed tomato-grabbing process. Kinematic analysis of the parallel robot was conducted using geometric methods, deriving the coordinates of each joint at various postures, resulting in a kinematic forward solution model and corresponding equations, which were verified with data. To address the drawbacks of the point-to-point “portal” trajectory in tomato grabbing, a 3-5-5-3 polynomial interpolation method in joint space was proposed to optimize the path, enhancing trajectory smoothness. To improve the efficiency of the tomato packaging process, a hybrid algorithm combining particle swarm optimization (PSO) and genetic algorithms (GA) was developed to optimize the operation time of the parallel robot. Compared to traditional PSO, the proposed algorithm exhibits better global convergence and is less likely to fall into local optima, thereby ensuring a smoother and more efficient path in the robot-grabbing tomato process and providing technical support for automated tomato packaging. Full article

The body structures and motion stability of worm-like and snake-like robots have garnered significant research interest. Recently, innovative serial–parallel hybrid segmented robots have emerged as a fundamental platform for a wide range of motion modes. To address the hyper-redundancy characteristics of these hybrid structures, we propose a novel caterpillar-inspired Stable Segment Update (SSU) gait generation approach, establishing a unified framework for multi-segment robot gait generation. Drawing inspiration from the locomotion of natural caterpillars, the segments are modeled as rigid bodies with six degrees of freedom (DOF). The SSU gait generation method is specifically designed to parameterize caterpillar-like gaits. An inverse kinematics solution is derived by analyzing the forward kinematics and identifying the minimum lifting segment, framing the problem as a single-segment end-effector tracking task. Three distinct parameter sets are introduced within the SSU method to account for the stability of robot motion. These parameters, represented as discrete hump waves, are intended to improve motion efficiency during locomotion. Furthermore, the trajectories for each swinging segment are determined through kinematic analysis. Experimental results validate the effectiveness of the proposed SSU multi-gait generation method, demonstrating the successful traversal of gaps and rough terrain. Full article

Red-light running at signalised intersections poses a significant safety risk, necessitating advanced predictive technologies to predict red-light violation behaviour, especially for advanced red-light warning (ARLW) systems. This research leverages Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models to forecast the red-light running and stopping behaviours of drivers in connected vehicles. We utilised data from the Ipswich Connected Vehicle Pilot (ICVP) in Queensland, Australia, which gathered naturalistic driving data from 355 connected vehicles at 29 signalised intersections. These vehicles broadcast Cooperative Awareness Messages (CAM) within the Cooperative Intelligent Transport Systems (C-ITS), providing kinematic inputs such as vehicle speed, speed limits, longitudinal and lateral accelerations, and yaw rate. These variables were monitored at 100-millisecond intervals for durations from 1 to 4 s before reaching various distances from the stop line. Our results indicate that the LSTM model outperforms the GRU in predicting both red-light running and stopping behaviours with high accuracy. However, the pre-trained GRU model performs better in predicting red-light running specifically, making it valuable in applications requiring early violation prediction. Implementing these models can enhance red-light violation countermeasures, such as dynamic all-red extension (DARE), decreasing the likelihood of severe collisions and enhancing road users’ safety. Full article

Plant height is a critical biophysical trait indicative of plant growth and developmental conditions and is valuable for biomass estimation and crop yield prediction. This study examined the effects of flight altitude and camera angle in quantifying cotton plant height using unmanned aerial system (UAS) imagery. This study was conducted in a field with a sub-surface irrigation system in Lubbock, Texas, between 2022 and 2023. Images using the DJI Phantom 4 RTKs were collected at two altitudes (40 m and 80 m) and three sensor angles (45°, 60°, and 90°) at different growth stages. The resulting images depicted six scenarios of UAS altitudes and camera angles. The derived plant height was subsequently calculated as the vertical difference between the apical region of the plant and the ground elevation. Linear regression compared UAS-derived heights to manual measurements from 96 plots. Lower altitudes (40 m) outperformed higher altitudes (80 m) across all dates. For the early season (4 July 2023), the 40 m altitude had r² = 0.82–0.86 and RMSE = 2.02–2.16 cm compared to 80 m (r² = 0.66–0.68, RMSE = 7.52–8.76 cm). Oblique angles (45°) yielded higher accuracy than nadir (90°) images, especially in the late season (24 October 2022) results (r² = 0.96, RMSE = 2.95 cm vs. r² = 0.92, RMSE = 3.54 cm). These findings guide optimal UAS parameters for plant height measurement. Full article

In this paper, the seismic vulnerability of churches is assessed using different methods characterized by different levels of complexity depending on the accuracy of the results to be achieved. Specifically, we compare the two main types of methodologies applied in the literature, namely, empirical and analytical methods. Empirical methods assess seismic vulnerability based on engineering judgements. In this study, these evaluations were carried out through an automatic tool, the MACHRO form, which was introduced in the past by the authors with the purpose of making evaluations as objective as possible. Analytical methods evaluate the vulnerability of a stock of churches through linear and nonlinear kinematic analyses performed for the most vulnerable macro-elements, which are treated by means of mechanical models. When the number of churches in the stock is huge, this type of evaluation might prove unfeasible. For this reason, churches are grouped into a manageable number of archetypes in order to be analyzed. The above-described methodologies were applied to a relevant number of churches, aiming to appraise discrepancies in terms of results and highlight advantages and drawbacks of their application. Full article

This technical note aims to present a method for developing a Digital Terrain Model (DTM) of the coastal zone based on topobathymetric data from remote sensors. This research was conducted in the waterbody adjacent to the Vistula Śmiała River mouth in Gdańsk, which is characterised by dynamic changes in its seabed topography. Bathymetric and topographic measurements were conducted using an Unmanned Aerial Vehicle (UAV) and two hydrographic methods (a Single-Beam Echo Sounder (SBES) and a manual survey using a Global Navigation Satellite System (GNSS) Real-Time Kinematic (RTK) receiver). The result of this research was the development of a topobathymetric chart based on data recorded by the above-mentioned sensors. It should be emphasised that bathymetric data for the shallow waterbody (less than 1 m deep) were obtained based on high-resolution photos taken by a UAV. They were processed using the “Depth Prediction” plug-in based on the Support Vector Regression (SVR) algorithm, which was implemented in the QGIS software as part of the INNOBAT project. This plug-in allowed us to generate a dense cloud of depth points for a shallow waterbody. Research has shown that the developed DTM of the coastal zone based on topobathymetric data from remote sensors is characterised by high accuracy of 0.248 m (p = 0.95) and high coverage of the seabed with measurements. Based on the research conducted, it should be concluded that the proposed method for developing a DTM of the coastal zone based on topobathymetric data from remote sensors allows the accuracy requirements provided in the International Hydrographic Organization (IHO) Special Order (depth error ≤ 0.25 m (p = 0.95)) to be met in shallow waterbodies. Full article

Cooperative intelligent transportation systems continuously send self-referenced data about their current status in the Cooperative Awareness Message (CAM). Each CAM contains the current position of the vehicle based on GPS accuracy, which can have inaccuracies in the meter range. However, a high accuracy of the position data is crucial for many applications, such as electronic toll collection or the reconstruction of traffic accidents. Kalman filters are already frequently used today to increase the accuracy of position data. The problem with applying the Kalman filter to the position data within the Cooperative Awareness Message is the low temporal resolution (max. $10 \mathrm{H}\mathrm{z}$) and the non-equidistant time steps between the messages. In addition, the filter can only be applied to the data retrospectively. To solve these problems, an Extended Kalman Filter and an Unscented Kalman Filter were designed and investigated in this work. The Kalman filters were implemented with two kinematic models. Subsequently, driving tests were conducted with two V2X vehicles to investigate and compare the influence on the accuracy of the position data. To address the problem of non-equidistant time steps, an iterative adjustment of the Process Noise Covariance Matrix $\mathit{Q}$ and the introduction of additional interpolation points to equidistance the received messages were investigated. The results show that without one of these approaches, it is impossible to design a generally valid filter to improve the position accuracy of the CAM position data retrospectively. The introduction of interpolation points did not lead to a significant improvement in the results. With the $\mathit{Q}$ matrix adaptation, an Unscented Kalman Filter could be created that improves the longitudinal position accuracy of the two vehicles under investigation by up to 80% (0.54 m) and the lateral position accuracy by up to 72% (0.18 m). The work thus contributes to improving the positioning accuracy of CAM data for applications that receive only these data retrospectively. Full article

In this paper, we analyze stiffness and perform geometrical optimization of a parallel–serial manipulator with five degrees of freedom (5-DOF). The manipulator includes a 3-DOF redundantly actuated planar parallel mechanism, whose stiffness determines the stiffness of the whole mechanical system. First, we establish the kinematic and stiffness models of the mechanism and define its stiffness matrix. Two components of this matrix and the inverse of its condition number are chosen as stiffness indices. Next, we introduce an original two-step procedure for workspace analysis. In the first step, the chord method is used to find the workspace boundary. In the second step, the workspace is sampled inside the boundary by solving the point-in-polygon problem. After that, we derive stiffness maps and compute the average stiffness indices for various combinations of design variables. The number of these variables is reduced to two geometrical parameters, simplifying the representation and interpretation of the obtained results. Finally, we formulate the multi-objective design optimization problem, whose main goal is to maximize the lateral stiffness of the mechanism. We solve this problem using a hierarchical ($\epsilon$-constraint) method. As a result, the lateral stiffness with optimized geometrical parameters increases by 54.1% compared with the initial design. Full article