Search Results (75)

A humanoid robot has a similar form to humans, allowing it to be deployed directly into many existing infrastructures built for people, making it highly applicable to future industries or services. However, generating motion is challenging, and it is highly affected by disturbances due to its complex dynamic characteristics. This paper proposes a method to enable a biped robot to achieve stable motion in various environments. The capture point (CP) control is used to modify the zero moment point (ZMP) to stabilize the naturally divergent dynamics of the simplified linear inverted pendulum model (LIPM) and a model predictive control (MPC) framework is implemented to generate a center of mass (COM) trajectory that tracks the adjusted ZMP. To minimize angular momentum caused by disturbances and discrepancies between the actual robot and the dynamics model, arm motion is generated through a momentum controller. Various walking simulations were conducted to verify stable whole-body motion. Full article

To investigate the mechanism of ground hydraulic fracturing technology in preventing mine earthquakes induced by hard–thick roof (HTR) breakage in coal mines, this study established a Timoshenko beam model on a Winkler foundation incorporating the elastoplasticity and strain-softening behavior of coal–rock masses. The following conclusions were drawn: (1) The periodic breaking step distance of a 15.8 m thick HTR on the 61,304 Workface of Tangjiahui coal mine was calculated as 23 m, with an impact load of 15,308 kN on the hydraulic support, differing from measured data by 4.5% and 4.8%, respectively. (2) During periodic breakage, both the bending moment and elastic deformation energy density of the HTR exhibit a unimodal distribution, peaking 1.0–6.5 m ahead of cantilever endpoint O, while their zero points are 40–41 m ahead, defining the breaking position and advanced influence area. (3) The PBSD has a cubic relationship with the peak values of bending moment and elastic deformation energy density, and the exponential relationship with the impact load on the hydraulic support is $F_{ZJ}=5185.2e^{0.00431L_p}$. (4) Theoretical and measured comparisons indicate that reducing PBSD is an effective way to control impact load. The hard–thick roof ground hydraulic fracturing technology (HTRGFT) weakens HTR strength, shortens PBSD, effectively controls impact load, and helps prevent mine earthquakes. Full article

Active patient participation in the rehabilitation process after stroke has been shown to accelerate neural remodeling. The control framework of rehabilitation robots should provide appropriate assistive forces to users. An assist-as-needed (AAN) control method is proposed to help users to move upper limbs in the workspace freely, and to control the exoskeleton to provide assistance. The method is based on zero moment control (ZMC), helping the user achieve robotic traction with minimal interaction force. Based on the posture of the upper arm and forearm, an AAN controller can modify assistive forces at two human–robot-interaction (HRI) points along the direction opposite to gravity. A shoulder motion prediction model is proposed to enable the exoskeleton to mimic the user’s upper limb natural movements. In order to improve the transparency during rehabilitation training, a nonlinear numerical friction model based on the Stribeck friction model is developed. A healthy adult male was recruited to perform various activities of daily living (ADL) tests to assess the effectiveness of the controllers. The experimental results show that the proposed ZMC controller has high HRI transparency and can control the exoskeleton to complete a wide range of upper limb movements, and the maximum interaction force and torque can be captured within −7.76 N and 4.58 Nm, respectively. The AAN controller can provide appropriate assistance in the desired direction, and the exoskeleton maintains kinematic synchronization with the user’s shoulder during shoulder girdle movement. Full article

The standardized hydrological index (SHI) is the standardized but not normalized (normal probability variate) value of the streamflow used to characterize a hydrological drought, akin to the standardized precipitation index (SPI, which is both standardized and normalized) in the realm of the meteorological drought. The time series of the SHI can be used as a platform for deriving the longest duration, L_T, and the largest magnitude, M_T (in standardized form), of a hydrological drought over a desired return period of T time units (year, month, or week). These parameters are predicted based on the SHI series derived from the annual, monthly, and weekly flow sequences of Canadian rivers. An important point to be reckoned with is that the monthly and weekly sequences are non-stationary compared to the annual sequences, which fulfil the conditions of stochastic stationarity. The parameters, such as the mean, standard deviation (or coefficient of variation), lag 1 autocorrelation, and conditional probabilities from SHI sequences, when used in Markov chain-based relationships, are able to predict the longest duration, L_T, and the largest magnitude, M_T. The product moment and L-moment ratio analyses indicate that the monthly and weekly flows in the Canadian rivers fit the gamma probability distribution function (pdf) reasonably well, whereas annual flows can be regarded to follow the normal pdf. The threshold level chosen in the analysis is the long-term median of SHI sequences for the annual flows. For the monthly and weekly flows, the threshold level represents the median of the respective month or week and hence is time varying. The runs of deficit in the SHI sequences are treated as drought episodes and thus the theory of runs formed an essential tool for analysis. This paper indicates that the Markov chain-based methodology works well for predicting L_T on annual, monthly, and weekly SHI sequences. Markov chains of zero order (MC0), first order (MC1), and second order (MC2) turned out to be satisfactory on annual, monthly, and weekly scales, respectively. The drought magnitude, M_T, was predicted satisfactorily via the model M_T = I_d × L_c, where I_d stands for drought intensity and L_c is a characteristic drought length related to L_T through a scaling parameter, ɸ (= 0.5). The I_d can be deemed to follow a truncated normal pdf, whose mean and variance when combined implicitly with L_c proved prudent for predicting M_T at all time scales in the aforesaid relationship. Full article

Stringent sustainability goals are set for the next generation of aircraft. A promising novel airframe concept is the ultra-high aspect ratio Strut-Braced Wing (SBW) aircraft. Hydrogen-based concepts are active contenders for sustainable propulsion. The study compares a medium-range Liquid Hydrogen (LH2) to a kerosene-based SBW aircraft designed with the same top-level requirements. For both concepts, overall design, operating costs, and emissions are evaluated using the tool SUAVE. Furthermore, aerostructural optimizations are performed for the wing mass of SBW aircraft with and without wing-based fuel tanks. Results show that the main difference in the design point definition results from a higher zero-lift drag due to an extended fuselage housing the LH2 tanks, with a small reduction in the required wing loading. Structural mass increases of the LH2 aircraft due to additional tanks and fuselage structure are mostly offset by fuel mass savings. While the fuel mass accounts for nearly 25% of the kerosene design’s Maximum Take-Off Mass (MTOM), this reduces to 10% for the LH2 design. The LH2 aircraft has 16% higher operating costs with emission levels reduced to 57–82% of the kerosene aircraft, depending on the LH2 production method. For static loads, the absence of fuel acting as bending moment relief in the wing results in an increase in wing structural mass. However, the inclusion of roll rate requirements causes large wing mass increases for both concepts, significantly outweighing dry wing penalties. Full article

With advancements in bipedal locomotion for humanoid robots, a critical challenge lies in generating gaits that are bounded to ensure stable operation in complex environments. Traditional Model Predictive Control (MPC) methods based on Linear Inverted Pendulum (LIP) or Cart–Table (C-T) methods are straightforward and linear but inadequate for robots with flexible joints and linkages. To overcome this limitation, we propose a Flexible MPC (FMPC) framework that incorporates joint dynamics modeling and emphasizes bounded gait control to enable humanoid robots to achieve stable motion in various conditions. The FMPC is based on an enhanced flexible C-T model as the motion model, featuring an elastic layer and an auxiliary second center of mass (CoM) to simulate joint systems. The flexible C-T model’s inversion derivation allows it to be effectively transformed into the predictive equation for the FMPC, therefore enriching its flexible dynamic behavior representation. We further use the Zero Moment Point (ZMP) velocity as a control variable and integrate multiple constraints that emphasize CoM constraint, embed explicit bounded constraint, and integrate ZMP constraint, therefore enabling the control of model flexibility and enhancement of stability. Since all the above constraints are shown to be linear in the control variables, a quadratic programming (QP) problem is established that guarantees that the CoM trajectory is bounded. Lastly, simulations validate the effectiveness of the proposed method, emphasizing its capacity to generate bounded CoM/ZMP trajectories across diverse conditions, underscoring its potential to enhance gait control. In addition, the validation of the simulation of real robot motion on the robots CASBOT and Openloong, in turn, demonstrates the effectiveness and robustness of our approach. Full article

We investigate a nonlinear integral equation derived through moment approximation from the individual-based representation of spatial logistic dynamics. The equation describes how the densities of pairs of individuals represented by points in continuous space are expected to equilibrate under spatially explicit birth–death processes characterized by constant fecundity with local natal dispersal and variable mortality determined by local competition. The equation is derived from a moment hierarchy truncated by a moment closure expressing the densities of triplets as a function of the densities of pairs. Focusing on results for individuals inhabiting two-dimensional habitats, we explore the solvability of the equation by introducing a dedicated space of functions that are integrable up to a constant. Using this function space, we establish sufficient conditions for the existence of solutions of the equation within a zero-centered ball. For illustration and further insights, we complement our analytical findings with numerical results. Full article

Many companies are turning their attention to digitizing the work efficiency of employees in large factories and warehouses, and the demand for measuring individual self-location indoors is increasing. While methods combining wireless network technology and Pedestrian Dead Reckoning (PDR) have been developed, they face challenges such as high infrastructure costs and low accuracy. In this study, we propose a novel approach that combines high-accuracy fiducial markers with the Center of Gravity Zero Moment Point (COG ZMP) model. Combining fiducial markers enables precise estimation of self-position on a map. Furthermore, the use of high-accuracy fiducial markers corrects modeling errors in the COG ZMP model, enhancing accuracy. This method was evaluated using an optical motion capture system, confirming high accuracy with a relative error of less than 3%. Thus, this approach allows for high-accuracy self-position estimation with minimal computational load and standalone operation. Moreover, it offers a cost-effective solution, contributing to society by enabling low-cost, high-performance self-positioning. This research enables high-accuracy standalone self-positioning and contributes to the advancement of indoor positioning technology. Full article

Parkinson’s disease (PD) is a neurodegenerative disorder and always results in balance loss. Although studies in lower-extremity exoskeleton robots are ample, applications with a lower-extremity exoskeleton robot for PD patients are still challenging. This paper aims to develop an effective assistive control for PD patients with a lower-extremity exoskeleton robot to maintain standing balance while being subjected to external disturbances. When an external force is applied to participants to force them to lose balance, the hip strategy for balance recovery based on the zero moment point (ZMP) metrics is used to generate a reference trajectory of the hip joint, and then, a model-free linear extended state observer (LESO)-based fuzzy sliding mode control (FSMC) is synthesized to regulate the human body to recover balance. Balance recovery trials for healthy individuals and PD patients with and without exoskeleton assistance were conducted to evaluate the performance of the proposed exoskeleton robot and balance recovery strategy. Our experiments demonstrated the potential effectiveness of the proposed exoskeleton robot and controller for standing balance recovery control in PD patients. Full article

Background/Objectives: Human papillomavirus (HPV) is a causative agent of infections and cancers of the reproductive and digestive tract, and vaccination is the most effective prevention method. This research aimed to assess the impact of health education on vaccination coverage and knowledge of the school population related to HPV infection and vaccination. Methods: This non-randomized clinical trial included 170 participants out of the 221 students in the generation of 2022/2023, who were divided into a group of Subjects and Controls and who self-assessed their knowledge and tested knowledge at four and two time points, respectively. Results: The study examined whether there is a difference in the share of vaccinated students of the entire generation compared to the previous generation (62% vs. 47%). The self-assessment and assessment of one’s knowledge in the group of subjects was significantly lower before education than during other time points during the research. At “moment zero”, there was no significant difference in the knowledge assessment between the groups. However, after 8 weeks, the knowledge assessment was significantly higher in the Subject group. Conclusions: The results suggest a positive impact of health education, which may contribute to raising awareness about the importance of prevention and vaccination against HPV. Full article

In recent decades, the study of discrete distributions has received increasing attention in the field of statistics, mainly because discrete distributions can model a wide range of count data. One common distribution used for modeling count data, for instance, is the negative binomial distribution (NBD), which performs well with over-dispersed data. In this paper, a new count distribution is introduced, called the conflation of negative binomial and logarithmic distributions, which is formed by conflating the negative binomial and logarithmic distributions, resulting in a distribution that possesses some of the properties of negative binomial and logarithmic distributions. The distribution has two parameters and is verified by a positive integer. Two modifications are proposed to the distribution, which includes zero as a support point. The new distribution is valuable from a theoretical perspective since it is a member of the weighted negative binomial distribution family. In addition, the distribution differs from the NBD in the sense that the probability of lower counts is inflated. This study discusses the characteristics of the proposed distribution and its modified versions, such as moments, probability generating functions, likelihood stochastic ordering, log-concavity, and unimodality properties. Real-world data are used to evaluate the performance of the proposed models against other models. All computations shown in this paper were produced using the R programming language. Full article

This article examines the flight dynamics and trajectory analysis of a parachute–payload system deployed from a C-17 aircraft. The aircraft is modeled with an open cargo door, extended flaps, and four turbo-fan engines operating at an altitude of 2000 feet Above Ground Level (AGL) and an airspeed of 150 knots. The payloads consist of simplified CONEX containers measuring either 192 inches or 240 inches in length, 9 feet in width, and 5.3 feet in height, with their mass and moments of inertia specified. At positive deck angles, gravitational forces cause these payloads to begin a gradual descent from the rear of the aircraft. For aircraft at zero deck angle, a ring-slot parachute with approximately 20% geometric porosity is utilized to extract the payload from the aircraft. This study specifically employs the CREATE-AV Kestrel simulation software to model the chute-payload system. The extraction and suspension lines are represented using Kestrel’s Catenary capability, with the extraction line connected to the floating confluence points of the CONEX container and the chute. The chute and payload will experience coupled motion, allowing for an in-depth analysis of the flight dynamics and trajectory of both elements. The trajectory data obtained will be compared to that of a payload (without chute and cables) exiting the aircraft at positive deck angles. An adaptive mesh refinement technique is applied to accurately capture the engine exhaust flow and the wake generated by the C-17, chute, and payloads. Friction and ejector forces are estimated to align the exit velocity and timing with those recorded during flight testing. The results indicate that the simulation of extracted payloads aligns with expected trends observed in flight tests. Notably, higher deck angles result in longer distances from the ramp, leading to increased exit velocities and reduced payload rotation rates. All payloads exhibit clockwise rotation upon leaving the ramp. The parachute extraction method yields significantly higher exit velocities and shorter exit times, while the payload-chute acceleration correlates with the predicted drag of the chute as demonstrated in prior studies. Full article

In this paper, for the first time, experimental tests of complete offline walking gaits generated by the essential model are performed. This model does not make simplifications in the dynamics of the robot, and its main advantage is the definition of desired Zero Moment Point trajectories. The designed gaits are implemented in the NAO robot, where starting and stopping stages are also included. Simulations in MATLAB and Webots, and experiments with the real robot are shown. Also, important remarks about the implementation of walking trajectories in the NAO robot are included, such as dealing with the hip joint shared by both legs. A comparison between the linear inverted pendulum (LIP) model and the essential model is also addressed in the experiments. As expected, the robot fails following the offline gait generated by the LIP model, but it does not with the essential model. Moreover, in order to push the boundaries of the essential model, a complex gait is designed with a vertical motion of the center of mass and an abrupt movement of the arms. As shown in experiments, no external balance controller is required to perform this complex gait. Thus, the efficiency of the essential model to design stable open-loop complex gaits is verified. Full article

The automotive industries currently face challenges such as emission limits, traffic congestion, and limited parking, which have prompted shifts in consumer preferences and modern passenger vehicle requirements towards compact vehicles. However, given the inherent limited width of compact vehicles, the potential risk of vehicle rollover is greater than that of regular vehicles. This paper addresses the safety concerns associated with vehicle rollover, focusing on narrow tilting vehicles (NTVs). Quantifying stability involves numerical indicators such as the lateral load transfer ratio (LTR). Additionally, a unique approach is taken by applying ZMP (zero moment point), commonly used in the robotics field, as an indicator of vehicle stability. Effective roll control requires a detailed analysis of the vehicle’s characteristic model and the derivation of lateral and roll dynamics. The paper presents the detailed roll dynamics of an NTV with a MacPherson strut-type suspension. A stability-enhancing method is proposed using a cascade structure based on the internal robust position controller and outer roll stability controller, addressing challenges posed by disturbances. Experimental verification using Simscape Multibody and CarSim validates the dynamic model and controller’s effectiveness, ensuring the reliability of the proposed tilting control for NTVs in practical scenarios. Full article

In spite of the IMO’s efforts to improve the safety of intact stability on ships, synchronous rolling still causes large rolling angles, resulting in a very dangerous situation on board. The implementation of automatic tools to predict this undesirable situation has not been widely implemented. Furthermore, the safety of ship stability is not the only responsibility of people involved in the design process, so ship operators must have enough knowledge to predict and avoid these dangerous situations well in advance. Therefore, from a theoretical point of view, in the first part, this paper aims to present a valuable guiding tool for ship operators in order to predict synchronous rolling and avoid undesirable situations on board by making use of only empirical observations of the wave profile and moments. With this purpose, mathematical models are first proposed, with the ship sailing in the worst condition, i.e., with and without considering the damping factor, at zero speed and considering the influence of any pure beam and trochoidal waves. Relevant results shown provide the exact time and wave profile at which the maximum rolling angles are reached. In the second part of the paper, a new control system making use of AI tools is proposed in order to be used by ship operators on board, avoiding dangerous situations. Finally, the results are validated using a set of ship rolling simulations for the most common and representative ship loading conditions and wave periods. Full article