Multiparameter Numerical Investigation of Two Types of Moving Interactions Between the Deep-Sea Mining Vehicle Track Plate and Seabed Soil:Digging and Rotating Motions

To ensure the safe performance of deep-sea mining vehicles(DSMVs),it is necessary to study the mechanical characteristics of the interaction between the seabed soil and the track plate.The rotation and digging motions of the track plate are important links in the contact between the driving mechanism of the DSMV and seabed soil.In this study,a numerical simulation is conducted using the coupled Eulerian–Lagrangian(CEL)large deformation numerical method to investigate the interaction between the track plate of the DSMV and the seabed soil under two working conditions:rotating condition and digging condition.First,a soil numerical model is established based on the elastoplastic mechanical characterization using the basic physical and mechanical properties of the seabed soil obtained by in situ sampling.Subsequently,the soil disturbance mechanism and the dynamic mechanical response of the track plate under rotating and digging conditions are obtained through the analysis of the sensitivity of the motion parameters,the grouser structure,the layered soil features and the soil heterogeneity.The results indicate that the above parameters remarkably influence the interaction between the DSMV and the seabed soil.Therefore,it is important to consider the rotating and digging motion of the DSMV in practical engineering to develop a detailed optimization design of the track plate.

Experimental study on reinforcement of bionic grouser of deep-sea mining vehicle

To fulfill the operational demands of deep-sea tracked mining vehicles traversing soft seabed substrates,an evaluation of the characteristics of these substrates was conducted,drawing a comparison with the land swamp black soil found in the buffalo's habitat.Employing the principles of biomimicry,two distinct types of bionic grouser were devised,replicating the configuration of the buffalo's hooves in both the horizontal and vertical planes.Utilizing self-constructed testing platforms,exhaustive examinations of the reinforcement efficacy of these bionic track grousers were undertaken,spanning from single-grouser to multi-grouser configurations and encompassing the entire track assembly.The findings unequivocally demonstrate a pronounced and consistent enhancement in traction force for both types of bionic grousers.Notably,the W-shaped bionic grouser,mimicking the horizontal contour of the buffalo's hoof,exhibits the most substantial increase in traction force.The maximum enhancement in traction force for individual bionic grouser exceeds 30%,while the overall track achieves an increase of over 19%.This research provides a valuable reference and establishes a foundational framework for the design of equipment tailored for the locomotion of deep-sea tracked mining vehicles across soft substrates.

Automatic Carrier Landing Control for Unmanned Aerial Vehicles Based on Preview Control

For carrier-based unmanned aerial vehicles(UAVs),one of the important problems is the design of an automatic carrier landing system(ACLS)that would enable the UAVs to accomplish autolanding on the aircraft carrier.However,due to the movements of the flight deck with six degree-of-freedom,the autolanding becomes sophisticated.To solve this problem,an accurate and effective ACLS is developed,which is composed of an optimal preview control based flight control system and a Kalman filter based deck motion predictor.The preview control fuses the future information of the reference glide slope to improve landing precision.The reference glide slope is normally a straight line.However,the deck motion will change the position of the ideal landing point,and tracking the ideal straight glide slope may cause landing failure.Therefore,the predictive deck motion information from the deck motion predictor is used to correct the reference glide slope,which decreases the dispersion around the desired landing point.Finally,simulations are carried out to verify the performance of the designed ACLS based on a nonlinear UAV model.

Trajectory Tracking of Vertical Take-off and Landing Unmanned Aerial Vehicles Based on Disturbance Rejection Control

We investigate the trajectory tracking problem of vertical take-off and landing (VTOL) unmanned aerial vehicles (UAV), and propose a practical disturbance rejection control strategy. Firstly, the nonlinear error model is established completely by the modified Rodrigues parameters, while considering dynamics of the servo actuators. Then, a hierarchical control scheme is applied to design the translational and rotational controllers based on the time-scale property of each subsystem, respectively. And the linear extended state observer and auxiliary observer are used to deal with the uncertainties and saturation. At last, global stability of the closed-loop system is analyzed based on the singular perturbation theory. Simulation results show the effectiveness of the proposed control strategy. © 2014 Chinese Association of Automation.

A fast computational method for the landing footprints of space-to-ground vehicles

Fast computation of the landing footprint of a space-to-ground vehicle is a basic requirement for the deployment of parking orbits, as well as for enabling decision makers to develop real-time programs of transfer trajectories. In order to address the usually slow computational time for the determination of the landing footprint of a space-to-ground vehicle under finite thrust, this work proposes a method that uses polynomial equations to describe the boundaries of the landing footprint and uses back propagation(BP) neural networks to quickly determine the landing footprint of the space-to-ground vehicle. First, given orbital parameters and a manoeuvre moment, the solution model of the landing footprint of a space-to-ground vehicle under finite thrust is established. Second, given arbitrary orbital parameters and an arbitrary manoeuvre moment, a fast computational model for the landing footprint of a space-to-ground vehicle based on BP neural networks is provided.Finally, the simulation results demonstrate that under the premise of ensuring accuracy, the proposed method can quickly determine the landing footprint of a space-to-ground vehicle with arbitrary orbital parameters and arbitrary manoeuvre moments. The proposed fast computational method for determining a landing footprint lays a foundation for the parking-orbit configuration and supports the design of real-time transfer trajectories.

Turning traction force of tracked mining vehicle based on rheological property of deep-sea sediment

Based on main physical and mechanical properties of deep-sea sediment from C-C poly-metallic nodule mining area in the Pacific Ocean, the best sediment simulant was successfully prepared by mixing bentonite with a certain content of water. Compression-shear coupling rheological constitutive model of the sediment simulant was established by endochronic theory and the coupling rheological parameters were obtained by compressive and compression-shear creep tests. A new calculation formula of turning traction force of the tracked mining vehicle was first derived based on the coupling rheological model and consideration of pushing resistance and sinkage of the tracked mining vehicle. Effects of the turning velocity, crawler spacing and contacting length of crawler with deep-sea sediment on the turning traction force were analyzed. Research results can provide theoretical foundation for operation safety and optimal design of the tracked mining vehicle.

Predicting the sinkage of a moving tracked mining vehicle using a new rheological formulation for soft deep-sea sediment

The sinkage of a moving tracked mining vehicle is greatly af fected by the combined compression-shear rheological properties of soft deep-sea sediments. For test purposes, the best sediment simulant is prepared based on soft deep-sea sediment from a C-C poly-metallic nodule mining area in the Pacific Ocean. Compressive creep tests and shear creep tests are combined to obtain compressive and shear rheological parameters to establish a combined compressive-shear rheological constitutive model and a compression-sinkage rheological constitutive model. The combined compression-shear rheological sinkage of the tracked mining vehicle at dif ferent speeds is calculated using the Recur Dyn software with a selfprogrammed subroutine to implement the combined compression-shear rheological constitutive model. The model results are compared with shear rheological sinkage and ordinary sinkage(without consideration of rheological properties). These results show that the combined compression-shear rheological constitutive model must be taken into account when calculating the sinkage of a tracked mining vehicle. The combined compression-shear rheological sinkage decrease with vehicle speed and is the largest among the three types of sinkage. The developed subroutine in the Recur Dyn software can be used to study the performance and structural optimization of moving tracked mining vehicles.

A Generic Plug-and-Play Navigation Fusion Strategy for Land Vehicles in GNSS-Denied Environment

Achieving accurate navigation information by integrating multiple sensors is key to the safe operation of land vehicles in global navigation satellite system(GNSS)-denied environment.However,current multi-sensor fusion methods are based on stovepipe architecture,which is optimized with custom fusion strategy for specific sensors.Seeking to develop adaptable navigation that allows rapid integration of any combination of sensors to obtain robust and high-precision navigation solutions in GNSS-denied environment,we propose a generic plug-and-play fusion strategy to estimate land vehicle states.The proposed strategy can handle different sensors in a plug-and-play manner as sensors are abstracted and represented by generic models,which allows rapid reconfiguration whenever a sensor signal is additional or lost during operation.Relative estimations are fused with absolute sensors based on improved factor graph,which includes sensors’error parameters in the non-linear optimization process to conduct sensor online calibration.We evaluate the performance of our approach using a land vehicle equipped with a global positioning system(GPS)receiver as well as inertial measurement unit(IMU),camera,wireless sensor and odometer.GPS is not integrated into the system but treated as ground truth.Results are compared with the most common filtering-based fusion algorithm.It shows that our strategy can process low-quality input sources in a plug-and-play and robust manner and its performance outperforms filtering-based method in GNSS-denied environment.

INERTIAL INTEGRATED SYSTEM OF NORTH SEEKING/SIGHT STABILIZING ON VEHICLE

A brand new method of automatic north seeking/sight stabilizing is introduced for usage in land fighting vehicles such as tank, etc. Some inertial devices are installed additionally on the platform along with relative control circuits to make its function of North seeking possible. Double position calculation is adopted in this method, and by alignment at two sites the azimuth angle can be figured out. Also the orientation and the horizontal shifts of the gyro are simultaneously measured and compensated so as to improve the accuracy of north seeking. The system can automatically seek north when the vehicle is immobile. And the time consumption is no more than 5.5 min. Besides, the system can keep azimuth angle and provide tilt angle and pitch angle of the vehicle.

GUIDANCE AND CONTROL FOR AUTOMATIC LANDING OF UAV

A scheme of guidance and control is presented to meet the requirements for automatic landing of unmanned aerial vehicles (UAVs) based on the airborne digital flight control system and radio tracker on ground station. An automatic landing system is realized for an unmanned aerial vehicle. The results of real time simulation and flight test are given to illustrate the effectiveness and availability of the scheme. Results meet all the requirements for automatic landing of the unmanned aerial vehicle.

Multi-objective Optimization Design of Vented Cylindrical Airbag Cushioning System for Unmanned Aerial Vehicle

Multi-objective optimization design of the gas-filled bag cushion landing system is investigated.Firstly,the landing process of airbag is decomposed into a adiabatic compression and a release of landing shock energy,and the differential equation of cylindrical gas-filled bag is presented from a theoretical perspective based on the ideal gas state equation and dynamic equation.Then,the effects of exhaust areas and blasting pressure on buffer characteristics are studied,taking those parameters as design variable for the multiobjective optimization problem,and the solution can be determined by comparing Pareto set,which is gained by NSGA-Ⅱ.Finally,the feasibility of the design scheme is verified by experimental results of the ground test.

Tradeoff Analysis of Factors Affecting Longitudinal Carrier Landing Performance for Small UAV Based on Backstepping Controller

Tradeoff analysis of the factors,including external environment and unmanned aerial vehicle(UAV)aerodynamic attributes,which affect longitudinal carrier landing performance,is important for small UAV.First,small UAV longitudinal carrier landing system is established,as well as the nonlinear dynamics and kinematics model,and then the longitudinal flight control system using backstepping technology with minimum information about the aerodynamic is designed.To assess the landing performance,a variety of influencing factors are considered,resulting in the constraints of aerodynamic attributes of carrier UAV.The simulation results show that the severe sea condition has the greatest influence on landing dispersion,while air wake is the primary factor on impact velocity.Among the longitudinal aerodynamic parameters,the lift curve slope is the most important factor affecting the landing performance,and increasing lift curve slope can improve the landing performance significantly.A better system performance will be achieved when the lift curve slope is larger than 2per radian.

Automated Autonomous Vehicles: Prospects and Impacts on Society

All automobile manufacturing companies, Google and Microsoft have announced recently their production of the Fully Automated Autonomous Vehicles (FAAVs), otherwise known as driverless cars. A few FAAVs would be available in the market as early as in 2018, but mostly in 2020’s. When FAAVs will be available to and become affordable by the average consumers, the implications to the society would be far reaching. The purpose of the paper is to examine the prospect of the popularity of FAAVs and their socio-economic implications to the future society of the World. The paper examines potential impacts on selected sectors of the society including changes in demand for automobiles, its impact on the use of oil, on the environment, and on urban land uses, to list a few.

Video-based construction vehicles detection and its application in intelligent monitoring system

While vehicle detection on highways has been reported before, to the best of our knowledge, intelligent monitoring system that aims at detecting hydraulic excavators and dump trucks on state-owned land has not been explored thoroughly yet. In this paper, we present an automatic, video-based algorithm for detecting hydraulic excavators and dump trucks. Derived from lessons learned from video processing, we proposed methods for foreground detection based on an improved frame difference algorithm, and then detected hydraulic excavators and dump trucks in the respective region of interest. From our analysis, we proposed methods based on inverse valley feature of mechanical arm and spatial-temporal reasoning for hydraulic excavator detection. In addition, we explored dump truck detection strategies that combine structured component projection with the spatial relationship. Experiments on real-monitoring sites demonstrated the promising performance of our system.

Switchable shape memory polymer bio-inspired adhesive and its application for unmanned aerial vehicle landing

Controlled and switchable adhesion is commonly observed in biological systems.In recent years,many scholars have focused on making switchable bio-inspired adhesives.However,making a bio-inspired adhesive with high adhesion performance and excellent dynamic switching properties is still a challenge.A Shape Memory Polymer Bio-inspired Adhesive(SMPBA)was successfully developed,well realizing high adhesion(about 337 kPa),relatively low preload(about90 kPa),high adhesion-to-preload ratio(about 3.74),high switching ratio(about 6.74),and easy detachment,which are attributed to the controlled modulus and contact area by regulating temperature and the Shape Memory Effect(SME).Furthermore,SMPBA exhibits adhesion strength of80–337 kPa on various surfaces(silicon,iron,and aluminum)with different roughness(Ra=0.021–10.280)because of the conformal contact,reflecting outstanding surface adaptability.The finite element analysis verifies the bending ability under different temperatures,while the adhesion model analyzes the influence of preload on contact area and adhesion.Furthermore,an Unmanned Aerial Vehicle(UAV)landing device with SMPBA was designed and manufactured to achieve UAV landing on and detaching from various surfaces.This study provides a novel switchable bio-inspired adhesive and UAV landing method.

融合语义分割与模糊推理的无人机应急降落选址算法

随着无人机的应用领域从娱乐摄影拓展到物流、军事和灾害响应,对于无人机的自主智能化要求也越来越高。针对无人机紧急情况下自主降落区域复杂难以保证着陆安全的问题,提出了一种实时语义分割网络与模糊推理相结合的降落选址算法(STDC-LSSNet)。考虑到潜在危险因素在航拍图像上占比小、易被错误分割的问题,提出了小目标特征提取模块(small target feature capture module,STFCM),通过计算不同尺度特征的相似性并进行权重分配,强化小目标特征的表达。考虑到安全区域与危险区域边界混淆会导致无人机降落存在巨大风险,提出了边界特征融合模块(boundary feature fusion module,BFFM),将浅层网络由拉普拉斯卷积得到的边界信息与深层网络的语义信息进行特征融合,引入注意力机制,增强边界区域特征的表达。通过对分割得到的图像进行模糊推理,从而精确识别应急降落地点。所提算法在公开数据集Semantic Drone和AeroScapes上与最先进的算法进行了广泛的对比实验,mIoU提升1.72个百分点和3.89个百分点,实时分割速度达到210 FPS,选址的速度达到58.62 ms,实现了无人机在复杂情况下的应急降落选址。

武汉市轨道交通车辆基地上盖开发规划指引研究

轨道交通车辆基地上盖的综合开发能实现城市土地的集约高效利用。近年来,武汉市5处车辆基地的复合开发项目已取得了良好效果,但未形成统一的标准化设计体系,亟需在总结北京、重庆、成都等城市的轨道交通设计指南或导则的基础上,梳理武汉市在车辆基地选址、功能布局与容量引导、交通一体化设计及公共空间营造等4个方面的规划指引要点,以期为后续武汉市车辆基地上盖开发设计指引的详细制定提供参考,使之适用于规范指导轨道交通上盖综合开发建设实践。

Cultivated land information extraction in UAV imagery based on deep convolutional neural network and transfer learning

The development of precision agriculture demands high accuracy and efficiency of cultivated land information extraction. As a new means of monitoring the ground in recent years, unmanned aerial vehicle （UAV） low-height remote sensing technique, which is flexible, efficient with low cost and with high resolution, is widely applied to investing various resources. Based on this, a novel extraction method for cultivated land information based on Deep Convolutional Neural Network and Transfer Learning （DTCLE） was proposed. First, linear features （roads and ridges etc.） were excluded based on Deep Convolutional Neural Network （DCNN）. Next, feature extraction method learned from DCNN was used to cultivated land information extraction by introducing transfer learning mechanism. Last, cultivated land information extraction results were completed by the DTCLE and eCognifion for cultivated land information extraction （ECLE）. The location of the Pengzhou County and Guanghan County, Sichuan Province were selected for the experimental purpose. The experimental results showed that the overall precision for the experimental image 1, 2 and 3 （of extracting cultivated land） with the DTCLE method was 91.7%, 88.1% and 88.2% respectively, and the overall precision of ECLE is 9o.7%, 90.5% and 87.0%, respectively. Accuracy of DTCLE was equivalent to that of ECLE, and also outperformed ECLE in terms of integrity and continuity.

Deep-sea rock mechanics and mining technology:State of the art and perspectives

The review covers the development and the state of the art in deep-sea mining rock mechanics,equipment and challenges.It begins by introducing the significance of deep-sea mining,the types and geographical distribution of deep-sea resources.Section 2 reviews the mechanical properties and fracture mechanism of seabed and related continental rocks,which contributes to the advancement of relevant technologies and theories.Deep-sea mining systems developed by coastal countries are presented in Section 3.Seabed mineral collection systems are critically assessed in Section 4.Subsea mining vehicle is reviewed by walking mechanism and controlling system in Section 5.In Section 6,the development of subsea lifting system is detailed by dividing it into hydraulic and pneumatic lifting modes,and some technical problems in the lifting system are described.An in-depth description of surface support systems is presented in Section 7,which includes the deep-sea mining ship,dynamic positioning system,heave compensation system,launch and retrieval system,mineral disposing system as well as the storage and transferring systems.Section 8 discusses the challenges in the deep-sea mining,in terms of natural occurrence conditions,international legal framework and cooperative mining,environmental protection and economic benefits,etc.Finally,a brief summary and some aspects of prospective research are presented in Section 9.

Avian contrast sensitivity inspired contour detector for unmanned aerial vehicle landing

Runway detection is a demanding task for autonomous landing of unmanned aerial vehicles. Inspired by the attenuation effect and surround suppression mechanism, a novel biologically computational method based on the avian contrast sensitivity is proposed for runway contour detection. For the noisy stimuli, deniosed responses of the biologically inspired Gabor energy operator are generalized followed by the denoising layer and the multiresolution fusion layer. Moreover, two factors such as contour effect and texture suppression are considered in the contrast sensitivity based surround inhibition. Different from traditional detectors, which do not distinguish between contours and texture edges, the proposed method can respond strongly to contours and suppress the texture information. Applying the contrast sensitivity inspired detector to noisy runway scenes yields effective contours, while the non-meaningful texture elements are removed dramatically at the same time. Besides the superior performance over traditional detectors, the proposed method is capable to provide insight into the attenuation effect of the avian contrast sensitivity function and has potential applications in computer vision and pattern recognition.