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This paper aims to gain the real-time terrain parameters of the battlefield for the evaluation of military vehicle trafficability. In military missions, improvements in vehicle mobility have the potential to greatly increase the military operational capacity, in which vehicle trafficability plays a significant role.

In this framework, an online terrain parameter estimation method based on the Gauss-Newton algorithm is proposed to estimate the primary terrain mechanical parameters. Good estimation results are indicated, unless the initial values involved are properly selected. Correspondingly, a method of terrain classification is then presented to contribute to the selection of the initial values. This method uses the wavelet packet transform technique for feature extraction and adopts the support vector machine algorithm for terrain classification. Once the terrain type is identified, advices can be given on the initial value selection referring to the empirical terrain parameters.

On the basis of a dynamic testing system suitable for real military vehicles, the proposed algorithms are validated. High estimation accuracy of the terrain parameters is indicated on sandy loam, and good classification performance is demonstrated on four tested terrains.

The presented algorithm outperforms the existing methods, which not only realizes the online terrain parameter estimation but also develops the estimation accuracy. Moreover, its effectiveness is confirmed by real vehicle tests in practice.

The purpose of this paper is to explore a novel measurement approach for wheel-terrain contact angle using laser scanning sensors based on near-terrain perception. Laser scanning sensors have rarely been applied to the measurement of wheel-terrain contact angle for wheeled mobile robots (WMRs) in previous studies; however, it is an effective way to measure wheel-terrain contact angle directly with the advantages of simple, fast and high accuracy.

First, kinematics model for a WMR moving on rough terrain was developed, taking into consideration wheel slip and wheel-terrain contact angle. Second, the measurement principles of wheel-terrain contact angle using laser scanning sensors was presented, including “rigid wheel - rigid terrain” model and “rigid wheel - deformable terrain” model.

In the proposed approach, the measurement of wheel-terrain contact angle using laser scanning sensors was successfully demonstrated. The rationality of the approach was verified by experiments on rigid and sandy terrains with satisfactory results.

This paper proposes a novel, fast and effective wheel-terrain contact angle measurement approach for WMRs moving on both rigid and deformable terrains, using laser scanning sensors.

This research aims to address the issue of safe navigation for autonomous vehicles in highly challenging outdoor environments. Indeed, robust navigation of autonomous mobile robots over long distances requires advanced perception means for terrain traversability assessment.

The use of visual systems may represent an efficient solution. This paper discusses recent findings in terrain traversability analysis from RGB-D images. In this context, the concept of point as described only by its Cartesian coordinates is reinterpreted in terms of local description. As a result, a novel descriptor for inferring the traversability of a terrain through its 3D representation, referred to as the unevenness point descriptor (UPD), is conceived. This descriptor features robustness and simplicity.

The UPD-based algorithm shows robust terrain perception capabilities in both indoor and outdoor environment. The algorithm is able to detect obstacles and terrain irregularities. The system performance is validated in field experiments in both indoor and outdoor environments.

The UPD enhances the interpretation of 3D scene to improve the ambient awareness of unmanned vehicles. The larger implications of this method reside in its applicability for path planning purposes.

This paper describes a visual algorithm for traversability assessment based on normal vectors analysis. The algorithm is simple and efficient providing fast real-time implementation, since the UPD does not require any data processing or previously generated digital elevation map to classify the scene. Moreover, it defines a local descriptor, which can be of general value for segmentation purposes of 3D point clouds and allows the underlining geometric pattern associated with each single 3D point to be fully captured and difficult scenarios to be correctly handled.

Magnetohydrodynamics angular regular sensor (MHD ARS) has been used in many applications for its low noise in wide bandwidth, impact resistance and low power consumption; however, it is unable to estimate the angular velocity at low frequencies such as below 1 Hz. It is difficult to design compensation methods without an exact model. The aim of this study is to investigate a more exact analytical model characterization of the sensor’s frequency response, especially at a low-frequency zone.

A correction coefficient of electromagnetic force in simplified MHD ARS model was introduced according to the theoretical analysis of MHD flow and it was obtained by numerical simulation of electromagnetic force varying with time, space structure and frequency.

To make comparison, the transfer function of the designed MHD ARS in the experiment was identified using Gauss–Newton method with reasonable weights. The identification results confirmed the analytical model. Furthermore, a digital filter was designed based on the analytical model, and the compensation results showed that the frequency limit at low-frequency side was extended from 1 to 0.01 Hz.

The modified analytical model can describe the MHD ARS’s frequency response exactly and may be applied in its low-frequency compensation.

To provide an autonomous navigation system to endow lunar rovers with increased autonomy both for exploration achievement of scientific goals and for safe navigation.

First, algorithm and technique of initial position determination of lunar rovers are introduced. Then, matched‐features set is build by multi steps of image processing such as feature detection, feature tracking and feature matching. Based on the analysis of the image processing error, a two‐stage estimation algorithm is used to estimate the motion, robust linear motion estimation is executed to estimate the motion initially and to reject the outliers, and Levenberg‐Marquardt non‐linear estimation is used to estimate the motion precisely. Next, a weighted ZSSD algorithm is presented to estimate the image disparities by analyzing the traditional ZSSD. Finally, a virtual simulation system is constructed using the development tool of open inventor, this simulation system can provide stereo images for simulations of stereo vision and motion estimation techniques, simulation results are provided and future research work is addressed in the end.

An autonomous navigation system is build based on stereo vision, the motion estimation algorithm and disparity estimation algorithm are developed.

The field test will be done in the near future to valid the autonomous navigation algorithm presented in this paper.

A very useful source of information for graduate students and technical reference for researchers who work on lunar rovers.

In this paper, stereo vision‐based autonomous navigation techniques for lunar rovers are discussed, and an autonomous navigation scheme which based on stereo vision is presented, and the validity of all the algorithms involved is confirmed by simulations.

The purpose of this paper is to strive to develop a rock fall velocity model in C++ language and to give spatial attributes to the model using Geographic Information System (GIS) capabilities. Interaction between the parameters involved in the model is evaluated through GIS embedded techniques.

The mathematical model developed in C++ is based on the physical law of gravitation pull, adjudging the potential fall between two points at different elevation. Further, parameters influencing the velocity gradient – namely local relief, coefficient of land use friction, slope amount and slope length – are incorporated in the model. GIS is used extensively to generate the data required for the model. GIS capabilities are also explored for visualisation and interpretation of the model output. Section profiles and a co‐relation coefficient further strengthen the velocity map.

The rock fall velocity map generated using GIS shows variations in the velocity gradient at selected sections. It is concluded from analysis that friction values play a pivotal role in drastically changing the velocity gradient.

The model presented is restricted to rock fall velocity evaluation for a rectangular matrix of input data and spatial extent, rather than for specific locations. Incorporating parameters to delineate source areas and runout zones would produce a more realistic scenario. Trials along this line are in progress and are expected to be executed successfully very shortly.

The paper presents a versatile model with easily extractable parameters to compute rock fall velocity at a regional scale, conditioned for rugged terrain. The model has specific implications in infrastructure development and planning management for rocky terrain. Moreover, the model's output can be implemented effectively in preliminary investigations of the protection of forest development and erecting defensive measures in rock fall‐prone areas.

Not many models are available for rock fall velocity estimation on a regional scale. The model developed through this research work provides a platform for a regional‐scale study using parameters that can be easily derived from DEM and a land use map. It is reiterated that the model output is helpful for land planners and managers engaged in mountain development. The model is an effective tool in the strategic development of hazard management plans in slide‐prone areas.

The purpose of this paper is to provide a new computational method based on the polynomial chaos (PC) expansion to identify the uncertain parameters of load sensing proportional valve (LSPV), which is commonly used to improve the efficiency of brake system in heavy truck.

For this investigation, the mathematic model of LSPV is constructed in the form of state space equation. Then the estimation process is implemented relying on the experimental measurements. With the coefficients of the PC expansion obtained by the numerical implementation, the output observation function can be transformed into a linear and time-invariant form. The uncertain parameter recursively update functions based on Newton method can therefore be derived fit for computer calculation. To improve the estimation accuracy and stability, the Newton method is modified by employing the acceptance probability to escape from the local minima during the estimation process.

The accuracy and effectiveness of the proposed parameter estimation method are confirmed by model validation compared with other estimation methods. Meanwhile, the influence of measurement noise on the robustness of the estimation methods is taken into consideration, and it is shown that the estimation approach developed in this paper could achieve impressive stability without compromising the convergence speed and accuracy too much.

The model of LSPV is originally developed in this paper, and then the authors propose a novel effective strategy for recursively estimating uncertain parameters of complicate pneumatic system based on the PC theory.

Availability of military systems is of major concern for military planners at both tactical (battle) level and at strategic level (long‐term national planning). Availability factors critically affect the operational effectiveness during military operations. Military systems are complex and lend themselves to simulation approach for availability estimation as analytical solutions are extremely difficult. The purpose of this paper is to discuss the method of systems modeling to approach the simulation for availability estimation of military systems.

Availability measures are needed for two main domains of application: peacetime operations and battlefield situations. Availability measures include not only inherent availability of interest to designers/manufacturers, but also operational availability and field/service availability. The simulation approach adopted here involves discrete event simulation (DES) techniques using Monte Carlo methods since a network of events can be included in the model. A system engineering approach is emphasized, starting with system representation and characterisation, and using system aggregation techniques.

Modeling involves hierarchical models and network diagrams for events. First the system is described by a hierarchical model; the events and transitions are represented with state transition diagrams (STD). The simulation scheme would be based on initial resources or inventory as military operations proceed, with random variates for event times or rates. The availability as a function of time A(t) is arrived at. The reliability and maintainability models are simulated with probability distributions or using empirical distributions. The methods of data collection and analysis, and sensitivity analysis are mentioned. The methodology is explained with two case studies from the authors' work. The approaches of other workers in recent years are summarised.

The paper shows that the simulation models can suitably be modified to include their applications for army and navy military operations. Also, with proper data on all major subsystems of interest for the weapon platform and accurate past war data, it is possible to fine‐tune the models for online use during military campaigns. The availability figures thus obtained may also be used for procurement decisions for long‐term and strategic planning.

The purpose of this study is to present an optimization-based gait planning method for biped robots according to the conditions of terrain, which takes fully the relationship between walking stability margin and energy efficiency into account.

First, the authors newly designed a practical gait motion synthesis algorithm by using the optimal allowable zero moment point (ZMP) variation region (OAZR), which can generate different gait motions corresponding to different terrains based on the modifiability of ZMP in lateral (y-axis) direction. Second, an effective gait parameter optimization algorithm is performed to find the optimal set of key gait parameters (step length, duration time of gait cycle, average height of center of mass (CoM), amplitude of the vertical CoM motion and double support ratio), which maximizes either the walking stability margin or the energy efficiency with certain walking stability margin under practical constraints (mechanical constraints of all joint motors, geometric constraints, friction force limit and yawing moment limit) according to the conditions of terrain. Third, the necessary controllers for biped robots have been introduced briefly.

The experiment data and results are described and analyzed, showing that the proposed method was verified through simulations and implemented on a DRC-XT biped robot.

The main contribution is that the OAZR has been defined based on AZR, which could be used to plan and generate the various feasible gait motions to help a biped robot to adapt effectively to various terrains.