An evolutionary algorithm for simultaneous localization and mapping (SLAM) of mobile robots

This paper presents a novel algorithm for simultaneous localization and mapping (SLAM) of mobile robots. The algorithm, termed Evolutionary SLAM, is based on an island model genetic algorithm (IGA). The IGA searches for the most probable map(s) such that the underlying robot's pose(s) provide(s) a robot with the best localization information. The correspondence problem in SLAM is solved by exploiting the property of natural selection, to support only better-performing individuals to survive. The algorithm does not follow any explicit heuristics for loop closure, rather it maintains multiple hypotheses to solve the loop-closing problem. The algorithm processes sensor data incrementally and, therefore, has the capability to work online. Experimental results in different indoor environments validate the robustness of the proposed algorithm.     

Development of a single-master multi-slave tele-micromanipulation system

This paper proposes the development of a human–robot cooperative tele-micromanipulation system through a network. We have developed a novel single-master (PHANToM haptic device) multi-slave (6-d.o.f. parallel manipulator) scaled tele-micromanipulation system which enables human operators to perform meso or small-size object manipulation such as assembly or manufacturing with sufficient telepresence. It is expected to improve the human's operability and the overall dexterity of conventional tele-micromanipulation systems. To overcome the problems of the multiple parallel mechanism manipulator, virtual kinematic mapping is considered, based on the manipulability analysis of the workspace. The pick-and-place experiment results prove the validity of the developed single-master multi-slave system.     

Heterogeneous multisensor fusion for mapping dynamic environments

In this paper, we propose a heterogeneous multisensor fusion algorithm for mapping in dynamic environments. The algorithm synergistically integrates the information obtained from an uncalibrated camera and sonar sensors to facilitate mapping and tracking. The sonar data is mainly used to build a weighted line-based map via the fuzzy clustering technique. The line weight, with confidence corresponding to the moving object, is determined by both sonar and vision data. The motion tracking is primarily accomplished by vision data using particle filtering and the sonar vectors originated from moving objects are used to modulate the sample weighting. A fuzzy system is implemented to fuse the two sensor data features. Additionally, in order to build a consistent global map and maintain reliable tracking of moving objects, the well-known extended Kalman filter is applied to estimate the states of robot pose and map features. Thus, more robust performance in mapping as well as tracking are achieved. The empirical results carried out on the Pioneer 2DX mobile robot demonstrate that the proposed algorithm outperforms the methods a using homogeneous sensor, in mapping as well as tracking behaviors.     

SLAMMOT-SP: Simultaneous SLAMMOT and Scene Prediction

In recent years, SLAMMOT (simultaneous localization, mapping and moving object tracking) has attracted widespread attention in the mobile robot field. This paper proposes a new approach, SLAMMOT-SP, which combines SLAMMOT and scene prediction (SP). It extends the SLAMMOT problem to simultaneous map prediction and moving object trajectory prediction. The robot not only passively collects the data and executes SLAMMOT, but actively predicts the scene. The recursive Bayesian formulation of SLAMMOT-SP is derived for real-time operations. A generalized framework for tracking and predicting the moving objects is also proposed. Simulations and experiments show that the proposed SLAMMOT-SP is effective and can be performed in real-time.     

Virtual circle mapping for master–slave hand systems

The classical mapping methods were developed based on anthropomorphic robot hands. Normally, they are not applicable or cannot provide satisfactory performance if the robot hand is non-anthropomorphic. This paper presents a virtual circle mapping method dealing with the three-fingered non-anthropomorphic robot hand. The basic idea is to express the operator's motion by a virtual circle determined by the three fingertips. Four sets of parameters are used to describe the circle: circle radius, central angles, circle center and circle orientation. By transforming the four sets of parameters from the human frame to the robot frame, the information of relative positions between the fingertips is delivered. The robot fingertip positions are then computed according to the transformed parameters. The concept is introduced and implemented on a specific three-fingered non-anthropomorphic robot hand. The simulation results and the experiments have shown that the proposed method is able to obtain better workspace matching and, thus, the operator can tele-control the robot hand more intuitively.     

Behaviour of surface oxide scale before roll bite in hot rolling of steel

Abstract

Hot stalling rolling tests using mild steel slabs with thin and thick scale layers, and cold stalling rolling simulation tests using lead slabs coated with brittle lacquer layers, have been conducted to investigate the behaviour of the surface oxide scales before hot rolling. The effects of rolling reduction, temperature, scale thickness and structure, and slab geometry were examined. The experimental results indicate that the oxide scale can either adhere and deform with the parent steel, or delaminate from the parent steel, or suffer from cracking before hot rolling, depending on the hot strength of the scale and the stress status in the scale, which depend on rolling reduction and temperature, and scale thickness and structure. Therefore, the cracks observed in the oxide scales on the steel slab after hot rolling are generally the combined results of cracking before rolling and further cracking in the roll gap. On the basis of comparative analysis, the prerolling behaviour of the oxide scales in a laboratory scale rolling mill and in an industrial hot strip mill is discussed.     

Statistical method for evaluating and ranking lubricants through micromechanical heterogeneity mapping of surfaces that experienced lubricated sliding

Abstract

The requirements for improved fuel economy and reduced vehicle emission have driven the lubricant industry to develop new lubricants for engines and other dynamic systems. The selection of appropriate lubricant formulation is a complicated process involving extensive and costly bench and field tests. Thus, there is a demand for developing quick, effective and less costly methods to evaluate and rank lubricants. The authors previously proposed a statistical technique for evaluating and ranking lubricants through examining spatial variations in local mechanical properties of a worn surface after lubricated sliding testing using a micromechanical probe. Examination of the mechanical heterogeneity of worn surface has been turned out a promising approach for prescreening lubricants before further bench and field tests. Research was conducted to further investigate the suitability of such a method to evaluate lubricant performance during lubricated wear tests for a number of engineering materials and in particular, to identify which mechanical property (e.g. hardness, Young's modulus, creep behaviour) was the most sensitive and reliable indicator of the surface mechanical heterogeneity. Efforts were also made to identify the optimum indentation load range for evaluating the mechanical heterogeneity. It was demonstrated that the statistical method based on the heterogeneity of worn surfaces was effective for evaluating and ranking lubricants. Microhardness was proven to be the most suitable parameter for evaluation of the mechanical heterogeneity of worn surfaces, especially for harder materials.     

Efficient Simultaneous Localization and Mapping Based on Ceiling-View: Ceiling Boundary Feature Map Approach

For simultaneous localization and mapping (SLAM) based on the extended Kalman filter, the size of the state vector is an essential factor because the feasibility depends on it. In this paper, a new SLAM based on ceiling vision (cv-SLAM) is proposed. To keep the size of the state vector compact, the boundaries between ceiling and walls are used as landmarks for visual SLAM (vSLAM). The ceiling boundaries are robust to illuminative variations and they are not as numerous as the point features. Some constraints are imposed on the features based on the characteristics of the ceiling boundaries and an efficient update method called 'double update' is proposed to improve the SLAM performance. The basic idea of the double update is to fully utilize the intersections of the boundary features. Finally, the proposed SLAM is applied to some simulations and experiment, and its effectiveness is demonstrated through them.     

A Simultaneous Localization and Mapping Algorithm in Complex Environments: SLASEM

In this paper we present an algorithm for the application of simultaneous localization and mapping in complex environments. Instead of building a grid map or building a feature map with a small number of the obstacles' geometric parameters, the proposed algorithm builds a sampled environment map (SEM) to represent a complex environment with a set of environment samples. To overcome the lack of one-toone correspondence between environment samples and raw observations, the signed orthogonal distance function is proposed to be used as the observation model. A method considering geometric constraints is presented to remove redundant environment samples from the SEM. We also present a method to improve the SEM's topological consistency by using corner constraints. The proposed algorithm has been verified in a simulation and an indoor experiment. The results show that the algorithm can localize the robot and build a complex map effectively.     

Damage nucleation in nuclear graphite

Abstract

This paper reports the use of advanced materials characterisation techniques, X-ray microtomography and surface strain mapping by electronic speckle pattern interferometry (ESPI), to study the mechanisms of damage nucleation in polygranular nuclear graphite. It is found that strain localisation occurs owing to the heterogeneous microstructure, giving rise to microcrack nucleation and coalescence before tensile failure. This produces a substantial damage zone at stress concentrations, such as notches and crack tips, which can be observed directly and in situ. Crack propagation occurs by the coalescence of microcracks in the damage zone. The measured R curve is a consequence of both frictional bridging in the crack wake and energy dissipation in the microcrack process zone.