Sound direction estimation using an artificial ear for robots

We propose a novel design of an artificial robot ear for sound direction estimation using two measured outputs only. The spectral features in the interaural transfer functions (ITFs) of the proposed artificial ears are distinctive and move monotonically according to the sound direction. Thus, these features provide effective sound cues to estimate sound direction using the measured two output signals. Bilateral asymmetry of microphone positions can enhance the estimation performance even in the median plane where interaural differences vanish. We propose a localization method to estimate the lateral and vertical angles simultaneously. The lateral angle is estimated using interaural time difference and Woodworth and Schlosberg’s formula, and the front–back discrimination is achieved by finding the spectral features in the ITF estimated from two measured outputs. The vertical angle of a sound source in the frontal region is estimated by comparing the spectral features in the estimated ITF with those in the database built in an anechoic chamber. The feasibility of the designed artificial ear and the estimation method were verified in a real environment. In the experiment, it was shown that both the front–back discrimination and the sound direction estimation in the frontal region can be achieved with reasonable accuracy. Thus, we expect that robots with the proposed artificial ear can estimate the direction of speaker from two output signals only.     

Planning the motions of a mobile robot in a sensory uncertaintyfield

Failures in mobile robot navigation are often caused by errors in localizing the robot relative to its environment. This paper explores the idea that these errors can be considerably reduced by planning paths taking the robot through positions where pertinent features of the environment can be sensed. It introduces the notion of a “sensory uncertainty field” (SUF). For every possible robot configuration q, this field estimates the distribution of possible errors in the robot configuration that would be computed by a localization function matching the data given by the sensors against an environment model, if the robot was at q. A planner is proposed which uses a precomputed SUF to generate paths that minimize expected errors or any other criterion combining, say, path length and errors. This paper describes in detail the computation of a specific SUF for a mobile robot equipped with a classical line-striping camera/laser range sensor. It presents an implemented SUF-based motion planner for this robot and shows paths generated by this planner. Navigation experiments were conducted with mobile robots using paths generated by the SUF-based planner and other paths. The former paths were tracked with greater precision than the others. The final section of the paper discusses additional research issues related to SUF-based planning     

一种基于RSSI的AOA估计算法

在无线传感器网络（WSNs）中,使用阵列天线进行到达角（AOA）估计存在成本昂贵和算法复杂度高的缺点,提出了一种基于接收信号强度指示（RSSI）的AOA估计算法。利用2个旋转的方向图部分重叠的定向天线接收RSSI值,通过双方向图求差法估计目标节点的AOA。实验结果表明：室内实验的AOA估计平均误差为6．7°,室外的平均误差为0．6°。该算法复杂度小,硬件成本低,适用于WSNs的节点定位。     

Direct position determination in the presence of model errors—known waveforms

The performance of the direct position determination (DPD) approach in the presence of model errors is examined. DPD was recently introduced as a promising technique for localization of multiple radio frequency emitters with superior accuracy under low signal-to-noise ratio conditions. We analyze the performance of DPD in the presence of model errors caused by multipath, calibration errors, mutual coupling, etc. The analysis is general enough to encapsulate various sources of errors. Monte Carlo simulations are used to validate the analysis. We show that in many cases of interest DPD should be selected as the preferred method of localization.     

一种基于N-最优阶次序列的无线传感器网络节点定位方法

基于阶次序列的无线传感器网络(Wireless sensor networks, WSN)定位方法是一种新颖的高精度定位方法, 该方法将定位空间划分为不同的子区域, 每个子区域用一条阶次序列唯一标识. 但该方法存在区域边界节点定位误差较大且不能保证平均定位误差最优. 提出了一种基于N-最优阶次序列的节点定位方法. 首先基于无线信号衰减模型产生虚拟测试点, 以参考点为样本, 通过随机采样确定最优N值,然后选择阶次位于前N位的序列所表示的子区域, 对目标进行加权定位. 文中完成了100个节点的仿真实验、15个ZigBee网络硬件节点的室外实验以及10个ZigBee硬件节点的防空洞模拟矿井应用实验. 结果表明, 本文方法有效地降低了平均定位误差, 并改善了边界节点的定位精度.     

侧面轮廓与人耳特征相结合的人耳检测与识别

为实现人耳的自动检测与识别,提出了结合侧面轮廓特征、人耳统计特征以及人耳与侧面轮廓的位置特征进行人耳检测与识别的方法。该方法分为离线的训练阶段和在线的检测与识别阶段。在离线阶段,通过训练得到一个综合特征向量,包括人脸侧面轮廓特征、人耳统计特征以及人耳相对于侧面轮廓的位置特征。在线的检测与识别过程分为两步：第1步是用侧面人脸轮廓进行粗检测,第2步是用人耳的统计特征和相对于侧面轮廓的位置特征进行精确定位和识别,即在定位的同时实现人耳的识别。实验结果表明,上述方法具有速度快、效率高和鲁棒性好的特点。     

Simultaneous localization of multiple unknown CSMA-based wireless sensor network nodes using a mobile robot with a directional antenna

We use a single mobile robot equipped with a directional antenna to simultaneously localize unknown carrier sensing multiple access (CSMA)-based wireless sensor network nodes. We assume the robot can only sense radio transmissions at the physical layer. The robot does not know network configuration such as size and protocol. We formulate this new localization problem and propose a particle filter-based localization approach. We combine a CSMA model and a directional antenna model using multiple particle filters. The CSMA model provides network configuration data while the directional antenna model provides inputs for particle filters to update. Based on the particle distribution, we propose a robot motion planning algorithm that assists the robot to efficiently traverse the field to search radio source. The final localization scheme consists of two algorithms: a sensing algorithms that runs in O(n) time for n particles and a motion planning algorithm that runs in O(nl) time for l radio sources. We have implemented the algorithm, and the results show that the algorithms are capable of localizing unknown networked radio sources effectively and robustly.     

Angle-of-arrival localization based on antenna arrays for wireless sensor networks

Among the large number of contributions concerning the localization techniques for wireless sensor networks (WSNs), there is still no simple, energy and cost efficient solution suitable in outdoor scenarios. In this paper, a technique based on antenna arrays and angle-of-arrival (AoA) measurements is carefully discussed. While the AoA algorithms are rarely considered for WSNs due to the large dimensions of directional antennas, some system configurations are investigated that can be easily incorporated in pocket-size wireless devices.A heuristic weighting function that enables decreasing the location errors is introduced. Also, the detailed performance analysis of the presented system is provided. The localization accuracy is validated through realistic Monte-Carlo simulations that take into account the specificity of propagation conditions in WSNs as well as the radio noise effects. Finally, trade-offs between the accuracy, localization time and the number of anchors in a network are addressed.     

A VLSI-Based Model of Azimuthal Echolocation in the Big Brown Bat

The azimuthal localization of objects by echolocating bats is based on the difference of echo intensity received at the two ears, known as the interaural level difference (ILD). Mimicking the neural computation of ILD in bats, we have constructed a spike-based VLSI model of the lateral superior olive (LSO) that can successfully produce direction-dependent responses. This simple algorithm, while studied in the acoustic domain, is applicable to any localization based on direction-dependent signal attenuation differences.     

Learning‐based Nonlinear Model Predictive Control to Improve Vision‐based Mobile Robot Path Tracking

This paper presents a Learning‐based Nonlinear Model Predictive Control (LB‐NMPC) algorithm to achieve high‐performance path tracking in challenging off‐road terrain through learning. The LB‐NMPC algorithm uses a simple a priori vehicle model and a learned disturbance model. Disturbances are modeled as a Gaussian process (GP) as a function of system state, input, and other relevant variables. The GP is updated based on experience collected during previous trials. Localization for the controller is provided by an onboard, vision‐based mapping and navigation system enabling operation in large‐scale, GPS‐denied environments. The paper presents experimental results including over 3 km of travel by three significantly different robot platforms with masses ranging from 50 to 600 kg and at speeds ranging from 0.35 to 1.2 m/s (associated video at http://tiny.cc/RoverLearnsDisturbances ). Planned speeds are generated by a novel experience‐based speed scheduler that balances overall travel time, path‐tracking errors, and localization reliability. The results show that the controller can start from a generic a priori vehicle model and subsequently learn to reduce vehicle‐ and trajectory‐specific path‐tracking errors based on experience.     

对深度学习中目标定位不确定度评定的讨论

得益于深度学习技术的快速发展,高准确率的目标自动定位得以实现,这为各领域的智能化转型提供了极大的助力。然而,尽管大多数情况下基于深度学习的目标定位方法都能够获得较为精确的输出,但一些误差较大的定位结果还是难以避免。正因为缺少规范的不确定度评定,所以那些误差较大的定位结果难以被有效地消除,进而影响了基于深度学习的目标定位方法的工程化应用。从符合计量规范的测量不确定度入手,讨论了当前深度学习中目标定位技术评价指标的意义和不足,并提出了对规范化目标定位技术不确定度评定的建议。     

On the interaction between localization and location verification for wireless sensor networks

Secure wireless sensor networks (WSNs) must be able to associate a set of reported data with a valid location. Many algorithms exist for the localization service that determines a WSN node’s location, and current research is developing for location verification, where the network must determine whether or not a node’s claimed location is valid (or invalid). However, the interaction of these two services creates another challenge, since there is no method to distinguish between benign errors, e.g., errors that are inherent to the localization technique, and malicious errors, e.g., errors due to a node’s deceptive location report. In this paper, we study the problem of inherent localization errors and their impact on the location verification service. We propose a localization and location verification (LLV) server model, and define categories of LLV schemes for discrete and continuous resolution. We then designate two metrics to measure the impact of inherent localization errors—the probability of verification (for the discrete location verification schemes) and the CDF of the deviation distance (for the continuous location verification schemes)—to analyze the performance of each LLV category. Numerical results show that a proper tuning mechanism is needed to tolerate even small inherited estimation errors, otherwise the location verification can result in the rejection of almost all nodes. In addition, we propose several location verification feedback (LV-FEED) algorithms to improve the localization accuracy. Analysis of these algorithms shows that a significant improvement in localization accuracy can be accomplished in a few iterations of executing the location verification feedback schemes.     

Modeling of the incudo-malleolar joint within a biomechanical model of the human ear

Under large quasi-static loads, the incudo-malleolar joint (IM joint), connecting the malleus and the incus, is highly mobile. It can be classified as a mechanical filter decoupling large quasi-static motions while transferring small dynamic excitations. To investigate the influence of the behavior of the IM joint, a detailed simulation model of the IM-complex is created. Mathematical modeling of the IM joint behavior under quasi-static excitation requires adequate modeling of the mechanics of the diarthrodial joint. Therefore, the geometry of the articular surfaces, the ligaments, as well as their viscoelastic properties have to be included in the model. The contact of the articular surfaces is implemented using a penalty based contact formulation utilizing the geometric information obtained from micro computer tomography (micro-CT) scans. The ligaments of the joint capsule are modeled by distributing force elements along the joint capsule, with the position and orientation derived from the micro-CT scans. It is shown that the effects which were observed in measurements on human temporal bones are described adequately by the model, if the contact of the articular surfaces and the preload of the viscoelastic fibers are taken into account in the simulation model. In the following, the detailed model is implemented in an elastic multibody system of the entire ear. The model allows the study of different quasi-static load cases of the ossicles, such as it occurs in the reconstruction of the middle ear and form the basis for future simulative studies of sound transmission in natural or reconstructed ears.     

A hemispherical–directional reflectance model as a tool for understanding image distinctions between cultivated and uncultivated bare surfaces

This paper discusses a model to predict the normalized hemispherical–directional reflectance function for soil or rocky surfaces of a given roughness under conditions of outdoor illumination. These surfaces are simulated by geometrical shapes similar to beads merging into each other, characterized by three parameters. In addition, the shape of the surface is characterized by the directivity factor D_R, expressing the differences between the maximum and the minimum deviations of its height, calculated along all possible directions. The surface is illuminated by a hemispherical light source created by a number of point sources of given light intensities. The light energy is scattered from the surface, in accordance the quasi-Lambertian function. The distribution of the surface reflectance, as viewed from all the possible directions, can be described for all the possible illumination conditions expressed by the solar zenith and the horizontal angles for a given hemisphere light distribution of a definite optical thickness. This represents the hemispherical–directional reflectance distribution function, HDRDF, of the surface. The HDRDF function is normalized to the nadir viewpoint and visualized for a given illumination condition. The model assumes that the HDRDF of a surface contains information about the directivity of the surface shape, as described by the directivity factor of the surface hemispherical–directional reflectance function D_HDRDF. This factor, expressing the asymmetry of the HDRDF with respect to the solar principal plane (SPP), is strongly correlated with the D_R. The use of both factors, the D_R and D_HDRDF, enables us to understand the distinctions between soil surface images with height irregularities of directional character that create a furrow microrelief, and irregularities spread non-directly, randomly, depending on whether the soil has been cultivated or not. The model was tested on directional reflectance data measured in the visible, the near and the middle infrared spectra for cultivated surface with furrows, as well as for three uncultivated desert loess and rocky surfaces situated in Israel.     

Directional control-response relationships for mining equipment

A variety of directional control-response relationships are currently found in mining equipment. Two experiments were conducted in a virtual environment to determine optimal direction control-response relationships in a wide variety of circumstances. Direction errors were measured as a function of control orientation (horizontal or vertical), location (left, front, right) and directional control-response relationships. The results confirm that the principles of consistent direction and visual field compatibility are applicable to the majority of situations. An exception is that fewer direction errors were observed when an upward movement of a horizontal lever or movement of a vertical lever away from the participants caused extension (lengthening) of the controlled device, regardless of whether the direction of movement of the control is consistent with the direction in which the extension occurs. Further, both the control of slew by horizontally oriented controls and the control of device movements in a frontal plane by the perpendicular movements of vertical levers were associated with relatively high rates of directional errors, regardless of the directional control-response relationship, and these situations should be avoided.

Statement of Relevance:The results are particularly applicable to the design of mining equipment such as drilling and bolting machines, and have been incorporated into MDG35.1 Guideline for bolting & drilling plant in mines (Industry & Investment NSW, 2010). The results are also relevant to the design of any equipment where vertical or horizontal levers are used to control the movement of equipment appendages, e.g. cranes mounted to mobile equipment and the like.     

移动机器人扩展卡尔曼滤波定位与传感器误差建模

针对里程计在定位过程中存在累积误差的问题,建立了一种通用的移动机器人里程计误差模型,对里程计误差进行实时反馈补偿.在利用激光雷达进行环境特征提取过程中,根据激光雷达原始数据存在的误差,建立了激光雷达的观测误差模型,并根据环境特征和机器人的相对位置关系,建立了移动机器人观测模型.最后,结合里程计和激光雷达误差模型,利用扩展卡尔曼滤波(EKF)实现了基于环境特征跟踪的移动机器人定位.实验结果验证了里程计和激光雷达误差模型的引入,在增加较短定位时间的情况下,可以有效地提高移动机器人的定位精度.     

基于支持向量机的人耳识别系统研究

介绍了人耳识别的优势以及识别处理过程,然后采用不变矩方法对人耳图像进行特征提取,获得7个不变矩特征向量。重点利用支持向量机算法进行60只人耳图像的分类与识别,达到了100％正确分类率和95％的正确识别率,证明了支持向量机在人耳识别技术中应用的可行性。     

基于随机漂移粒子群算法的WSNs节点定位

提出了随机漂移粒子群优化（RDPSO）算法,并将该算法应用于接收信号强度指示（RSSI）定位算法中,以降低由RSSI测距产生的定位误差.在仿真实验中,分别比较了基于RDPSO和PSO的RSSI定位算法.实验结果表明：RDPSO算法是在优化性能上优于PSO算法,有效提高了节点定位精度,证明该方法收敛速度快,稳定性能好,精度高,适用于WSNs节点定位问题.