Co-axial depth sensor with an extended depth range for AR/VR applications

Background Depth sensor is an essential element in virtual and augmented reality devices to digitalize users'environment in real time.The current popular technologies include the stereo,structured light,and Time-of-Flight(ToF).The stereo and structured light method require a baseline separation between multiple sensors for depth sensing,and both suffer from a limited measurement range.The ToF depth sensors have the largest depth range but the lowest depth map resolution.To overcome these problems,we propose a co-axial depth map sensor which is potentially more compact and cost-effective than conventional structured light depth cameras.Meanwhile,it can extend the depth range while maintaining a high depth map resolution.Also,it provides a high-resolution 2 D image along with the 3 D depth map.Methods This depth sensor is constructed with a projection path and an imaging path.Those two paths are combined by a beamsplitter for a co-axial design.In the projection path,a cylindrical lens is inserted to add extra power in one direction which creates an astigmatic pattern.For depth measurement,the astigmatic pattern is projected onto the test scene,and then the depth information can be calculated from the contrast change of the reflected pattern image in two orthogonal directions.To extend the depth measurement range,we use an electronically focus tunable lens at the system stop and tune the power to implement an extended depth range without compromising depth resolution.Results In the depth measurement simulation,we project a resolution target onto a white screen which is moving along the optical axis and then tune the focus tunable lens power for three depth measurement subranges,namely,near,middle and far.In each sub-range,as the test screen moves away from the depth sensor,the horizontal contrast keeps increasing while the vertical contrast keeps decreasing in the reflected image.Therefore,the depth information can be obtained by computing the contrast ratio between features in orthogonal directions.Conclusions The proposed depth map sensor could implement depth measurement for an extended depth range with a co-axial design.

A Depth Sensor Based on Transient Property of Liquid Crystal Lens

The property of maintaining the lens state of the liquid crystal(LC)lens during the switching between positive and negative lens states is made use of in the fast acquirement of multi-focus images without magnification change.A depth from focus(DFF)pipeline that can generate a low-error depth map and an all-in-focus image is proposed.The depth of the scene is then obtained via DFF pipeline from the captured images.The depth sensor proposed in this paper has the advantages of simple structure,low cost,and long service life.

Fast tool to evaluate 3D movements of the foot-ankle complex using multi-view depth sensors

Movement disorders of the human foot-ankle complex are a common occurrence,owing to the altered joint mechanics during foot-ground interactions.Diagnostics of such movement disorders will require quantitative tools to evaluate in-vivo foot motions,in particular to the multi-segment/joint foot kinematics(MSFK),during gait.Unfortunately,current MSFK analysis largely rely on conventional technologies,such as skin-marker based motion capturing,video fluoroscopy and dynamic 3D scanning,being extremely time-consuming and costly.In this work,a novel movement tracking method,named the point-cloud foot analysis(PFA),was implemented with multi-view depth sensors,to allow fast evaluations of 3D motions of the foot-ankle complex during gait.Quantitative analysis obtained by the PFA methods and their accuracy relative to the conventional MSFK analysis methods were evaluated.The 3D surface reconstructions of the foot-ankle complex were achieved with a RMSE less than 2 mm.It was proven to be feasible to track multi-segment foot motions in both healthy and diseased subjects during walking conditions,with the processing time decreased from more than 4-6 h to less than 6 min for the entire flow of the contact phase analysis.The PFA method can be useful for fast evaluations of the movement disorders of the foot-ankle complex in diagnostics and design of therapeutic interventions and rehabilitation programs for clinical applications.

Calculation of Skin Depths and Eddy-Current Power Losses for Magnetic Position Sensors

We present a theoretic model to calculate skin depths and eddy-current power losses for a magnetic position sensor. Eddy-current, arised from the operation of an alternating-current excitation, induces secondary currents and fields between magnetic material and magnetic position sensor. In this paper, a magnetic position sensor system is simplified to be an outer-winding coil along the axial direction of a low carbon steel bar. The analytical model is derived from basic field and circuit theory considering a linear approximation for a nonlinear permeability. Thus the skin depths and eddy-current power losses from the model in eddy-current modeling techniques at various frequencies of an excited current source can be calculated. The proposed configuration is capable of predicting the skin depths and eddy-current power losses for a magnetic position sensor and has a consistence with experiments.

深度与形貌检测的仿生磁致伸缩触觉传感器设计及实验测试

物体表面形貌深度信息对于智能机器人检测物体表面特征、人机交互具有重要意义。受动物毛发感知机理启发,设计了一种新型仿生磁致伸缩触觉传感器单元及阵列;基于逆磁致伸缩效应、欧拉-伯努利梁理论和胡克定律,推导了深度检测的输出电压模型。仿真研究确定了最佳偏置磁场和阵列间距,实验测试了传感器单元在静态和动态下的输出特性,在0.05~4.8 mm深度检测范围内,灵敏度为185.72 mV/mm,响应时间和恢复时间分别为31 ms和43 ms,且具有良好的重复性,传感器阵列中单元之间输出电压的耦合影响不超过2.4%。将传感器单元及阵列安装在机械手上,选择合适的滑动速度滑过不同物体表面时,根据输出电压波形精确测量各种深度和形貌,结果表明该传感器单元和阵列可为深度与形貌检测提供参考。

免耕播种机播深智能控制系统设计

免耕播种机作为免耕播种技术的核心装备,播种深度的精准控制直接影响作物的生长发育。为了进一步提高免耕播种机智能控制系统的稳定性,构建免耕播种机播深自动控制系统,系统阐述其工作原理与流程,并对关键控制模块及设备进行设计与选型。系统测试试验表明,该系统通过充分利用先进的传感器和算法技术,系统响应时间在0.12~0.18 s之间,能够根据不同作物和土壤条件,自动调整播种深度,并取得了良好的播种效果和产量表现。

基于激光雷达与相机融合的树干检测方法

针对传统传感器在树干检测中的局限性和单一性,提出一种基于激光雷达与相机融合的树干检测方法.首先,利用深度图对激光雷达点云进行处理,实现地面点云去除以及树干点云聚类,并在聚类中设置横、纵向自适应阈值,去除聚类中墙体、杂草、树叶等多余信息;然后,利用YOLOv3算法对相机图像进行分析,基于树干特征实现目标识别并返回检测框与类别信息;最后,基于交并比方法(IoU)对2种传感器的检测结果进行融合,识别树干并返回其三维信息与位置信息.以无人割草机为载体开展场地测试,实验结果表明:融合算法的树干检测准确率在93.1%左右,树干定位横、纵向平均误差分别为0.075 m和0.078 m,能够满足无人割草机的树干检测要求,为智能农机的环境感知提供了一种新的方法.

基于播种单体限深臂压力和角度的播深智能控制系统

为了提高农作物播种深度的稳定性和一致性,进而提高农作物的产量,设计一套以限深臂对限深块的作用力和限深臂摆动角度为监测对象获取播深信息,以电动推杆为执行元件调节单体上下摆幅的基于力反馈式播深智能调节系统。通过对限深臂、四连杆处进行力学分析,确定了压力传感器和电动推杆的量程。针对电动推杆工作中存在误差的问题,采用Mamdani模糊算法建立智能调节模型,对电动推杆的控制进行优化。静态试验表明:在控制系统中添加Mamdani模糊控制算法,误差峰值的校正达到75.6%,播种深度的控制误差降低了60%。

消磁站水下磁传感器定位方法

采用消磁站海底平面磁传感器阵列进行测量是获取舰艇磁场的主要途径,水下磁传感器位置误差是影响舰艇磁场测量的主要因素。针对该问题,将磁场与深度测量数据相融合,提出一种基于磁场梯度优化的消磁站水下磁传感器定位方法。将通电螺线管线圈等效成磁偶极子,通过磁传感器位置偏差区域x和y方向的平均磁场梯度优化确定线圈的两组磁源移动位置,结合深度测量数据分别建立方程组构造目标函数,并采用动态学习策略多群体粒子群算法进行优化求解,从而实现消磁站水下磁传感器的高精度定位。在系统分析和评估深度传感器精度、环境磁噪声等影响规律的基础上,开展位置校正数值模拟和物理缩比模型实验。实验结果表明,该方法可有效地解决消磁站水下磁传感器的定位问题,定位误差小于0.1 m,能够满足舰艇磁场的测量要求。

基于Phyphox的气垫导轨上阻尼振动的研究

传统的阻尼振动实验中,人们需要靠肉眼观测,用电子秒表记录半衰期,才能求出对数减缩等一系列关键数据.然而,肉眼观测和电子秒表记录必然带来较大的偶然误差.本实验中我们利用Phyphox深度传感器对整个阻尼振动过程进行测量,可以直接呈现振动物体的位移与时间关系图像,进而得到每个周期的振幅和半衰期的数据,该方法在一定程度上提高了实验精度.

基于深度传感器的多视角点云配准研究

为了解决大尺寸对称物体在多视角配准过程中出现的误匹配点对和累计误差问题,提出了一种基于深度传感器的多视角点云配准算法。首先,使用深度传感器获取目标物体不同视角下的多片点云并进行预处理,对物体单侧相邻点云采用超四点快速鲁棒匹配算法(Super 4-points congruent sets,Super4PCS)进行粗配准,利用改进的点到平面ICP算法去除误匹配点对并进行精配准,之后将左右两部分的点云拼接,从而获取完整的三维点云模型。最后,针对多视角配准出现的累计误差问题,提出了一种全局优化方法从而减少累计误差。实验结果证明所提方法可以精准地完成多视角点云配准,获得准确的三维点云模型。

融合深度调整和自适应转发的水声网络机会路由

针对水声传感器网络路由过程中的空洞问题和数据传输中能效低下的问题,该文提出了融合深度调整和自适应转发的水声网络机会路由(OR-DAAF)。针对路由空洞,区别于传统绕路策略,OR-DAAF提出一种基于拓扑控制的空洞恢复模式算法—利用剩余能量对空洞节点分级,先后调整空洞节点到新的深度以克服路由空洞,恢复网络联通。针对数据传输中的能效低下问题,OR-DAAF提出了转发区域划分机制,通过转发区域的选择自适应转发面积以抑制冗余包,并提出基于加权推进距离,能量和链路质量的多跳多目标路由决策指标,综合考虑区域能量,链路质量和推进距离实现能效平衡。实验数据表明,相比DVOR协议,OR-DAAF的包投递率和生命周期分别提高10%和48.7%,端到端时延减少22%。

应对不规则物体局部温变的柔性阵列压力传感系统

针对柔性压力传感器阵列在形状不规则又局部温变物体表面测量压力时传感量输出漂移的问题,提出了一种采用红外相机与深度相机的非接触式获取柔性压力传感器阵列温度信息与深度信息的补偿手段。采用拟合法建立不同压力下柔性压力传感器阵列传感单元弯曲应变特性与温敏特性的拟合函数,结果表明经弯曲应变、温度联合补偿后,柔性传感器阵列64个传感单元输出阻值的相对误差最大值从85.48%降低到9.23%,补偿后有59个传感单元相对误差小于0.5%,满足本系统精度要求。

特高海拔寒区隧道温度场分布规律研究

为解决高寒高海拔地区运营隧道的冻害问题,在某单洞双向隧道4个断面的不同位置处布设了大量温度传感器进行现场温度监测,分析研究了特高海拔寒区隧道围岩、衬砌在不同位置处的温度场分布规律以及围岩冻深情况。结果表明:隧道温度随季节呈周期性变化,距洞口10 m处冻害最为严重;隧道衬砌温度与隧道纵向深度呈负相关,围岩温度与隧道径向深度呈正相关关系;在距隧道洞口越近的最不利断面处,拱顶温度高于拱腰和拱脚;距洞口10 m的拱脚处冻深最大,隧道冻深影响范围为0 m~250 m。研究结果可为寒区隧道施工和保温防冻提供依据和指导。

Enhanced Autonomous Exploration and Mapping of an Unknown Environment with the Fusion of Dual RGB-D Sensors

The autonomous exploration and mapping of an unknown environment is useful in a wide range of applications and thus holds great significance. Existing methods mostly use range sensors to generate twodimensional (2D) grid maps. Red/green/blue-depth (RGB-D) sensors provide both color and depth information on the environment, thereby enabling the generation of a three-dimensional (3D) point cloud map that is intuitive for human perception. In this paper, we present a systematic approach with dual RGB-D sensors to achieve the autonomous exploration and mapping of an unknown indoor environment. With the synchronized and processed RGB-D data, location points were generated and a 3D point cloud map and 2D grid map were incrementally built. Next, the exploration was modeled as a partially observable Markov decision process. Partial map simulation and global frontier search methods were combined for autonomous exploration, and dynamic action constraints were utilized in motion control. In this way, the local optimum can be avoided and the exploration efficacy can be ensured. Experiments with single connected and multi-branched regions demonstrated the high robustness, efficiency, and superiority of the developed system and methods.

Retrieval of Snow Depth on Sea Ice in the Arctic Using the FengYun-3B Microwave Radiation Imager

Snow on sea ice is a sensitive indicator of climate change because it plays an important role regulating surface and near surface air temperatures. Given its high albedo and low thermal conductivity, snow cover is considered a key reason for amplified warming in polar regions. This study focuses on retrieving snow depth on sea ice from brightness temperatures recorded by the Microwave Radiation Imager(MWRI) on board the FengYun(FY)-3 B satellite. After cross calibration with the Advanced Microwave Scanning Radiometer-EOS(AMSR-E) Level 2 A data from January 1 to May 31, 2011, MWRI brightness temperatures were used to calculate sea ice concentrations based on the Arctic Radiation and Turbulence Interaction Study Sea Ice(ASI) algorithm. Snow depths were derived according to the proportional relationship between snow depth and surface scattering at 18.7 and 36.5 GHz. To eliminate the influence of uncertainties in snow grain sizes and sporadic weather effects, seven-day averaged snow depths were calculated. These results were compared with snow depths from two external data sets, the IceBridge ICDIS4 and AMSR-E Level 3 Sea Ice products. The bias and standard deviation of the differences between the MWRI snow depth and IceBridge data were respectively 1.6 and 3.2 cm for a total of 52 comparisons. Differences between MWRI snow depths and AMSR-E Level 3 products showed biases ranging between-1.01 and-0.58 cm, standard deviations from 3.63 to 4.23 cm, and correlation coefficients from 0.61 to 0.79 for the different months.

Multifunctional disk device for optical switch and temperature sensor

A multifunctional surface plasmon polariton disk device coupled by two metal-insulator-metal（MIM） waveguides is proposed and investigated numerically with finite-difference time-domain simulation. It can be used as optical switch and temperature sensor by filling disk with liquid crystal and ethanol, respectively. The simulation results demonstrate that the transmission characteristics of an optical switch can be manipulated by adjusting the radius of disk and the slit width between disk and MIM waveguides. The transmittance and modulation depth of optical switch at 1550 nm are up to 64.82% and 17.70 d B, respectively. As a temperature sensor, its figure of merit can reach 30.46. In this paper, an optical switch with better efficiency and a temperature sensor with better sensitivity can be achieved.

北京昌平兴寿镇地震监测井不同深度水温变化特征及机理分析

将北京昌平兴寿镇地震监测井同一型号水温传感器分别置于井下400 m、600 m、700m展开对比观测,就水温数据的变化幅度、差分日变差、均方差和同震响应特征进行差异性分析,以揭示井下不同深度处环境扰动信号的强弱及对水温观测效能的影响。分析发现,传感器置于井下600 m,受观测含水层流体渗入影响,水温数据变化平稳,异常信息更易于识别;传感器置于井下400 m、700 m,受到水温梯度值相对大和距离观测含水层顶板过长的影响,水温数据所受扰动信号增强,异常信息被湮没而不易识别。为提高水温观测效能,应结合井孔条件,综合评价水温传感器的有效置深。

A Solution for Scalable Routing in Depth Divisions-Based DUSNs via Adding a Scalable Parameter to Control Depth Clusters: Creating an Energy Efficient and Low Delay NI-Independent Communication Protocol

Due to effectiveness of network layer on general performance of networks, designing routing protocols is very important for lifetime and traffic efficiency in wireless sensor networks. So in this paper, we are going to represent an efficient and scalable version of depth-based routing (DBR) protocol that is limited by depth divisions-policy. In fact the new version is a network information independent routing protocol for acoustic communications. Proposed method by use of depth clustering is able to reduce consumed energy and end-to-end delay in dense underwater sensor networks (DUSNs) and this issue is proved by simulation.

基于Kinect v2低成本动作捕捉系统在步态分析中的开发及应用

近年诸多证据表明基于深度传感器的微软Kinect v2可以进行精准数字化步态分析,从而提高神经系统和运动系统疾病的临床实践水平。本文从基于Kinect v2步态分析研究的步态录制条件、步态参数提取方法、步态分析准确性等方面综述Kinect v2的可靠性及可行性。文献综述提示,虽然受制于硬件及现有算法,Kinect v2在运动学步态参数测量上尚存在较大误差,但依靠其所提取的时-空间步态参数与金标准相比均具有极好的一致性,可以作为简易、低成本的步态记录及数字化分析的工具。因各研究所使用配套软件及终端算法不尽相同,未来研究方向应该聚焦于优化算法并建立标准化系统,且需要更大样本量的受试者数据验证该系统作为临床步态分析工具的真正效能。