An inertial navigation system for small autonomous underwater vehicles

A Small AUV Navigation System (SANS) is being developed at the Naval Postgraduate School. The SANS is an integrated GPS/inertial navigation system composed of low-cost, small-size components. It is designed to demonstrate the feasibility of using a low-cost inertial measurement unit to navigate between intermittent GPS fixes. This paper reports recent improvements to the SANS hardware, latest testing results and development of an asynchronous Kalman filter for improved position estimation.     

Tightly coupled long baseline/ultra-short baseline integrated navigation system

This paper proposes a novel integrated navigation filter based on a combined long baseline/ultra short baseline acoustic positioning system with application to underwater vehicles. With a tightly coupled structure, the position, linear velocity, attitude, and rate gyro bias are estimated, considering the full nonlinear system dynamics without resorting to any algebraic inversion or linearisation techniques. The resulting solution ensures convergence of the estimation error to zero for all initial conditions, exponentially fast. Finally, it is shown, under simulation environment, that the filter achieves very good performance in the presence of sensor noise.     

An open-source navigation system for micro aerial vehicles

This paper presents an open-source indoor navigation system for quadrotor micro aerial vehicles (MAVs), implemented in the ROS framework. The system requires a minimal set of sensors including a planar laser range-finder and an inertial measurement unit. We address the issues of autonomous control, state estimation, path-planning, and teleoperation, and provide interfaces that allow the system to seamlessly integrate with existing ROS navigation tools for 2D SLAM and 3D mapping. All components run in real time onboard the MAV, with state estimation and control operating at 1 kHz. A major focus in our work is modularity and abstraction, allowing the system to be both flexible and hardware-independent. All the software and hardware components which we have developed, as well as documentation and test data, are available online.     

Low computational-complexity algorithms for vision-aided inertial navigation of micro aerial vehicles

This paper presents low computational-complexity methods for micro-aerial-vehicle localization in GPS-denied environments. All the presented algorithms rely only on the data provided by a single onboard camera and an Inertial Measurement Unit (IMU). This paper deals with outlier rejection and relative-pose estimation. Regarding outlier rejection, we describe two methods. The former only requires the observation of a single feature in the scene and the knowledge of the angular rates from an IMU, under the assumption that the local camera motion lies in a plane perpendicular to the gravity vector. The latter requires the observation of at least two features, but it relaxes the hypothesis on the vehicle motion, being therefore suitable to tackle the outlier detection problem in the case of a 6DoF motion. We show also that if the camera is rigidly attached to the vehicle, motion priors from the IMU can be exploited to discard wrong estimations in the framework of a 2-point-RANSAC-based approach. Thanks to their inherent efficiency, the proposed methods are very suitable for resource-constrained systems. Regarding the pose estimation problem, we introduce a simple algorithm that computes the vehicle pose from the observation of three point features in a single camera image, once that the roll and pitch angles are estimated from IMU measurements. The proposed algorithm is based on the minimization of a cost function. The proposed method is very simple in terms of computational cost and, therefore, very suitable for real-time implementation. All the proposed methods are evaluated on both synthetic and real data.     

自适应P值映射的惯性/天文角度组合导航算法

惯性/天文角度组合导航在应用于高动态飞行器时,动态飞行环境变更会导致星光角度观测量发生程度不等的偏差,使得常规组合滤波方法误差显著增大.为此,本文提出了基于P值映射的观测质量自主评估及自适应滤波方法,并应用于惯性/天文角度组合导航系统.该方法根据历年可见导航星情况分解冗余观测子集,再由P值度量其含有观测量偏差的显著性水平.在此基础上,通过遍历每颗导航星所隶属子集得到其观测量质量值,最后对惯性/天文角度组合滤波增益进行自适应调节.仿真结果表明,本文方法能够实现天文高度角观测质量的自主在线评估,有效提高星光观测质量下降情况下惯性/天文角度组合导航的精度和适应性.     

SPINS: A structure priors aided inertial navigation system

We propose a navigation system combining sensor-aided inertial navigation and prior-map-based localization to improve the stability and accuracy of robot localization in structure-rich environments. Specifically, we adopt point, line, and plane features in the navigation system to enhance the feature richness in low-texture environments and improve the localization reliability. We additionally integrate structure prior information of the environments to constrain the localization drifts and improve the accuracy. The prior information is called structure priors and parameterized as low-dimensional relative distances/angles between different geometric primitives. The localization is formulated as a graph-based optimization problem that contains sliding-window-based variables and factors, including Inertial Measurement Unit, heterogeneous features, and structure priors. A limited number of structure priors are selected based on the information gain to alleviate the computation burden. Finally, the proposed framework is extensively tested on synthetic data, public data sets, and, more importantly, on the real Unmanned Aerial Vehicle flight data obtained from both indoor and outdoor inspection tasks. The results show that the proposed scheme can effectively improve the accuracy and robustness of localization for autonomous robots in civilian applications.     

An optical navigation sensor for micro aerial vehicles

This paper describes a catadioptric microsensor for multidirectional imaging and 3D egomotion computation. Inspired by the wide viewing angle of insects’ compound eyes, we show how to extract egomotion information from spherical images. We demonstrate how reflective surfaces can be used for building a compact, multidirectional eye that enables to collect video from 60% of the full sphere. Some experiments performed on synthetic images (using a ray-tracing environment) are presented to validate the concept. We have called the resulting imaging system SICONS (SIngle Chip Optical Navigation Sensor). SICONS is intended for application in micro unmanned aerial vehicles (micro-UAVs) to develop their perceptive, visual guidance and motive abilities to move within the real world in the same way an insect does.     

PRIAMOS: An experimental platform for reflexive navigation

In this paper the new mobile robot system PRIAMOS is presented. The system emphasizes on fast navigation algorithms. In a (partially) unknown or changing environment fast perception and reaction is necessary for efficient task execution. Low level mapping and planning modules are used to span the period until higher control layers have enough time to react. The first part of this paper briefly describes the mechanical and technical construction of PRIAMOS. After an explanation of the software architecture the solutions for motion control and reflexive navigation, as realized in PRIAMOS, are given.     

舰船捷联惯导系统粗对准方法研究

提出适合于舰船系泊、锚泊状态下的捷联惯性导航系统惯性凝固粗对准方法。在惯性凝固坐标系和惯性坐标系上对重力向量分别进行积分,并利用重力向量随地球旋转在惯性空间的方向变化信息,粗略计算初始捷联姿态矩阵。该方法通过积分抵消掉舰船线性位移引入的干扰加速度,同时,避免了舰船姿态摇摆引入的干扰角速度。仿真分析表明：在舰船系泊、锚泊状态下,惯性凝固粗对准方法比较传统算法优势明显。     

Sigma-Point直接式卡尔曼滤波惯性组合导航算法

基于西格玛点采样加权的方法,以姿态、速度和位置等9个导航参数为状态向量,以卫星导航系统的速度和位置组成6维观测向量,构建直接式卡尔曼滤波器,融惯性导航系统求解和状态估计的过程为一体,直接描述系统导航参数动态过程.仿真结果验证了惯性组合导航Sigma-Point直接式滤波方法的有效性,表明该非线性直接式滤波方法可提高惯性组合导航系统的导航精度和对飞机、导弹等载体非线性机动过程的适应性.     

Adaptive speed tracking control for autonomous land vehicles in all‐terrain navigation: An experimental study

This paper develops a nonparametric controller with an internal model control (IMC) structure for the longitudinal speed tracking control of autonomous land vehicles by designing a proportional and internal model control (IMC) cascade (P‐IMC) controller. An IMC architecture is employed in the inner control loop by establishing a nonparametric longitudinal dynamical model, whereas a P controller is designed for the outer control loop. An approach for estimating the terrain effects and compensating for the model errors is also introduced. The differences from other nonparametric controllers are discussed, and the stability of the P‐IMC controller is analyzed and validated experimentally. The P‐IMC controller is compared with the SpAM+PI to illustrate its advantages. The experimental results of autonomous all‐terrain driving show the effectiveness of the P‐IMC controller.     

井下捷联惯导系统导航数据处理滤波分析

针对现有煤矿井下定位技术误差较大、准确性不足的问题,引入了捷联惯导系统对煤矿井下人员和设备进行精确定位导航。为进一步提高捷联惯导系统的定位精度,提出了采用扩展卡尔曼滤波和采样卡尔曼滤波对系统数据进行滤波的算法,分析了扩展卡尔曼滤波和采样卡尔曼滤波的滤波原理,并对算法公式以及滤波效果进行了仿真分析。仿真结果表明,在假设井下噪声为高斯白噪声的前提下,采样卡尔曼滤波抖动性较小,曲线更为平滑,即滤波后的数据更加接近于真实数据,能够更准确地反映出坐标信息,且误差基本控制在允许的范围之内,具有较好的滤波效果。     

舰载武器惯导系统传递对准仿真验证的研究

针对传统船用惯导系统采用理想运动状态对传递对准方案进行仿真验证的问题,提出了引入舰船空间运动模型的传递对准仿真验证方法。通过舰船空间运动模型提供接近真实运动环境的空间运动参数,并实现了空间运动信息至惯性敏感信息的正确转换,给出了各模块的空间变换算法转换流程。"速度+姿态"子惯导传递对准模块的仿真精度优于0.05°,证明了仿真验证系统变换算法的正确性。该研究设计为开展其它领域的传递对准仿真验证提供了有效的参考依据。     

辅助机载惯导快速对准的光学测量装置

机载惯导系统在地面静基座对准需要较长的对准时间,严重影响飞机的出动速度。为辅助机载惯导进行快速、精确的对准,设计了一种通过对飞机上的标志点进行激光测距从而获取航向信息的装置。描述了该测量装置的构成和基本原理,推导了利用该装置测量飞机航向角的测量公式,给出了标定和测量的完整流程。通过仿真实验对测量仪测距误差、俯仰及方位测角误差进行了分析,证明该装置能够满足惯导快速对准的精度需求。     

Cooperative formation control of autonomous underwater vehicles: An overview

Formation control is a cooperative control concept in which multiple autonomous underwater mobile robots are deployed for a group motion and/or control mission. This paper presents a brief review on various cooperative search and formation control strategies for multiple autonomous underwater vehicles (AUV) based on literature reported till date. Various cooperative and formation control schemes for collecting huge amount of data based on formation regulation control and formation tracking control are discussed. To address the challenge of detecting AUV failure in the fleet, communication issues, collision and obstacle avoidance are also taken into attention. Stability analysis of the feasible formation is also presented. This paper may be intended to serve as a convenient reference for the further research on formation control of multiple underwater mobile robots.     

A virtual environment-based system for the navigation of underwater robots

Efficient teleoperation of underwater robot requires clear 3D visual information of the robot's spatial location and its surrounding environment. However, the performance of existing telepresence systems is far from satisfactory. In this paper, we present our virtual telepresence system for assisting tele-operation of an underwater robot. This virtual environment-based telepresence system transforms robot sensor data into 3D synthetic visual information of the workplace based on its geometrical model. It provides the operators with a full perception of the robot's spatial location. In addition, we propose a robot safety domain to overcome the robot's location offset in the virtual environment caused by its sensor errors. The software design of the system and how a safety domain can be used to overcome robot location offset in virtual environment will be examined. Experimental tests and its result analysis will also be presented in this paper.     

基于雷达–扫描器/惯性导航系统的微小型无人机室内组合导航

本文提出一种基于雷达–扫描器/惯性导航系统(radar-scanner/INS)的微小型无人机室内导航方法.为提高算法的实时性,采用基于扩展卡尔曼滤波(EKF)的DC同步定位与构图技术(SLAM)实现定位和构图;在更新状态值的扫描匹配过程中提出启发性逻辑来筛选激光雷达数据,以提高算法对无人机因姿态和高度变化而引起的轮廓地图波动的抗干扰性;在特征匹配的过程中选取合理的地图轮廓特征,并利用扫描匹配的结果和特征匹配的传递性提出了精度较高的引导配对,以提高特征配对在三维环境下的准确性;最后,将DC SLAM与惯性导航系统进行基于EKF的组合滤波,给出无人机的全状态估计.通过与GPS/INS组合导航对比以及室内飞行验证,本文提出的方法能够满足无人机飞行控制对导航实时性和精度的要求.     

Visual SLAM for underwater vehicles: A survey

Underwater scene is highly unstructured, full of various noise interferences. Moreover, GPS information is not available in the underwater environment, which thus brings huge challenges to the navigation of autonomous underwater vehicle. As an autonomous navigation technology, Simultaneous Localization and Mapping (SLAM) can deliver reliable localization to vehicles in unknown environment and generate models about their surrounding environment. With the development and utilization of marine and other underwater resources, underwater SLAM has become a hot research topic. By focusing on underwater visual SLAM, this paper reviews the basic theories and research progress regarding underwater visual SLAM modules, such as sensors, visual odometry, state optimization and loop closure detection, discusses the challenges faced by underwater visual SLAM, and shares the prospects of underwater visual SLAM. It is found that the traditional underwater visual SLAM based on filtering methods is gradually developing towards optimization-based methods. Underwater visual SLAM presents a diversified trend, and various new methods have emerged. This paper aims to provide researchers and practitioners with a better understanding of the current status and development trend of underwater visual SLAM, while offering help for collecting underwater vehicles intelligence.