Acoustic motion estimation and guidance for unmanned underwater vehicles

The problem of navigation, guidance and control of Unmanned Underwater Vehicles (UUVs) is addressed in this paper. A task-function based guidance system and an acoustic motion estimation module have been integrated with a conventional UUV autopilot within a two-layered hierarchical architecture for closed-loop control. The design of the guidance system is based on suitable Lyapunov functions that can handle the different manoeuvres involved in approaching a target. Range and bearing information provided by a pencil beam profiling sonar are processed by an Extended Kalman Filter based algorithm for motion estimation in a structured environment. The resulting Navigation Guidance and Control (NGC) system has been tested on Roby2, the UUV testbed developed at the Istituto Automazione Navale of Italy's National Research Council. The experimental set-up as well as modalities and results are discussed.     

Neuro-control of unmanned underwater vehicles

Unmanned underwater vehicles (UUVs) typically operate in uncertain and changing environments. Since the dynamics of UUVs are highly nonlinear and their hydrodynamic coefficients vary with different operating conditions, a high-performance control system of a UUV is needed to have the capacities of learning and adaptation to the variations in the UUV's dynamics. This paper presents the utilization of an adaptive neuro-control scheme as a controller for controlling a UUV in six degrees of freedom. No prior offline training phase and no explicit knowledge of the structure of the vehicle are required, and the proposed scheme exploits the advantages of both neural network control and adaptive control. Asymptotic convergence of the UUV's tracking errors and stability of the presented control system is guaranteed on the basis of the Lyapunov theory. In this paper, neural network architectures based on radial basis functions and multilayer structures have been used to evaluate the performance of the adaptive controller via computer simulation.     

Experimental study on fine motion control of underwater robots

This paper considers thruster dead zones and saturation limits, which are nonlinear elements that complicate fine motion control of underwater robots. If the vehicle is configured with redundant thrusters, the respective dead zones and their surrounding nonlinear regions could be avoided by implementing a null motion solution for the command input of the vehicle. This solution is derived from the vehicle's geometry and is realized before the application of the motion control algorithm. The result is an improvement in system performance exclusive of the implemented controller type. The approach is illustrated through simulation and experiment with an underwater robot, ODIN.     

Active sonar-based bottom-following for unmanned underwater vehicles

The problem of high-precision bottom-following in the proximity of the seabed for open-frame unmanned underwater vehicles (UUVs) is addressed in this paper. The suggested approach consists of the integration of a guidance and control system with an active multi-hypothesis extended Kalman filter, able to estimate the motion of the vehicle with respect to the bottom profile. The guidance module is based on the definition of a suitable Lyapunov function associated with the bottom-following task, while the motion controller is a conventional autopilot, performing autoheading, autodepth, and autospeed. The motion of the vehicle is estimated from range and bearing measurements supplied by a high-frequency pencil-beam profiling sonar. Moreover, a general-purpose sensor-based guidance and control system for advanced UUVs, able to manage active sensing-based guidance and motion estimation modules, is presented. An application of the proposed architecture to execute high-precision bottom-following using Romeo, a prototype UUV, developed by the Robotics Dept. of the Istituto Automazione Navale, is described. Experimental results of tests, conducted in a high-diving pool with the vehicle equipped with a sonar profiler, are presented.     

Multi-Sensory Motion Estimation and Control of an Autonomous Quadrotor

In this paper, a fully autonomous quadrotor in a heterogeneous air–ground multi-robot system is established only using minimal on-board sensors: a monocular camera and inertial measurement units (IMUs). Efficient pose and motion estimation is proposed and optimized. A continuous-discrete extended Kalman filter is applied, in which the high-frequency IMU data drive the prediction, while the estimates are corrected by the accurate and steady vision data. A high-frequency fusion at 100 Hz is achieved. Moreover, time delay analysis and data synchronizations are conducted to further improve the pose/motion estimation of the quadrotor. The complete on-board implementation of sensor data processing and control algorithms reduces the influence of data transfer time delay, enables autonomous task accomplishment and extends the work space. Higher pose estimation accuracy and smaller control errors compared to the standard works are achieved in real-time hovering and tracking experiments.     

Real-time optical SLAM-based mosaicking for unmanned underwater vehicles

This article discusses the possibility of building in real-time a mosaic of the seafloor relying on a simultaneous localization and mapping (SLAM) framework. The goal is to provide an unmanned underwater vehicle with a relatively rough visual map of the seafloor to support basic navigation and context awareness. To achieve that goal, an accurate estimation of the location of the visual landmarks and, in particular, the correct data association when a visual landmark is re-visited by the vehicle are the crucial points. Instead of using a global mosaic, this work uses the combination of a set of local mosaics constructed in the vicinity of the SLAM visual landmarks. The contributions of this article are mainly the use of SURF features, the local mosaics approach and the real-time capability. The use of SURF features allows eliminating false positives in the data association of SLAM visual landmarks. The local mosaics approach is an effective way of correcting the effects of the drift on the mosaic in real time. The main contribution is the real-time capability as it will be seen. The algorithm was tested using a batch of experimental data in typical operating conditions and the results prove the effectiveness of the approach.     

Fault detection of actuator faults in unmanned underwater vehicles

A fault-diagnostic system for unmanned underwater vehicles has been designed and tested in real operating conditions. Actuator faults have been considered, relying on approximate models of the vehicles’ dynamics. Fault detection and diagnosis is accomplished by evaluating any significant change in the behaviour of the vehicle. This task is performed by a bank of estimators: a filter is implemented for each actuator fault type, including the no-fault case. The estimators used are extended Kalman filters (EKF), due to the presence of nonlinearities in the dynamic models. Experimental results are reported, to demonstrate the effectiveness of the proposed approach.     

On the identification of non-linear models of unmanned underwater vehicles

This documentation presents a comparison between two identification methods for the off-line identification of non-linear models of unmanned underwater vehicles (UUVs), one based on the minimization of the acceleration prediction error (direct method) and another one based on the minimization of the velocity one step prediction error (integral method). The direct method has already been used in UUV's identification (IFAC Conference CAMs’ 2001, Control Application in Marine Systems, Glasgow, Scotland, UK, 2001). Our new proposal, the integral method, can be applied to a quite general class of non-linear multivariable models and is characterized by an excellent numerical performance. Both methods are compared through their application to the identification of the dynamic model of URIS UUV. Results suggest that better models can be obtained using the proposed method (integral method).     

Automatic terminal guidance for small fixed-wing unmanned aerial vehicles

The research presented in this article focuses on expanding and deepening the prior research of a low-cost terminal guidance system in a previous paper entitled “Design, implementation and verification of a low-cost terminal guidance system for small fixed-wing UAVs.” An automatic terminal guidance workflow is specially designed for an individual in a small fixed-wing unmanned aerial vehicle (SUAV) swarm. The extended work around the proposed workflow primarily involves upgrading onboard hardware modules to improve sensor accuracy and environmental adaptability, the imaging performance of the seeker, as well as the computational capability of the image processor, applying object detection to replace the human-in-the-loop function and adopting the integral proportional guidance law in the vertical direction to reduce the required overload and obtain a larger impact angle. Furthermore, we conducted several field tests on two types of SUAV against a stationary target on the ground in a field scenario. The experiments have generated valuable onboard image data and SUAV status information, all of which are aligned in the time domain. The only remaining data sets that support the findings of this study are available from the corresponding author. Our study into automatic terminal guidance has yielded a solution of the automatic strap-down monocular terminal guidance problem of individual SUAVs. The field trials of a single SUAV demonstrate the robustness and efficiency of the proposed automatic terminal guidance methodology and lays a foundation for the future SUAVs' cooperative attack test.     

Exact non-linear Bayesian parameter estimation for autonomous compliant motion

This paper presents theoretical and experimental results for the estimation of large position and orientation inaccuracies during force-controlled compliant motion. This is a significant improvement over previous results. The estimation is based on position, velocity and force measurements. For large position and orientation inaccuracies, the non-linear estimation problem is not satisfactorily solved by existing Kalman filters. Therefore, a new Bayesian estimator is derived. The filter is derived independently of our application and is valid for static systems (parameter estimation) with any kind of non-linear measurement equation subject to Gaussian measurement uncertainty and for a limited class of dynamic systems. Experimental results for the estimation of the inaccurately known positions and orientations of contacting objects during autonomous compliant motion are presented.     

欠驱动无人水下航行器三维轨迹跟踪的反步控制

针对欠驱动无人水下航行器(underactuated unmanned underwater vehicles,UUVs)三维轨迹跟踪控制问题,本文有别于传统反步法中基于视线法设计姿态角误差变量的思路,提出了一种定义虚拟速度误差变量的反步控制器设计方法,能够有效避免传统反步法控制律设计时存在的奇异值问题,简化了传统反步法复杂的计算过程;设计了欠驱动UUV的三维轨迹跟踪控制器,给出了系统的误差方程,基于Lyapunov稳定性理论证明了系统在定常外界扰动下的鲁棒性和稳定性;仿真结果表明本文提出的UUV三维轨迹跟踪反步控制方法收敛、有效,能够实现欠驱动UUV对时变三维轨迹的精确跟踪控制.     

Underwater guidance of distributed autonomous underwater vehicles using one leader

Consider the case where autonomous underwater vehicles (AUVs) are deployed to monitor a 3D underwater environment. This paper tackles the problem of guiding all AUVs to the destination while not colliding with a priori unknown 3D obstacles. Suppose that among all AUVs, only the leader AUV has an ability of locating itself, while accessing a destination location. A follower, an AUV that is not a leader, has no sensors for locating itself. Every follower can only measure the relative position of its neighbor AUVs utilizing its sonar sensors. Our paper addresses distributed controls, so that multiple followers track the leader while preserving communication connectivity. We design controls, so that all AUVs reach the destination safely, while maintaining connectivity in cluttered 3D environments. To the best of our knowledge, our article is novel in developing 3D underwater guidance controls, so that all AUVs equipped with sonar sensors are guided to reach a destination in a priori unknown cluttered environments. MATLAB simulations are used to validate the proposed guidance scheme in underwater environments with many obstacles.     

Image-based predictive display for high d.o.f. uncalibrated tele-manipulation using affine and intensity subspace models

The addition of immediate but estimated visual feedback, called predictive display, improves tele-manipulaton performance when the real video feedback is delayed. Current systems typically rely upon a previously calibrated camera and manipulator. We present a method where the motor-visual calibration is estimated on-line from motor commands and returned video images only. Predicted visual feedback is presented in two forms. As soon as a basic model has been estimated, a wire frame drawing of the predicted current pose is overlaid on the delayed video feedback. After some time when a rich model has been estimated, predicted intensity images are synthesized and these replace the delayed real video. In an intermediate situation where blurry synthesized images can be computed, the wireframe is overlaid on the synthesized images to show precisely the pose of the object. Experiments with a Utah/MIT robot hand and PUMA robot arm are shown.     

Design of a vision-guided microrobotic colonoscopy system

In this paper presents a novel design of a microrobotic colonoscopy (MRC) system. The proposed microrobotic colonoscope is an autonomous vision-guided device, which is designed to navigate inside a human colon for the purpose of observation, analysis and diagnosis. It is developed to alleviate the shortcomings in the existing manual colonoscopy procedure, which is generally cumbersome and tedious for the colonoscopist and painful to the patients. The MRC system is divided into three areas, i.e. design of the microrobotic device, path planning and guidance, and offboard control system. A novel design of the microrobot is presented which utilizes a pneumatic mechanism to achieve locomotion and steering. A new concept of clamping the colon wall based on passive vacuum devices is suggested. General mathematical analysis governing the differential steering of the robotic tip is also described. The path planning of the microrobot is carried out based on the sensory fusion utilizing the quantitative parameters derived from the captured images and the tactile sensors. An off-board control system to control the directional movements of the microrobot is explained. The proposed colonoscopy system was tested with physical models and animal colons, and the experimental observations are presented.     

A survey on tracking control of unmanned underwater vehicles: Experiments-based approach

This paper aims to provide a review of the conceptual design and theoretical framework of the main control schemes proposed in the literature for unmanned underwater vehicles (UUVs). Additionally, the objective of the paper is not only to present an overview of the recent control architectures validated on UUVs but also to give detailed experimental-based comparative studies of the proposed control schemes. To this end, the main control schemes, including proportional–integral–derivative (PID) based, sliding mode control (SMC) based, adaptive based, observation-based, model predictive control (MPC) based, combined control techniques, are revisited in order to consolidate the principal efforts made in the last two decades by the automatic control community in the field. Besides implementing some key tracking control schemes from the classification mentioned above on Leonard UUV, several real-time experimental scenarios are tested, under different operating conditions, to evaluate and compare the efficiency of the selected tracking control schemes. Furthermore, we point out potential investigation gaps and future research trends at the end of this survey.     

自主水下航行器的回坞导引和入坞控制算法

针对军事侦察和海洋环境监测领域中对自主水下航行器（AUV）水下自主回收能力的需求,研究了AUV自主回收过程中回坞和入坞的导引和控制问题。将水下自主回收过程分为回坞导引和入坞控制两个连续的阶段,其中回坞阶段采用经典的视线（LOS）导引法,使AUV到达回收器正前方的回坞航路点;入坞阶段则采用非线性横向跟踪控制方法,使AUV精确跟踪沿回收器中轴线的入坞直线航路航行并最终进入回收器。采用REMUS AUV的模型参数对水下回收进行了仿真研究,结果表明该方法是有效的,具有良好的工程应用前景。     

Energy-based guidance of an underactuated unmanned underwater vehicle on a helical trajectory

This paper presents a motion control system for guidance of an underactuated Unmanned Underwater Vehicle (UUV) on a helical trajectory. The control strategy is developed using Port-Hamiltonian theory and interconnection and damping assignment passivity-based control. Using energy routing, the trajectory of a virtual fully actuated plant is guided onto a vector field. A tracking controller is then used that commands the underactuated plant to follow the velocity of the virtual plant. An integral control is inserted between the two control layers, which adds robustness and disturbance rejection to the design.     

Visual Odometry for a Hopping Rover on an Asteroid Surface using Multiple Monocular Cameras

Visual odometry refers to the use of images to estimate the motion of a mobile robot. Real-time systems have already been demonstrated for terrestrial robotic vehicles, while a near real-time system has been successfully used on the Mars Exploration Rovers for planetary exploration. In this paper, we adapt this method to estimate the motion of a hopping rover on an asteroid surface. Due to the limited stereo depth resolution and the continuous rotational motion on a hopping rover, we propose to use a system of multiple monocular cameras. We describe how the scale of the scene observed by different cameras without overlapping views can be transferred between the cameras, allowing us to reconstruct a single continuous trajectory from multiple image sequences. We describe the implementation of our algorithm and its performance under simulation using rendered images.     

The bio-inspired model based hybrid sliding-mode tracking control for unmanned underwater vehicles

In this paper a novel hybrid control strategy is developed for trajectory tracking control of unmanned underwater vehicle (UUV). The proposed hybrid control strategy consists of two subsystems: a virtual velocity controller and a sliding-mode controller. The tracking errors are shown to asymptotically converge to zero by Lyapunov stability theory using the new approach, whereas in the traditional backstepping method, speed jump occurs if the tracking error changes suddenly. The biologically inspired model is designed to smooth the virtual velocity controller output, avoid speed jumps of underwater vehicles and satisfy the thruster control constraint. The effectiveness and efficiency of the proposed control strategy are demonstrated through simulations and comparison studies.