Designing a Computer Vision System for Underwater Robotic Interventions

This thesis deals with the challenging problem of designing systems able to perceive objects in underwater environments. In the last few decades research activities in robotics have advanced the state of art regarding intervention capabilities of autonomous systems. State of art in fields such as localization and navigation, real time perception and cognition, safe action and manipulation capabilities, applied to ground environments (both indoor and outdoor) has now reached such a readiness level that it allows high level autonomous operations. On the opposite side, the underwater environment remains a very difficult one for autonomous robots. Water influences the mechanical and electrical design of systems, interferes with sensors by limiting their capabilities, heavily impacts on data transmissions, and generally requires systems with low power consumption in order to enable reasonable mission duration. Interest in underwater applications is driven by needs of exploring and intervening in environments in which human capabilities are very limited. Nowadays, most underwater field operations are carried out by manned or remotely operated vehicles, deployed for explorations and limited intervention missions. Manned vehicles, directly on-board controlled, expose human operators to risks related to the stay in field of the mission, within a hostile environment. Remotely Operated Vehicles (ROV) currently represent the most advanced technology for underwater intervention services available on the market. These vehicles can be remotely operated for long time but they need support from an oceanographic vessel with multiple teams of highly specialized pilots. Vehicles equipped with multiple state-of-art sensors and capable to autonomously plan missions have been deployed in the last ten years and exploited as observers for underwater fauna, seabed, ship wrecks, and so on. On the other hand, underwater operations like object recovery and equipment maintenance are still challenging tasks to be conducted without human supervision since they require object perception and localization with much higher accuracy and robustness, to a degree seldom available in Autonomous Underwater Vehicles (AUV). This thesis reports the study, from design to deployment and evaluation, of a general purpose and configurable platform dedicated to stereo-vision perception in underwater environments. Several aspects related to the peculiar environment characteristics have been taken into account during all stages of system design and evaluation: depth of operation and light conditions, together with water turbidity and external weather, heavily impact on perception capabilities. The vision platform proposed in this work is a modular system comprising off-the-shelf components for both the imaging sensors and the computational unit, linked by a high performance ethernet network bus. The adopted design philosophy aims at achieving high flexibility in terms of feasible perception applications, that should not be as limited as in case of a special-purpose and dedicated hardware. Flexibility is required by the variability of underwater environments, with water conditions ranging from clear to turbid, light backscattering varying with daylight and depth, strong color distortion, and other environmental factors. Furthermore, the proposed modular design ensures an easier maintenance and update of the system over time. Performance of the proposed system, in terms of perception capabilities, has been evaluated in several underwater contexts taking advantage of the opportunity offered by the MARIS national project. Design issues like energy power consumption, heat dissipation and network capabilities have been evaluated in different scenarios. Finally, real-world experiments, conducted in multiple and variable underwater contexts, including open sea waters, have led to the collection of several datasets that have been publicly released to the scientific community. The vision system has been integrated in a state of the art AUV equipped with a robotic arm and gripper, and has been exploited in the robot control loop to successfully perform underwater grasping operations.

Underwater acoustic networks: the FP7 UAN project

The EU-funded project UAN - Underwater Acoustic Network aims at conceiving, developing and testing at sea an innovative and operational concept for integrating in a unique communication system submerged, surface and aerial sensors with the objective of protecting off-shore and coastline critical infrastructures. A crucial aspect of the project consisted in the use of autonomous underwater vehicles (AUVs) as mobile nodes in the underwater acoustic communication network. In particular, AUVs have the role of adapting the network geometry to the variation of the acoustic channel. This paper reports on the project concept and vision as well as on the progress of its various development phases. The recent at-sea successes that have been demonstrated within the UAN framework are detailed and results of the final UAN project demonstration, UAN11, held in the May of 2011, are reported. The UAN network was in operation for five continuous days with up to five nodes, of which three of them were mobile nodes. © IFAC.

Field and Service Robotics Results of the 5th International Conference

The 5th International Conference on Field and Service Robotics (FSR05) was held in Port Douglas, Australia, on 29th - 31st July 2005, and brought together the worlds' leading experts in field and service automation. The goal of the conference was to report and encourage the latest research and practical results towards the use of field and service robotics in the community with particular focus on proven technology. The conference provided a forum for researchers, professionals and robot manufacturers to exchange up-to-date technical knowledge and experience. Field robots are robots which operate in outdoor, complex, and dynamic environments. Service robots are those that work closely with humans, with particular applications involving indoor and structured environments. There are a wide range of topics presented in this issue on field and service robots including: Agricultural and Forestry Robotics, Mining and Exploration Robots, Robots for Construction, Security & Defence Robots, Cleaning Robots, Autonomous Underwater Vehicles and Autonomous Flying Robots. This meeting was the fifth in the series and brings FSR back to Australia where it was first held. FSR has been held every 2 years, starting with Canberra 1997, followed by Pittsburgh 1999, Helsinki 2001 and Lake Yamanaka 2003.

Sensor Network Based AUV Localisation

The operation of Autonomous Underwater Vehicles (AUVs) within underwater sensor network fields provides an opportunity to reuse the network infrastructure for long baseline localisation of the AUV. Computationally efficient localisation can be accomplished using off-the-shelf hardware that is comparatively inexpensive and which could already be deployed in the environment for monitoring purposes. This paper describes the development of a particle filter based localisation system which is implemented onboard an AUV in real-time using ranging information obtained from an ad-hoc underwater sensor network. An experimental demonstration of this approach was conducted in a lake with results presented illustrating network communication and localisation performance.

Constrained control design for dynamic positioning of marine vehicles with control allocation

In this paper, we address the control design problem of positioning of over-actuated marine vehicles with control allocation. The proposed design is based on a combined position and velocity loops in a multi-variable anti-windup implementation together with a control allocation mapping. The vehicle modelling is considered with appropriate simplifications related to low-speed manoeuvring hydrodynamics and vehicle symmetry. The control design is considered together with a control allocation mapping. We derive analytical tuning rules based on requirements of closed-loop stability and performance. The anti- windup implementation of the controller is obtained by mapping the actuator-force constraint set into a constraint set for the generalized forces. This approach ensures that actuation capacity is not violated by constraining the generalized control forces; thus, the control allocation is simplified since it can be formulated as an unconstrained problem. The mapping can also be modified on-line based on actuator availability to provide actuator-failure accommodation. We provide a proof of the closed-loop stability and illustrate the performance using simulation scenarios for an open-frame underwater vehicle.

A guide to the deep-water sponges of the Aleutian Island Archipelago

The first dedicated collections of deep-water (>80 m) sponges from the central Aleutian Islands revealed a rich fauna including 28 novel species and geographical range extensions for 53 others. Based on these collections and the published literature, we now confirm the presence of 125 species (or subspecies)of deep-water sponges in the Aleutian Islands. Clearly the deep-water sponge fauna of the Aleutian Islands is extraordinarily rich and largely understudied. Submersible observations revealed that sponges, rather than deep-water corals, are the dominant feature shaping benthic habitats in the region and that they provide important refuge habitat for many species of fish and invertebrates including juvenile rockfish (Sebastes spp.) and king crabs (Lithodes sp). Examination of video footage collected along 127 km of the seafloor further indicate that there are likely hundreds of species still uncollected from the region, and many unknown to science. Furthermore, sponges are extremely fragile and easily damaged by contact with fishing gear. High rates of fishery bycatch clearly indicate a strong interaction between existing fisheries and sponge habitat. Bycatch in fisheries and fisheries-independent surveys can be a major source of information on the location of the sponge fauna, but current monitoring programs are greatly hampered by the inability of deck personnel to identify bycatch. This guide contains detailed species descriptions for 112 sponges collected in Alaska, principally in the central Aleutian Islands. It addresses bycatch identification challenges by providing fisheries observers and scientists with the information necessary to adequately identify sponge fauna. Using that identification data, areas of high abundance can be mapped and the locations of indicator species of vulnerable marine ecosystems can be determined. The guide is also designed for use by scientists making observations of the fauna in situ with submersibles, including remotely operated vehicles and autonomous underwater vehicles.

基于视觉伺服的水下机器人悬停定位

为实现水下机器人的悬停定位,提出一种基于视觉伺服的方法．通过安装在机器人上的摄像机实时摄取特定观察目标的图像,应用基于单目视觉位姿估计方法获取观察目标相对干摄像机的位姿信息,并以此作为反馈构成机器人运动的伺服控制．以本单位的水下机器人控制系统实验研究平台为载体,在实验水池内完成了实验．实验结果表明,在存在外力扰动的情况下机器人可以运动到指定位姿并保持悬停．

非完整自主车基于圆轨迹的道路避障

本文就四轮非完整自主车提出了一种基于圆轨迹的道路避障策略。先将道路上的障碍按照障碍距离自主车的远近划分层次,使一个层次的障碍能在自主车视场中全部出现。然后给出基于圆轨迹的避障算法,即自主车沿由自主车出发位姿和子目标点确定的圆弧轨迹走行。在此之前推导四轮非完整车的运动模型为提出避障策略的基础准备。尽量减小自主车在走行过程中运动状态的改变,基于圆轨迹避障策略能够很好地满足这一要求。最后引入代价函数,给出对于此方法的评价,体现了本方法的优越性。

分散式控制和管理的UUV体系结构模型研究

针对传统的分层式体系结构在UUV 控制系统开发设计、维护和升级过程中所遇到的困难，首先分析了集中式控制和管理方法的不足和原因。在此基础上，借鉴自主计算的思想，提出了分散控制和管理的体系结构。这种方法把系统中每个独立的功能模块都抽象成为具有相同模型的控制基元，称之为“自主基元”，然后通过自主基元层次式、嵌套式的组织，构成完整的系统。分析表明，这种方法能够缩短控制系统的开发周期，也降低了维护和升级的难度。

估计从UUV航行参数的混合坐标系下的EKF算法

在主从式UUV 协作系统中，由于定位和导航的需要，要求尽快估计出从UUV 的航行参数，但通常所用的递推最小二乘（RLS）算法，其初始方位测量对滤波结果影响大且存在收敛速度慢、计算精度低的缺点，难以满足应用需求，而推广卡尔曼滤波（EKF）算法能较好地克服上述问题。在直角坐标系下（CEKF），方位信息与距离信息相互耦合导致初始振荡剧烈，改为混合坐标系（MEKF）后问题得到了极大的改善。最后，通过仿真及现场试验验证了此改进方法的有效性。

水下机器人锁紧释放技术综述

叙述了锁紧释放系统在水下机器人上的应用,说明了锁紧释放装置是控制水下机器人作业的重要手段。分析了天津大学研制的水下机器人解锁释放搭载体和设备、半埋雷打捞装置夹紧爪和美国某型号武器水下发射装置完成预定任务的工作原理和结构特点。归纳总结了水下大型构件锁紧释放系统设计中应着重考虑的问题。讨论了动力源形式的选择和力(矩)裕度分析、支撑与紧固点的选择、锁紧与释放形式的选择和实现、密封技术等四项锁紧释放机构的关键技术。

微型遥控潜水器视频监控系统

介绍了一种微型遥控潜水器视频监控系统,包括硬件装置及基于软件技术的视频数据处理技术。硬件装置完成视频信号的采集、传输、显示。视频数据处理技术解决了视频信号的捕获、存储、画面质量调节等。该系统已经在微型遥控潜水器中应用,效果良好。

主从式UUV群的随从UUV导航

单只水下机器人导航方法存在着各自的缺陷,无法满足低成本UUV群的作业需要。建立由一只具有高精度自主导航能力的主UUV和多只由低成本导航传感器的随从UUV组成的一主多从式UUV群,研究随从UUV导航方法。与前人的极坐标化方法不同,在直角坐标系下对随从UUV导航系统进行了能观性证明。随从UUV通过测距传感器测量自身到主UUV的距离,采用EKF算法进行位置估计,给出了机动航行方案。仿真实验证明了有效性。

反水雷UUV的作战效能模型分析

针对UUV的战术技术性能和使用特点,基于WSEIAC方法建立了反水雷UUV的作战效能基本评估模型,系统地论述了反水雷UUV作战效能的定义、量度和反水雷UUV作战效能基本评估模型及效能评定所涉及的UUV可用性、可信性及作战能力的分析方法。该模型能鲜明反映UUV装备的系统效能的物理本质,并在工程应用上具有简便灵活的特点,对于设计反水雷UUV——一种未来海军必要的新型反水雷装备,具有重要的指导意义。

水下机器人的神经网络自适应控制

研究了水下机器人神经网络直接自适应控制方法,采用Lyapunov稳定性理论,证明了存在有界外界干扰和有界神经网络逼近误差条件下,水下机器人控制系统的跟踪误差一致稳定有界.为了进一步验证该水控制方法的正确性和稳定性,利用水下机器人实验平台进行了动力定位实验、单自由度跟踪实验和水平面跟踪实验等验证实验.