Cooperative research in underwater robot mission-level programming methodologies

Programming autonomous vehicles to accomplish complex missions is a complicated task for which the development of control architectures is of prime importance. The goal of this paper is to describe the accomplishments of both French and American teams within a cooperative research program focused on the development of high-level control of semi-autonomous underwater vehicles. In particular, two different mission-programming methodologies are examined in the context of the requirements of a generic, reactive and complex underwater mission. The French team uses a combination of the ESTEREL synchronous programming language and the PIRRAT real-time control library to implement a methodology derived from the ORCCAD programming system. The approach taken by the American team builds a trilevel hybrid architecture using the CONTROLSHELL real-time software development environment. The details of each methodology are highlighted through the presentation of the high-level programs designed by each team using their approach to control an underwater robot to perform a multiphased underwater mission. The utility of both programming methodologies was verified through the successful completion of those missions in experimental demonstrations by the French VORTEX and American OTTER autonomous underwater vehicles.     

基于逆模型的混合驱动水下滑翔机垂直面控制

混合驱动水下滑翔机（Hybrid-driven underwater gliders ,简称HDUGs)是集无人自治水下机器人（Automomous Underwater Vehicles ,简称 AUVs）和水下滑翔机（Autonomous Underwater Gliders,简称 AUGs）于一体的新型水下机器人。由于HDUGs是非线性、强耦合,且受到海流、结构不确定等因素的影响,为了克服这些问题,针对混合驱动水下机器人工作在混合模式下,对其垂直面提出了一种基于逆模型和滑模控制的非线性控制方法,该方法将原始系统解耦为两个单入单出的线性系统,仿真结果证明了该方法具有良好的控制性能,而且对外界扰动具有一定的鲁棒性。     

Introduction to the special issue on Advances in intelligent nonlinear control for robotic systems

In the last two decades, robotic systems have achieved wide applications in every aspect of human society, including industrial manufacturing, automotive production, medical devices, and social lives. With the     

Development of autonomous underwater vehicles in Japan

In the hope of expanding underwater observation and research, the Institute of Industrial Science (IIS) at the University of Tokyo started extensive R&D on autonomous underwater vehicle (AUV) in 1984. IIS has constructed nine vehicles, including three ocean-going vehicles, one lake survey vehicle and various testbed vehicles. The R-One Robot is equipped with a closed-cycle diesel engine system and it successfully completed a 12-h operation of long-range autonomous diving in the Pacific Ocean in 1998. Utilizing the testbed robots, many intelligent systems, especially those for underwater vision systems, have been developed. The success of these AUVs at the IIS has led to the establishment of the 'Underwater Technology Research Center' which opened on 1 April 1999. This new center also plans to collaborate both nationally and internationally with other facilities for further R&D of AUVs and other new underwater observation technologies.     

Coordinated Motion and Force Control of Multi-Limbed Robotic Systems

This analytic and experimental study proposes a control algorithm for coordinated position and force control for autonomous multi-limbed mobile robotic systems. The technique is called Coordinated Jacobian Transpose Control (CJTC). Such position/force control algorithms will be required if future robotic systems are to operate effectively in unstructured environments. Generalized Control Variables (GCVs), express in a consistent and coordinated manner the desired behavior of the forces exerted by the multi-limbed robot on the environment and a system's motions. The effectiveness of this algorithm is demonstrated in simulation and laboratory experiments on a climbing system.     

Design and Control of Autonomous Underwater Robots: A Survey

During the 1990s, numerous worldwide research and development activities have occurred in underwater robotics, especially in the area of autonomous underwater vehicles (AUVs). As the ocean attracts great attention on environmental issues and resources as well as scientific and military tasks, the need for and use of underwater robotic systems has become more apparent. Great efforts have been made in developing AUVs to overcome challenging scientific and engineering problems caused by the unstructured and hazardous ocean environment. In the 1990s, about 30 new AUVs have been built worldwide. With the development of new materials, advanced computing and sensory technology, as well as theoretical advancements, R&D activities in the AUV community have increased. However, this is just the beginning for more advanced, yet practical and reliable AUVs. This paper surveys some key areas in current state-of-the-art underwater robotic technologies. It is by no means a complete survey but provides key references for future development. The new millennium will bring advancements in technology that will enable the development of more practical, reliable AUVs.     

混合驱动水下滑翔器主从互转式应急控制技术研究

水下滑翔器是一种长续航新型水下机器人,利用其高效的驱动方式能够航行数月,因而相比其他无人水下自主航行器,滑翔器控制系统的可靠性显得尤为关键。根据水下滑翔器长续航的工作需求,结合其分布式控制系统的架构形式,设计了一种主从互转式应急控制技术。通过CPU互监控以及建立公共存储区等手段,实现了控制器异常情况下的非复位式热切换,保证了滑翔器重要动作部件的正常运行。试验结果表明,利用主从互转式控制方式,可以极大的减小了控制系统中主CPU宕机对滑翔器自主运行的影响,增加水下滑翔器的安全性能。     

Experiments in the coordinated control of an underwater arm/vehicle system

The addition of manipulators to small autonomous underwater vehicles (AUVs) can pose significant control challenges due to hydrodynamic interactions between the arm and the vehicle. Experiments conducted at the Monterey Bay Aquarium Research Institute (MBARI) using the OTTER vehicle have shown that dynamical interactions between an arm and a vehicle can be very significant. For the experiments reported in this paper, a single-link arm was mounted on OTTER. Tests showed that for 90-degree, two-second repetitive slews of the arm, the vehicle would move as much as 18 degrees in roll and 14 degrees in yaw when no vehicle control was applied.Using a new, highly accurate model of the arm/vehicle hydrodynamic interaction forces, which was developed as part of this research, a coordinated arm/vehicle control strategy was implemented. Under this model-based approach, interaction forces acting on the vehicle due to arm motion were predicted and fed into the vehicle controller. Using this method, station-keeping capability was greatly enhanced. Errors at the manipulator end point were reduced by over a factor of six when compared to results when no control was applied to the vehicle and by a factor of 2.5 when compared to results from a standard independent arm and vehicle feedback control approach. Using the coordinated-control strategy, arm end-point settling times were reduced by a factor three when compared to those obtained with arm and vehicle feedback control alone. These dramatic performance improvements were obtained with only a five-percent increase in total applied thrust.     

Cognitive neuroscience and robotics: Advancements and future research directions

In recent years, brain-based technologies that capitalise on human abilities to facilitate human–system/robot interactions have been actively explored, especially in brain robotics. Brain–computer interfaces, as applications of this conception, have set a path to convert neural activities recorded by sensors from the human scalp via electroencephalography into valid commands for robot control and task execution. Thanks to the advancement of sensor technologies, non-invasive and invasive sensor headsets have been designed and developed to achieve stable recording of brainwave signals. However, robust and accurate extraction and interpretation of brain signals in brain robotics are critical to reliable task-oriented and opportunistic applications such as brainwave-controlled robotic interactions. In response to this need, pervasive technologies and advanced analytical approaches to translating and merging critical brain functions, behaviours, tasks, and environmental information have been a focus in brain-controlled robotic applications. These methods are composed of signal processing, feature extraction, representation of neural activities, command conversion and robot control. Artificial intelligence algorithms, especially deep learning, are used for the classification, recognition, and identification of patterns and intent underlying brainwaves as a form of electroencephalography. Within the context, this paper provides a comprehensive review of the past and the current status at the intersection of robotics, neuroscience, and artificial intelligence and highlights future research directions.     

面向北京2022年冬奥会水下火炬传递的新型机器人

面向北京2022年冬奥会水下火炬传递应用需求,设计水下变结构机器人和两栖机器人,并提出水下火炬传递控制方法。克服机械臂（含火炬）运动和野外流场的复合扰动是火炬传递控制的关键问题,尤其是手持燃烧火炬的机械臂对浮游模式水下机器人的影响更加显著。针对以上问题,本文提出一种基于自适应控制策略的水下火炬传递控制方法,在线辨识静力学和流场水动力参数,预先补偿控制扰动,实现水下机器人的高精度姿态控制、位置控制。最终,在北京2022年冬奥会上成功完成奥运史上首次机器人间水下火炬接力。     

Wearable Robots for Human Underwater Movement Ability Enhancement: A Survey

Underwater robot technology has shown impressive results in applications such as underwater resource detection. For underwater applications that require extremely high flexibility, robots cannot replace skills that require human dexterity yet, and thus humans are often required to directly perform most underwater operations. Wearable robots (exoskeletons) have shown outstanding results in enhancing human movement on land. They are expected to have great potential to enhance human underwater movement. The purpose of this survey is to analyze the state-of-the-art of underwater exoskeletons for human enhancement, and the applications focused on movement assistance while excluding underwater robotic devices that help to keep the temperature and pressure in the range that people can withstand. This work discusses the challenges of existing exoskeletons for human underwater movement assistance, which mainly includes human underwater motion intention perception, underwater exoskeleton modeling and human-cooperative control. Future research should focus on developing novel wearable robotic structures for underwater motion assistance, exploiting advanced sensors and fusion algorithms for human underwater motion intention perception, building up a dynamic model of underwater exoskeletons and exploring human-in-the-loop control for them.      

Problems of creating intelligent autonomous robotic underwater vehicles and their application

Basic scientific and applied tasks to be accomplished by autonomous robotic underwater vehicles are considered, and distinctive features of their control system are analyzed. Some unsolved fundamental problems in this subject are formulated. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 100–110, September–October 2007.     

A fail-safe tele-autonomous robotic system for nuclear facilities

A fail-safe tele-autonomous robotic system is proposed for use in advanced nuclear reprocessing facilities. The design exploits the technologies developed for space telerobotics. The target system consists of a graphical user interface for an operator to execute robotic tasks, hand controllers for teleoperation, a three-dimensional graphical simulator, and robot control software to drive both the graphical simulation and dual six degree-of-freedom robots to perform tasks using autonomous, teleoperated, and shared control modes. A preliminary design for a safety monitoring system for fail-safe operations is also described.     

空间机器人控制系统硬件仿真平台的研究

建立了空间机器人控制系统的硬件仿真平台。研究了空间机器人基于手眼视觉的控制问题,建立了系统关键部件的模拟设备。仿真平台由中央控制器、关节模拟器、手眼模拟器、动力学/运动学仿真计算机和三维动画显示计算机组成。基于该平台,对空间机器人控制特性和仿真过程中的延时环节进行了研究。系统自主捕获仿真试验结果表明,所采用的运动控制算法能够稳定收敛于目标,仿真平台能够较好地完成对实际机器人系统控制过程的模拟测试及系统控制算法的验证。     

Maneuverability modeling and trajectory tracking for fish robot

This study develops a 6-DOF mathematical model for a robotic fish that considers surge, sway, heave, roll, pitch, and yaw. The model considers the conditions of a fish swimming in ocean current perturbations similar to the ocean current perturbations of the slender-body autonomous underwater vehicles. For swimming and turning behaviors, a nonlinear, dynamic, carangiform locomotion model is derived by using a planar four-link model. A 2-DOF barycenter mechanism is proposed to provide body stabilization and to serve as an actuating device for active control design. A barycenter control scheme is developed to change the center of gravity of the robot fish body by moving balancing masses along two axes. The projected torque on x and y axes propel pitch and roll angles to the desired settings. A Stabilizing controller, fish-tail mechanism, rigid body dynamics, and kinematics are incorporated to enable the fish robot to move in three dimensional space. Simulation results have demonstrated maneuverability and control system performance of the developed controller which is proposed to conduct path tracking of the robot fish as it swims under current perturbations.     

Development of a real-time control architecture for a semi-autonomous underwater vehicle for intervention missions

The need for autonomous underwater vehicles (AUVs) for intervention missions becomes greater as they can perform underwater tasks requiring physical contacts with the underwater environment, such as underwater plug-in/plug-out, construction and repair, cable streaming, mine hunting, munitions retrieval, and scientific sampling. This paper describes a semi-autonomous underwater vehicle for intervention missions that has multiple on-board CPUs, redundant sensors and actuators, on-board power source and a robotic manipulator for dextrous underwater performance. Such a complex robotic vehicle system requires advanced control software architecture for on-board intelligence with a wide range of sensors and actuators to carry out required missions. In this paper, AUV control architectures are reviewed and a sensor data bus based control architecture (SDBCA) is presented. SDBCA is a modified hierarchical architecture that offers good controllability and stability while sensor data bus increases flexibility of system design, making it possible to have a prompt response from high-level control with respect to low-level sensor data. The overall sensor input mechanism of SDBCA becomes similar to the sensor input mechanism of subsumption architecture.     

Dynamics and Noncollocated Model‐Free Position Control for a Space Robot with Multi‐Link Flexible Manipulators

In this paper, both the dynamics and noncollocated model‐free position control (NMPC) for a space robot with multi‐link flexible manipulators are developed. Using assumed modes approach to describe the flexible deformation, the dynamic model of the flexible space robotic system is derived with Lagrangian method to represent the system dynamic behaviors. Based on Lyapunov's direct method, the robust model‐free position control with noncollocated feedback is designed for position regulation of the space robot and vibration suppression of the flexible manipulators. The closed‐loop stability of the space robotic system can be guaranteed and the guideline of choosing noncollocated feedback is analyzed. The proposed control is easily implementable for flexible space robot with both uncertain complicated dynamic model and unknown system parameters, and all the control signals can be measured by sensors directly or obtained by a backward difference algorithm. Numerical simulations on a two‐link flexible space robot are provided to demonstrate the effectiveness of the proposed control.     

机器人卫星地面实验平台全局视觉系统

机器人卫星地面实验平台是研制机器人卫星的重要手段。本文针对所开发的机器人卫星地面实验平台，设计了全局视觉，完成机器人卫星姿态分析、目标和障碍物的识别与定位。     

Infiltrating the zebrafish swarm: design,implementation and experimental tests of a miniature robotic fish lure for fish–robot interaction studies

Robotic fish are nowadays developed for various types of research, such as bio-inspiredrobotics, biomimetics and animal behavior studies. In the context of our research on the social interactions of the zebrafish Danio Rerio, we developed a miniature robotic fish lure for direct underwater interaction with the living fish. This remotely controlled and waterproof device has a total length of 7.5 cm with the same size ratio as zebrafish and is able to beat its tail with different frequencies and amplitudes, while following the group of living animals using a mobile robot moving outside water that is coupled with the robotic lure using magnets. The robotic lure is also equipped with a rechargeable battery and can be used autonomously underwater for experiments of up to 1 h. We performed experiments with the robot moving inside an aquarium with living fish to analyze its impact on the zebrafish behavior. We found that the beating rate of the tail increased the attractiveness of the lure among the zebrafish shoal. We also demonstrated that the lure could influence a collective decision of the zebrafish shoal, the swimming direction, when moving with a constant linear speed inside a circular corridor. This new robotic fish design and the experimental results are promising for the field of fish–robot interaction.     

基于深度强化学习与多参数域随机化的水下机械手自适应抓取研究

以水下机械手自主作业的应用需求为背景,针对水下机械手动力学参数时变、工作环境复杂、传感器限制、控制精度低等问题,基于强化学习与多参数域随机化理论提出一个具有通用性的水下机械手作业框架。首先,建立基本的机器人强化学习控制系统,然后采用多参数域随机化方法增强强化学习训练策略的稳定性与策略迁移效果,包括机械手动力学参数、水动力参数、状态空间与动作空间的噪声和延时等;最后,将训练的策略分别迁移到一个新的机器人仿真环境与一款真实的工作级水下机械手上进行实验。大量实验验证了本文所提方法的有效性,为未来真实海域自主作业奠定了基础。