Tracking control has been a vital research topic in robotics. This paper presents a novel hybrid control strategy for an unmanned underwater vehicle (UUV) based on a bioinspired neural dynamics model. An enhanced backstepping kinematic control strategy is first developed to avoid sharp velocity jumps and provides smooth velocity commands relative to conventional methods. Then, a novel sliding mode control is proposed, which is capable of providing smooth and continuous torque commands free from chattering. In comparative studies, the proposed combined hybrid control strategy has ensured control signals smoothness, which is critical in real world applications, especially for an unmanned underwater vehicle that needs to operate in complex underwater environments.
Bioinspired Tapered-Spring Turbulence Sensor for Underwater Flow Detection
Dyson School of Design Engineering, Imperial College London（帝国理工学院伦敦校区设计工程学院）；Imperial College London（帝国理工学院）；Department of Computer Science, University of Aberdeen（阿伯丁大学计算机科学系）
Bioinspired SLAM Approach for Unmanned Surface Vehicle
Department of Electrical Engineering, Federal University of Rio de Janeiro（电气工程系，里约热内卢联邦大学）；Department of Mathematics and Computer Science, Providence College（数学与计算机科学系，普罗维登斯学院）；School of Computing and Information Sciences, Florida International University（计算与信息科学学院，佛罗里达国际大学）
An intelligent control strategy is proposed to eliminate the actuator saturation problem that exists in the trajectory tracking process of unmanned underwater vehicles (UUV). The control strategy consists of two parts: for the kinematic modeling part, a fuzzy logic-refined backstepping control is developed to achieve control velocities within acceptable ranges and errors of small fluctuations; on the basis of the velocities deducted by the improved kinematic control, the sliding mode control (SMC) is introduced in the dynamic modeling to obtain corresponding torques and forces that should be a…
Consensus formation tracking of multiple autonomous underwater vehicles (AUVs) subject to nonlinear and uncertain dynamics is a challenging problem in robotics. To tackle this challenge, a distributed bioinspired sliding mode controller is proposed in this paper. First, the conventional sliding mode controller (SMC) is presented, and the consensus problem is addressed on the basis of graph theory. Next, to tackle the high frequency chattering issue in SMC scheme and meanwhile improve the robustness to the noises, a bioinspired approach is introduced, in which a neural dynamic model is employed…
The motion planning and tracking control techniques of unmanned underwater vehicles (UUV) are fundamentally significant for efficient and robust UUV navigation, which is crucial for underwater rescue, facility maintenance, marine resource exploration, aquatic recreation, etc. Studies on UUV motion planning and tracking control have been growing rapidly worldwide, which are usually sorted into the following topics: task assignment of the multi-UUV system, UUV path planning and UUV trajectory tracking. This paper provides a comprehensive review of conventional and intelligent technologies for mo…
Underwater Motions Analysis and Control of a Coupling-Tiltable Unmanned Aerial-Aquatic Vehicle
Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS)（深圳人工智能与机器人研究院）；The Chinese University of Hong Kong（香港中文大学）；Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）
Yale University（耶鲁大学）；Naval Research Laboratory（美国海军研究实验室）；University of Maryland College Park（马里兰大学帕克分校）；Thomas Jefferson High School for Science and Technology（托马斯·杰斐逊科技高中）
Flapping-fin unmanned underwater vehicle (UUV) propulsion systems provide high maneuverability for naval tasks such as surveillance and terrain exploration. Recent work has explored the use of time-series neural network surrogate models to predict thrust from vehicle design and fin kinematics. We develop a search-based inverse model that leverages a kinematics-to-thrust neural network model for control system design. Our inverse model finds a set of fin kinematics with the multi-objective goal of reaching a target thrust and creating a smooth kinematic transition between flapping cycles. We de…
DIVO: Continuous-time DVL-Inertial-Visual Odometry for Unmanned Underwater Vehicles
Voyis Imaging Inc.（Voyis影像公司）；Natural Sciences and Engineering Research Council of Canada (NSERC)（加拿大自然科学与工程研究理事会（NSERC））；McGill University（麦吉尔大学）；McGill Engineering Doctoral Award (MEDA) Program（麦吉尔大学工程博士奖（MEDA）项目）
Univ. Fed. do Rio Grande – FURG（里奥格兰德联邦大学）；Univ. Fed. de Minas Gerais（米纳斯吉拉斯联邦大学）；AuRos Robotics；Universidade de Campinas（坎皮纳斯大学）
In the last decade, a great effort has been employed in the study of Hybrid Unmanned Aerial Underwater Vehicles, robots that can easily fly and dive into the water with different levels of mechanical adaptation. However, most of this literature is concentrated on physical design, practical issues of construction, and, more recently, low-level control strategies. Little has been done in the context of high-level intelligence, such as motion planning and interactions with the real world. Therefore, we proposed in this paper a trajectory planning approach that allows collision avoidance against u…
USV-AUV Collaboration Framework for Underwater Tasks under Extreme Sea Conditions
Tsinghua University（清华大学）；Tsinghua Shenzhen International Graduate School（清华大学深圳国际研究生院）；Zhejiang University（浙江大学）；College of Information Science & Electronic Engineering（信息科学与电子工程学院）；New Jersey Institute of Technology（新泽西理工学院）
This paper presents a prototype of a low-cost Unmanned Surface Vehicle (USV) that is operated by wave and solar energy which can be used to minimize the cost of ocean data collection. The current prototype is a compact USV, with a length of 1.2m that can be deployed and recovered by two persons. The design includes an electrically operated winch that can be used to retract and lower the underwater unit. Several elements of the design make use of additive manufacturing and inexpensive materials. The vehicle can be controlled using radio frequency (RF) and a satellite communication, through a cu…
Never too Cocky to Cooperate: An FIM and RL-based USV-AUV Collaborative System for Underwater Tasks in Extreme Sea Conditions
Tsinghua Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院，清华大学）；Department of Data and Systems Engineering, The University of Hong Kong（数据与系统工程系，香港大学）；School of Engineering Science, University of Chinese Academy of Sciences（工程科学学院，中国科学院大学）；Department of Data Science, New Jersey Institute of Technology（数据科学系，新泽西理工学院）
Universidad Tecnológica del Uruguay (UTEC)（乌拉圭技术大学）；Centro de Ciências Computacionais (C3) of Universidade Federal do Rio Grande (FURG)（里奥格兰德联邦大学计算科学中心）；Universidade Federal de Santa Maria (UFSM)（圣玛丽亚联邦大学）
Previous works showed that Deep-RL can be applied to perform mapless navigation, including the medium transition of Hybrid Unmanned Aerial Underwater Vehicles (HUAUVs). This paper presents new approaches based on the state-of-the-art actor-critic algorithms to address the navigation and medium transition problems for a HUAUV. We show that a double critic Deep-RL with Recurrent Neural Networks improves the navigation performance of HUAUVs using solely range data and relative localization. Our Deep-RL approaches achieved better navigation and transitioning capabilities with a solid generalizatio…
Oslo Metropolitan University（奥斯陆城市大学）；Norwegian University of Science and Technology（挪威科技大学）
This paper presents preliminary results towards the development of an autonomous ocean observing system using Miniature Underwater Gliders (MUGs) that can operate with the support of Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vessels (USVs) for deployment, recovery, battery charging, and communication relay. The system reduces human intervention to the minimum, revolutionizing the affordability of a broad range of surveillance and data collection operations. The MUGs are equipped with a small Variable Buoyancy System (VBS) composed of a gas filled piston and a linear actuator powered…
ZS-Puffin: Design, Modeling and Implementation of an Unmanned Aerial-Aquatic Vehicle with Amphibious Wings
School of Ocean Engineering and Technology, Sun Yat‐sen University（海洋工程与技术学院，中山大学）；Southern Marine Science and Engineering Guangdong Laboratory（广东海洋工程科学实验室）；Key Laboratory of Comprehensive Observation of Polar Environment (Sun Yat‐sen University)（极地环境综合观测重点实验室（中山大学））；Guangdong Provincial Key Laboratory of Information Technology for Deep Water Acoustics（广东省深水声学信息技术重点实验室）
To eliminate the effect of ocean currents when addressing the optimal path in the underwater environment, an intelligent algorithm designed for the unmanned underwater vehicle (UUV) is proposed in this paper. The algorithm consists of two parts: a neural network-based algorithm that deducts the shortest path and avoids all possible collisions; and an adjusting component that balances off the deviation brought by the effect of ocean currents. The optimization results of the proposed algorithm are presented in detail, and compared with the path planning algorithm that does not consider the effec…
MarineGym: Accelerated Training for Underwater Vehicles with High-Fidelity RL Simulation
The State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University（浙江大学流体动力与机电系统国家重点实验室）；School of Informatics, University of Edinburgh（爱丁堡大学信息学院）；School of Engineering and Physical Sciences, Heriot-Watt University（赫瑞瓦特大学工程与物理科学学院）
Faculty of Information Technology, Monash University, Australia（澳大利亚莫纳什大学信息技术学院）
This paper describes a reflexive multilayered mission planner with a mounted energy efficient local path planner for Unmanned Underwater Vehicle's (UUV) navigation throughout the complex subsea volume in a time-variant semi-dynamic operation network. The UUV routing protocol in Underwater Wireless Sensor Network (UNSW) is generalized with a homogeneous Dynamic Knapsack-Traveler Salesman Problem emerging with an adaptive path planning mechanism to address UUV's long-duration missions on dynamically changing subsea volume. The framework includes a base layer of global path planning, an inner lay…
System Architecture and Communication Infrastructure for the RoboVaaS project
Fraunhofer Center for Maritime Logistics and Service（弗劳恩霍夫海事物流与服务中心）；University of Padova（帕多瓦大学）；Wireless and More srl（Wireless and More有限公司）；Hamburg University of Technology（汉堡工业大学）
Universidade Federal de Santa Maria - UFSM（圣玛丽亚联邦大学）
Since the application of Deep Q-Learning to the continuous action domain in Atari-like games, Deep Reinforcement Learning (Deep-RL) techniques for motion control have been qualitatively enhanced. Nowadays, modern Deep-RL can be successfully applied to solve a wide range of complex decision-making tasks for many types of vehicles. Based on this context, in this paper, we propose the use of Deep-RL to perform autonomous mapless navigation for Hybrid Unmanned Aerial Underwater Vehicles (HUAUVs), robots that can operate in both, air or water media. We developed two approaches, one deterministic an…
Gust Estimation and Rejection with a Disturbance Observer for Proprioceptive Underwater Soft Morphing Wings
Institute of Integrated Micro and Nano Systems, School of Engineering, The University of Edinburgh（集成微纳系统研究所，工程学院，爱丁堡大学）；School of Informatics, The University of Edinburgh（信息学院，爱丁堡大学）
Compressed delayed-information projection for underwater navigation under acoustic measurement latency
Department of Electrical Engineering and Electronics, School of Engineering, University of Liverpool（利物浦大学工程学院电气工程与电子系）；Jiangsu JITRI Tsingunited Intelligent Control Technology Co., Ltd.（江苏集萃清联智控科技有限公司）；School of Computer Science and Informatics, University of Liverpool（利物浦大学计算机科学与信息学院）；ARIES Research Centre, Polytechnic School, Universidad Antonio de Nebrija（安东尼奥·德·内布里哈大学理工学院ARIES研究中心）
Batch Estimation of a Steady, Uniform, Flow-Field from Ground Velocity and Heading Measurements
Department of Mechanical Engineering（机械工程系）；Engineering Science, University of North Carolina at Charlotte（工程科学，北卡罗来纳大学夏洛特分校）；Physical Acoustics Branch, Code 7135, Naval Research Laboratory（声学分支，海军研究实验室）
Autonomous underwater vehicles (AUV) are commonly used in many underwater applications. Recently, the usage of multi-rotor unmanned autonomous vehicles (UAV) for marine applications is receiving more attention in the literature. Usually, both platforms employ an inertial navigation system (INS), and aiding sensors for an accurate navigation solution. In AUV navigation, Doppler velocity log (DVL) is mainly used to aid the INS, while for UAVs, it is common to use global navigation satellite systems (GNSS) receivers. The fusion between the aiding sensor and the INS requires a definition of step s…
Unmanned aerial vehicles (UAVs) have become very popular for many military and civilian applications including in agriculture, construction, mining, environmental monitoring, etc. A desirable feature for UAVs is the ability to navigate and perform tasks autonomously with least human interaction. This is a very challenging problem due to several factors such as the high complexity of UAV applications, operation in harsh environments, limited payload and onboard computing power and highly nonlinear dynamics. The work presented in this report contributes towards the state-of-the-art in UAV contro…
University at Albany, SUNY（纽约州立大学奥尔巴尼分校）；Southern Illinois University（南伊利诺伊大学）
Path planning in dynamic environments is essential to high-risk applications such as unmanned aerial vehicles, self-driving cars, and autonomous underwater vehicles. In this paper, we generate collision-free trajectories for a robot within any given environment with temporal and spatial uncertainties caused due to randomly moving obstacles. We use two Poisson distributions to model the movements of obstacles across the generated trajectory of a robot in both space and time to determine the probability of collision with an obstacle. Measures are taken to avoid an obstacle by intelligently manip…
