Robot missions typically involve a number of desired objectives, such as avoiding collisions, staying connected to other robots, gathering information using sensors and returning to the charging station before the battery runs out. Some of these objectives need to be taken into account at the same time, such as avoiding collisions and staying connected, while others are focused upon during different parts of the executions, such as returning to the charging station and connectivity maintenance.
In this paper, we show how Control Barrier Functions(CBFs) and Behavior Trees(BTs) can be combined in a principled manner to achieve both types of task compositions, with performance guarantees in terms of mission completion. We illustrate our method with a simulated underwater coverage mission.
School of Information Technology, Deakin University（迪肯大学信息技术学院）
This study introduces a connective model of routing -- local path planning for Autonomous Underwater Vehicle (AUV) time efficient maneuver in long-range operations. Assuming the vehicle operating in a turbulent underwater environment, the local path planner produces the water-current resilient shortest paths along the existent nodes in the global route. A re-routing procedure is defined to re-organize the order of nodes in a route and compensate any lost time during the mission. The Firefly Optimization Algorithm (FOA) is conducted by both of the planners to validate the model's performance in…
NemeSys: Toward Online Underwater Exploration with Remote Operator-in-the-loop Adaptive Autonomy
Department of ECE University of Florida Gainesville, FL, USA（电子工程系佛罗里达大学盖恩斯维尔分校）；Department of MAE University of Florida Gainesville, FL, USA（机械与航空航天工程系佛罗里达大学盖恩斯维尔分校）
Expansion of today's underwater scenarios and missions necessitates the requestion for robust decision making of the Autonomous Underwater Vehicle (AUV); hence, design an efficient decision making framework is essential for maximizing the mission productivity in a restricted time. This paper focuses on developing a deliberative conflict-free-task assignment architecture encompassing a Global Route Planner (GRP) and a Local Path Planner (LPP) to provide consistent motion planning encountering both environmental dynamic changes and a priori knowledge of the terrain, so that the AUV is reactively…
Validation of Space Robotics in Underwater Environments via Disturbance Robustness Equivalency
Division of Robotics, Perception and Learning, KTH Royal Institute of Technology（机器人、感知与学习 division，皇家理工学院）；School of Engineering Sciences, KTH Royal Institute of Technology（工程科学学院，皇家理工学院）；Division of Decision and Control Systems, KTH Royal Institute of Technology（决策与控制系统 division，皇家理工学院）；Department of Mechanical and Civil Engineering, California Institute of Technology（机械与土木工程 department，加州理工学院）
Technical University of Delft（代尔夫特理工大学）；University of Oslo（奥斯陆大学）；Vrije Universiteit Amsterdam（阿姆斯特丹自由大学）
Once deployed in the real world, autonomous underwater vehicles (AUVs) are out of reach for human supervision yet need to take decisions to adapt to unstable and unpredictable environments. To facilitate research on self-adaptive AUVs, this paper presents SUAVE, an exemplar for two-layered system-level adaptation of AUVs, which clearly separates the application and self-adaptation concerns. The exemplar focuses on a mission for underwater pipeline inspection by a single AUV, implemented as a ROS2-based system. This mission must be completed while simultaneously accounting for uncertainties suc…
An Autonomous Underwater Vehicle (AUV) needs to acquire a certain degree of autonomy for any particular underwater mission to fulfill the mission objectives successfully and ensure its safety in all stages of the mission in a large scale operating filed. In this paper, a novel combinatorial conflict-free-task assignment strategy consisting an interactive engagement of a local path planner and an adaptive global route planner, is introduced. The method is established upon the heuristic search potency of the Particle Swarm Optimisation (PSO) algorithm to address the discrete nature of routing-ta…
We propose a robust gesture-based communication pipeline for divers to instruct an Autonomous Underwater Vehicle (AUV) to assist them in performing high-risk tasks and helping in case of emergency. A gesture communication language (CADDIAN) is developed, based on consolidated and standardized diver gestures, including an alphabet, syntax and semantics, ensuring a logical consistency. A hierarchical classification approach is introduced for hand gesture recognition based on stereo imagery and multi-descriptor aggregation to specifically cope with underwater image artifacts, e.g. light backscatt…
This paper presents a real-time programming and parameter reconfiguration method for autonomous underwater robots in human-robot collaborative tasks. Using a set of intuitive and meaningful hand gestures, we develop a syntactically simple framework that is computationally more efficient than a complex, grammar-based approach. In the proposed framework, a convolutional neural network is trained to provide accurate hand gesture recognition; subsequently, a finite-state machine-based deterministic model performs efficient gesture-to-instruction mapping, and further improves robustness of the inte…
NATO STO Centre for Maritime Research and Experimentation (CMRE)（北约科技组织海事研究与实验中心）
In this paper we address the mine countermeasures (MCM) search problem for an autonomous underwater vehicle (AUV) surveying the seabed using a side-looking sonar. We propose a coverage path planning method that adapts the AUV track spacing with the objective of collecting better data. We achieve this by shifting the coverage overlap at the tail of the sensor range where the lowest data quality is expected. To assess the algorithm, we collected data from three at-sea experiments. The adaptive survey allowed the AUV to recover from a situation where the sensor range was overestimated and resulte…
College of Science and Engineering, Flinders University（弗林德斯大学科学与工程学院）；Centre for Maritime Engineering, Control and Imaging, Flinders University（弗林德斯大学海事工程、控制与成像中心）；Seattle Children's Research Institute, University of Washington（华盛顿大学西雅图儿童研究所）
This paper presents a hybrid route-path planning model for an Autonomous Underwater Vehicle's task assignment and management while the AUV is operating through the variable littoral waters. Several prioritized tasks distributed in a large scale terrain is defined first; then, considering the limitations over the mission time, vehicle's battery, uncertainty and variability of the underlying operating field, appropriate mission timing and energy management is undertaken. The proposed objective is fulfilled by incorporating a route-planner that is in charge of prioritizing the list of available t…
Flinders University of South Australia（南澳大利亚弗林德斯大学）
An Autonomous Underwater Vehicle (AUV) should carry out complex tasks in a limited time interval. Since existing AUVs have limited battery capacity and restricted endurance, they should autonomously manage mission time and the resources to perform effective persistent deployment in longer missions. Task assignment requires making decisions subject to resource constraints, while tasks are assigned with costs and/or values that are budgeted in advance. Tasks are distributed in a particular operation zone and mapped by a waypoint covered network. Thus, design an efficient routing-task priority as…
Stevens Institute of Technology（史蒂文斯理工学院）；Amazon Robotics（亚马逊机器人）；Exyn Technologies（Exyn科技）；SRI International（斯坦福国际研究院）
We consider the problem of autonomous mobile robot exploration in an unknown environment, taking into account a robot's coverage rate, map uncertainty, and state estimation uncertainty. This paper presents a novel exploration framework for underwater robots operating in cluttered environments, built upon simultaneous localization and mapping (SLAM) with imaging sonar. The proposed system comprises path generation, place recognition forecasting, belief propagation and utility evaluation using a virtual map, which estimates the uncertainty associated with map cells throughout a robot's workspace…
Autonomous Underwater Vehicles (AUVs) are capable of spending long periods of time for carrying out various underwater missions and marine tasks. In this paper, a novel conflict-free motion planning framework is introduced to enhance underwater vehicle's mission performance by completing maximum number of highest priority tasks in a limited time through a large scale waypoint cluttered operating field, and ensuring safe deployment during the mission. The proposed combinatorial route-path planner model takes the advantages of the biogeography-based optimization (BBO) algorithm toward satisfying…
Mapping-Guided Task Discovery and Allocation for Robotic Inspection of Underwater Structures
Department of Mechanical Engineering, University of Washington（机械工程系，华盛顿大学）；Department of Industrial & Systems Engineering and Department of Mechanical Engineering, University of Washington（工业与系统工程系和机械工程系，华盛顿大学）
REACT: Real-time Entanglement-Aware Coverage Path Planning for Tethered Underwater Vehicles
Artificial Intelligence in Robotics Laboratory (AiR Lab), Department of Electrical and Computer Engineering, Aarhus University（人工智能机器人实验室（AiR实验室），电气与计算机工程系，阿arhus大学）；NestAI；EIVA a/s（EIVA公司）；Deutsches Forschungszentrum für Künstliche Intelligenz GmbH (DFKI)（德国人工智能研究中心（DFKI））；Automatic Control Group, Department of Electrical Engineering and Information Technology, Paderborn University（自动控制组，电气工程与信息科技系，帕德博恩大学）
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…
This paper presents a solution to Autonomous Underwater Vehicles (AUVs) large scale route planning and task assignment joint problem. Given a set of constraints (e.g., time) and a set of task priority values, the goal is to find the optimal route for underwater mission that maximizes the sum of the priorities and minimizes the total risk percentage while meeting the given constraints. Making use of the heuristic nature of genetic and swarm intelligence algorithms in solving NP-hard graph problems, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are employed to find the optimum sol…
Visually-guided underwater robots are deployed alongside human divers for cooperative exploration, inspection, and monitoring tasks in numerous shallow-water and coastal-water applications. The most essential capability of such companion robots is to visually interpret their surroundings and assist the divers during various stages of an underwater mission. Despite recent technological advancements, the existing systems and solutions for real-time visual perception are greatly affected by marine artifacts such as poor visibility, lighting variation, and the scarcity of salient features. The dif…
University of Michigan（密歇根大学）；Toyota Technological Institute at Chicago（芝加哥丰田技术研究所）；University of Sydney（悉尼大学）；Woods Hole Oceanographic Institution（伍兹霍尔海洋研究所）
In this report, we present the system design, operational strategy, and results of coordinated multi-vehicle field demonstrations of autonomous marine robotic technologies in search-for-life missions within the Pacific shelf margin of Costa Rica and the Santorini-Kolumbo caldera complex, which serve as analogs to environments that may exist in oceans beyond Earth. This report focuses on the automation of ROV manipulator operations for targeted biological sample-collection-and-return from the seafloor. In the context of future extraterrestrial exploration missions to ocean worlds, an ROV is an …
In the context of robotic underwater operations, the visual degradations induced by the medium properties make difficult the exclusive use of cameras for localization purpose. Hence, most localization methods are based on expensive navigational sensors associated with acoustic positioning. On the other hand, visual odometry and visual SLAM have been exhaustively studied for aerial or terrestrial applications, but state-of-the-art algorithms fail underwater. In this paper we tackle the problem of using a simple low-cost camera for underwater localization and propose a new monocular visual odome…
Democritus University of Thrace（色雷斯德谟克利特大学）；Information Technologies Institute, The Centre for Research & Technology, Hellas（希腊研究与技术中心信息技术研究所）；National Technical University（国立技术大学）
This paper proposes a novel mission planning platform, capable of efficiently deploying a team of UAVs to cover complex-shaped areas, in various remote sensing applications. Under the hood lies a novel optimization scheme for grid-based methods, utilizing Simulated Annealing algorithm, that significantly increases the achieved percentage of coverage and improves the qualitative features of the generated paths. Extensive simulated evaluation in comparison with a state-of-the-art alternative methodology, for coverage path planning (CPP) operations, establishes the performance gains in terms of a…
Wukong-Omni: Design, Modeling and Control of a Multi-mode Robot for Air, Land, and Underwater Exploration with All-in-One Propulsion Unit
School of Automation, Guandong University of Technology（广东技术大学自动化学院）；School of Electromechanical Engineering, Guangdong University of Technology（广东技术大学机电工程学院）；Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology（香港科技大学电子与计算机工程系）
This paper presents a novel Rapidly-exploring Adaptive Sampling Tree (RAST) algorithm for the adaptive sampling mission of a hybrid aerial underwater vehicle (HAUV) in an air-sea 3D environment. This algorithm innovatively combines the tournament-based point selection sampling strategy, the information heuristic search process and the framework of Rapidly-exploring Random Tree (RRT) algorithm. Hence can guide the vehicle to the region of interest to scientists for sampling and generate a collision-free path for maximizing information collection by the HAUV under the constraints of environmenta…
Microscopic analysis of micro particles in situ in diverse water environments is necessary for monitoring water quality and localizing contamination sources. Conventional sensors such as optical microscopes and fluorometers often require complex sample preparation, are restricted to small sample volumes, and are unable to simultaneously capture all pertinent details of a sample such as particle size, shape, concentration, and three dimensional motion. In this article we propose a novel and cost-effective robotic system for mobile microscopic analysis of particles in situ at various depths whic…
This paper presents a novel approach to modeling curiosity in a mobile robot, which is useful for monitoring and adaptive data collection tasks, especially in the context of long term autonomous missions where pre-programmed missions are likely to have limited utility. We use a realtime topic modeling technique to build a semantic perception model of the environment, using which, we plan a path through the locations in the world with high semantic information content. The life-long learning behavior of the proposed perception model makes it suitable for long-term exploration missions. We valid…
