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Digital Twins Below the Surface: Enhancing Underwater Teleoperation
Favour O. Adetunji;Niamh Ellis;Maria Koskinopoulou;Ignacio Carlucho;Yvan R. Petillot
OCEANS 2024 - Singapore
Year: 2024 | Conference Paper |
Subsea exploration, inspection, and intervention operations heavily rely on remotely operated vehicles (ROVs). However, the inherent complexity of the underwater environment presents significant challenges to the operators of these vehicles. This paper delves into the challenges associated with navigation and maneuvering tasks in the teleoperation of ROVs, such as reduced situational awareness and...Show More
URoBench: Comparative Analyses of Underwater Robotics Simulators from Reinforcement Learning Perspective
Zebin Huang;Markus Buchholz;Michele Grimaldi;Hao Yu;Ignacio Carlucho;Yvan R. Petillot
OCEANS 2024 - Singapore
Year: 2024 | Conference Paper |
In an effort to standardise the evaluation of Reinforcement Learning (RL) algorithms across different simulators of underwater robots, this paper introduces a benchmark framework, URoBench, to test the capabilities of simulators in RL- related tasks of underwater robotics. This framework is characterised by its modular architecture. By abstracting these components, the framework allows for integra...Show More
Modeling and Motion Control of a Fully Actuated Multirotor for Aerial Manipulation Using PX4 and ROS2
2024 9th International Conference on Mechatronics Engineering (ICOM)
Year: 2024 | Conference Paper |
Aerial physical interaction and manipulation are increasingly in demand for various industrial applications. Research groups are striving to create innovative fully actuated designs tailored to these needs. However, creating custom flight stacks and software drivers often slows development and impedes research replication and benchmarking. This paper aims to leverage open-source libraries to accel...Show More
Semi-autonomous surface-tracking tasks using omnidirectional mobile manipulators
2024 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2024 | Conference Paper |
Despite the potential of mobile manipulators and applications where robots require a force-controlled physical interaction with the environment, the majority of robot automation nowadays is still based on fixed manipulators for free-motion tasks (e.g. welding, pick and place, or painting). In this work, we propose a control solution for omnidirectional mobile manipulators in force-tracking tasks, ...Show More
Enhancing AUV Autonomy with Model Predictive Path Integral Control
Pierre Nicolay;Yvan Petillot;Mykhaylo Marfeychuk;Sen Wang;Ignacio Carlucho
OCEANS 2023 - MTS/IEEE U.S. Gulf Coast
Year: 2023 | Conference Paper |
Autonomous underwater vehicles (AUVs) play a crucial role in surveying marine environments, carrying out underwater inspection tasks, and ocean exploration. However, in order to ensure that the AUV is able to carry out its mission successfully, a control system capable of adapting to changing environmental conditions is required. Furthermore, to ensure the safe operation of the robotic platform th...Show More
Large-Scale Radar Localization using Online Public Maps
2023 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2023 | Conference Paper |
Cited by: Papers (3)
In this paper, we propose using online public maps, e.g., OpenStreetMap (OSM), for large-scale radar-based localization without needing a prior sensing map. This can potentially extend the localization system to anywhere worldwide without building, saving, or maintaining a sensing map, as long as an online public map covers the operating area. Existing methods using OSM only use route network or s...Show More
Observability-Aware Active Extrinsic Calibration of Multiple Sensors
Shida Xu;Jonatan Scharff Willners;Ziyang Hong;Kaicheng Zhang;Yvan R. Petillot;Sen Wang
2023 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2023 | Conference Paper |
Cited by: Papers (3)
The extrinsic parameters play a crucial role in multi-sensor fusion, such as visual-inertial Simultaneous Localization and Mapping(SLAM), as they enable the accurate alignment and integration of measurements from different sensors. However, extrinsic calibration is challenging in scenarios, such as underwater, where in-view structures are scanty and visibility is limited, causing incorrect extrins...Show More
Adaptive Heading for Perception-Aware Trajectory Following
Jonatan Scharff Willners;Sean Katagiri;Shida Xu;Tomasz Łuczyński;Joshua Roe;Yvan Petillot
2023 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2023 | Conference Paper |
Cited by: Papers (4)
This paper presents an adaptive heading approach for perception awareness during trajectory following. By adapting the heading of a robot to improve the feature tracking in the current mapped environment, the accuracy in localisation can be improved. This can have a significant advantage for autonomous operations in GPS-denied environments such as subsea or in caves. The aim of the proposed approa...Show More
Advanced Underwater Wireless Optical Communication System Assisted by Deep Echo State Network
2022 Asia Communications and Photonics Conference (ACP)
Year: 2022 | Conference Paper |
The underwater wireless sensor network (UWSN) has been widely employed in scientific and commercial applications. The underwater wireless optical communication (UWOC) provides high transmission data rate, high security, and low latency communication to link the nodes in a UWSN. However, the link length of the UWOC systems is severely affected by large absorption and scattering losses that reduce t...Show More
Autonomous Underwater Robotic Grasping Research Based on Navigation and Hierarchical Operation
Cong Wang;Qifeng Zhang;Xiaohui Wang;Shida Xu;Yvan Petillot;Sen Wang
2022 7th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
This paper proposes a new framework for the autonomous underwater operation of underwater vehicle manipulator systems (UVMS), which is modular, standardized, and hierarchical. The framework consists of three subsystems: perception, navigation, and grasping. The perception module is based on an underwater stereo vision system, which provides effective environment and target information for the navi...Show More
Multi-Task Reinforcement Learning based Mobile Manipulation Control for Dynamic Object Tracking and Grasping
Cong Wang;Qifeng Zhang;Xiaohui Wang;Shida Xu;Yvan Petillot;Sen Wang
2022 7th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
Agile control of mobile manipulator is challenging because of the high complexity coupled by the robotic system and the unstructured working environment. Tracking and grasping a dynamic object with a random trajectory is even harder. In this paper, a multi-task reinforcement learning-based mobile manipulation control framework is proposed to achieve general dynamic object tracking and grasping. Se...Show More
Sliding Mode Controller for Positioning of an Underwater Vehicle Subject to Disturbances and Time Delays
Harun Tugal;Kamil Cetin;Xiaoran Han;Ibrahim Kucukdemiral;Joshua Roe;Yvan Petillot;M. Suphi Erden
2022 International Conference on Robotics and Automation (ICRA)
Year: 2022 | Conference Paper |
Cited by: Papers (6)
Unmanned underwater vehicles are crucial for deep-sea exploration and inspection without imposing any danger to human life due to extreme environmental conditions. But, designing a robust controller that can cope with model uncertainties, external disturbances, and time delays for such vehicles is a challenge. This paper implements a sliding mode position control algorithm with a time-delay estima...Show More
Sectorized FMCW MIMO Radar by Modular Design With Non-Uniform Sparse Arrays
Cristian A. Alistarh;Symon K. Podilchak;Pascual D. Hilario Re;Thomas M. Ströber;Yan Pailhas;Carolina Mateo-Segura;Mathini Sellathurai;George Goussetis;Yvan R. Petillot;John S. Thompson;Jaesup Lee
Automotive radars are designed to enhance road user safety and reduce the number of accidents on public roads and there is a constant demand to improve the performance for these radars. In this paper, a novel proof-of-concept multiple-input multiple-output (MIMO) radar architecture is presented by frequency modulated continuous waveform (FMCW) transmission. For enhanced angular resolution, the rad...Show More
Porous Elastomer Based Wide Range Flexible Pressure Sensor for Autonomous Underwater Vehicles
Ensieh S. Hosseini;Moupali Chakraborty;Joshua Roe;Yvan Petillot;Ravinder S. Dahiya
This work presents the design and implementation of a porous polydimethylsiloxane (PDMS)-based wide-range flexible pressure sensor for autonomous underwater vehicles. The capacitive sensor, with porous PDMS as dielectric, is encapsulated in bulk PDMS polymer. The fabricated sensor was evaluated over a wide pressure range (0-230 kPa), which is similar to pressures experienced up to approx. 23 m bel...Show More
Online Mapping and Motion Planning Under Uncertainty for Safe Navigation in Unknown Environments
Èric Pairet;Juan David Hernández;Marc Carreras;Yvan Petillot;Morteza Lahijanian
Safe autonomous navigation is an essential and challenging problem for robots operating in highly unstructured or completely unknown environments. Under these conditions, not only robotic systems must deal with limited localization information but also their maneuverability is constrained by their dynamics and often suffers from uncertainty. In order to cope with these constraints, this article pr...Show More
Learning-Based Underwater Autonomous Grasping via 3D Point Cloud
Cong Wang;Qifeng Zhang;Shuo Li;Xiaohui Wang;David Lane;Yvan Petillot;Sen Wang
Underwater autonomous grasping is a challenging task for robotic research. In this paper, we propose a learning-based underwater grasping method using 3D point cloud generated from an underwater stereo camera. First, we use Pinax-model for accurate refraction correction of a stereo camera in a flat-pane housing. Second, dense point cloud of the target is generated using the calibrated stereo image...Show More
From market-ready ROVs to low-cost AUVs
Jonatan Scharff Willners;Ignacio Carlucho;Sean Katagiri;Chandler Lemoine;Joshua Roe;Dylan Stephens;Tomasz Łuczyński;Shida Xu;Yaniel Carreno;Èric Pairet;Corina Barbalata;Yvan Petillot;Sen Wang
Autonomous Underwater Vehicles (AUVs) are becoming increasingly important for different types of industrial applications. The generally high cost of AUVs restricts the access to them and therefore advances in research and technological development. However, recent advances have led to lower cost commercially available Remotely Operated Vehicles (ROVs), which present a platform that can be enhanced...Show More
Underwater Visual Acoustic SLAM with Extrinsic Calibration
Shida Xu;Tomasz Luczynski;Jonatan Scharff Willners;Ziyang Hong;Kaicheng Zhang;Yvan R. Petillot;Sen Wang
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2021 | Conference Paper |
Cited by: Papers (19)
Underwater scenarios are challenging for visual Simultaneous Localization and Mapping (SLAM) due to limited visibility and intermittently losing structures in image views. In this paper, we propose a visual acoustic bundle adjustment system which fuses a camera and a Doppler Velocity Log (DVL) in a graph SLAM framework for reliable underwater localization and mapping. In order to fuse the vision w...Show More
Robust Underwater Visual SLAM Fusing Acoustic Sensing
Elizabeth Vargas;Raluca Scona;Jonatan Scharff Willners;Tomasz Luczynski;Yu Cao;Sen Wang;Yvan R. Petillot
2021 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2021 | Conference Paper |
Cited by: Papers (29)
In this paper, we propose an approach for robust visual Simultaneous Localisation and Mapping (SLAM) in underwater environments leveraging acoustic, inertial and altimeter/depth sensors. Underwater visual SLAM is challenging due to factors including poor visibility caused by suspended particles in water, a lack of light and insufficient texture in the scene. Because of this, many state-of-the-art ...Show More
Connected Sensors, Innovative Sensor Deployment, and Intelligent Data Analysis for Online Water Quality Monitoring
Libu Manjakkal;Srinjoy Mitra;Yvan R. Petillot;Jamie Shutler;E. Marian Scott;Magnus Willander;Ravinder Dahiya
IEEE Internet of Things Journal
Cited by: Papers (41)
The sensor technology for water quality monitoring (WQM) has improved during recent years. The cost-effective sensorised tools that can autonomously measure the essential physical-chemical-biological (PCB) variables are now readily available and are being deployed on buoys, boats, and ships. Yet, there is a disconnect between the data quality, data gathering, and data analysis due to the lack of s...Show More
Path Planning for Manipulation Using Experience-Driven Random Trees
Èric Pairet;Constantinos Chamzas;Yvan Petillot;Lydia E. Kavraki
Robotic systems may frequently come across similar manipulation planning problems that result in similar motion plans. Instead of planning each problem from scratch, it is preferable to leverage previously computed motion plans, i.e., experiences, to ease the planning. Different approaches have been proposed to exploit prior information on novel task instances. These methods, however, rely on a va...Show More
A Comparison of Few-Shot Learning Methods for Underwater Optical and Sonar Image Classification
Global Oceans 2020: Singapore – U.S. Gulf Coast
Year: 2020 | Conference Paper |
Cited by: Papers (18)
Deep convolutional neural networks generally perform well in underwater object recognition tasks on both optical and sonar images. Many such methods require hundreds, if not thousands, of images per class to generalize well to unseen examples. However, obtaining and labeling sufficiently large volumes of data can be relatively costly and time-consuming, especially when observing rare objects or pe...Show More
RadarSLAM: Radar based Large-Scale SLAM in All Weathers
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2020 | Conference Paper |
Cited by: Papers (99)
Numerous Simultaneous Localization and Mapping (SLAM) algorithms have been presented in last decade using different sensor modalities. However, robust SLAM in extreme weather conditions is still an open research problem. In this paper, RadarSLAM, a full radar based graph SLAM system, is proposed for reliable localization and mapping in large-scale environments. It is composed of pose tracking, loc...Show More
Self-Assessment of Grasp Affordance Transfer
Paola Ardón;Èric Pairet;Yvan Petillot;Ronald P. A. Petrick;Subramanian Ramamoorthy;Katrin S. Lohan
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2020 | Conference Paper |
Cited by: Papers (13)
Reasoning about object grasp affordances allows an autonomous agent to estimate the most suitable grasp to execute a task. While current approaches for estimating grasp affordances are effective, their prediction is driven by hypotheses on visual features rather than an indicator of a proposal's suitability for an affordance task. Consequently, these works cannot guarantee any level of performance...Show More
TextPlace: Visual Place Recognition and Topological Localization Through Reading Scene Texts
2019 IEEE/CVF International Conference on Computer Vision (ICCV)
Year: 2019 | Conference Paper |
Cited by: Papers (38)
Visual place recognition is a fundamental problem for many vision based applications. Sparse feature and deep learning based methods have been successful and dominant over the decade. However, most of them do not explicitly leverage high-level semantic information to deal with challenging scenarios where they may fail. This paper proposes a novel visual place recognition algorithm, termed TextPlac...Show More
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