Heterogeneous aquatic robot system: architecture and core technologies
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Heterogeneous Aquatic Robot System: Architecture and Core Technologies
view moreCredit: Shanghai Jiao Tong University,Hainan University
Published in Robot Learning, this study reviews recent advances in heterogeneous aquatic robot systems, which integrate underwater, surface, and aerial robots to perform coordinated tasks in complex marine environments. It highlights key developments in communication, sensing, navigation, control, decision-making, and energy management. Real-world applications—from ocean monitoring to underwater archaeology—are discussed, along with technical challenges and future directions. This work offers a roadmap for building intelligent, collaborative robotic systems to support sustainable marine exploration.
This review article, authored by Dr. Weidong Zhang’s team from Shanghai Jiao Tong University, was recently published in the journal Robot Learning. Focusing on the increasingly prominent topic of heterogeneous aquatic robotic systems, the paper provides a comprehensive overview and analysis of the development status and future applications of key technologies in this field. The research team also includes scholars from Tongji University and Hainan University, reflecting the interdisciplinary and cross-institutional nature of the collaboration.
Heterogeneous aquatic robotic systems refer to intelligent systems composed of different types of robots working together, including underwater remotely operated vehicles (ROVs), autonomous underwater vehicles (AUVs), surface vessels, and aerial drones. Each type of robot offers unique capabilities, but it is through coordination and collaboration that these systems can effectively perform diverse tasks such as resource exploration, environmental monitoring, and emergency response in complex aquatic environments. The paper reviews the system from six major technical perspectives: communication, perception, navigation, control, decision-making, and energy management. In addition to summarizing the current research progress, it presents several representative engineering case studies.
The authors note that although these technologies have shown promising potential in various real-world applications, they still face significant challenges, such as signal attenuation in underwater communication, limited energy capacity, and unreliable perception in dynamic environments. These limitations hinder the performance of robotic systems in high-complexity tasks, highlighting the need for continued advancements in algorithms, hardware, and system architecture. The paper also outlines potential future directions, including the integration of multiple communication methods for improved data transmission, the use of deep learning to enhance autonomous decision-making, and multi-robot collaboration for greater intelligence and system robustness.
As a review article, the goal of this work is not to propose a single technological breakthrough, but rather to provide a structured and systematic summary that can serve as a reference point for future research. For researchers in the field, it may offer a helpful entry point to better understand this interdisciplinary area and contribute to the ongoing evolution of intelligent aquatic systems through cross-domain collaboration and integrated platform development.
This paper ”Survey on heterogeneous aquatic robot systems: communication, perception, navigation, control, decision-making and energy management” was published in Robot Learning.
Liu R, Hu X, Jiang Z, Wang J, Zhang W. Survey on heterogeneous aquatic robot systems: communication, perception, navigation, control, decision-making and energy management. Robot Learn. 2025(1):0003, https://doi.org/10.55092/rl20250003.
Journal
Robot Learning
Method of Research
Literature review
Subject of Research
Not applicable
Article Title
Survey on heterogeneous aquatic robot systems: communication, perception, navigation, control, decision-making and energy management
HKU engineering team revolutionizes drone technology with bird-like autonomous flight for micro air vehicles
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SUPER can navigate complex environments at high speeds with a level of safety previously unattainable.
view moreCredit: The University of Hong Kong
Unlike birds, which navigate unknown environments with remarkable speed and agility, drones typically rely on external guidance or pre-mapped routes. However, a groundbreaking development by Professor Fu Zhang and researchers from the Department of Mechanical Engineering of Faculty of Engineering at the University of Hong Kong (HKU), has enabled drones and micro air vehicles (MAVs) to emulate the flight capabilities of birds more closely than ever before.
The team has developed the Safety-Assured High-Speed Aerial Robot (SUPER), capable of flying at speeds exceeding 20 meters per second and avoiding obstacles as thin as 2.5 millimetres – such as power lines or twigs – using solely on onboard sensors and computing power. With a compact design featuring a wheelbase of just 280 mm and a takeoff weight of 1.5 kg, SUPER demonstrates exceptional agility, navigating dense forests at night and skilfully avoiding thin wires.
Professor Zhang describes this invention as a game-changer in the field of drone technology, “Picture a 'Robot Bird' swiftly maneuvering through the forest, effortlessly dodging branches and obstacles at high speeds. This is a significant step forward in autonomous flight technology. Our system allows MAVs to navigate complex environments at high speeds with a level of safety previously unattainable. It’s like giving the drone the reflexes of a bird, enabling it to dodge obstacles in real-time while racing toward its goal.”
The breakthrough lies in the sophisticated integration of hardware and software. SUPER utilises a lightweight 3D light detection and ranging (LIDAR) sensor capable of detecting obstacles up to 70 metres away with pinpoint accuracy. This is paired with an advanced planning framework that generates two trajectories during flight: one that optimising speed by venturing into unknown spaces and another prioritising safety by remaining within known, obstacle-free zones.
By processing LIDAR data directly as point clouds, the system significantly reduces computation time, enabling rapid decision-making even at high velocities. The technology has been tested in various real-life applications, such as the autonomous exploration of ancient sites, and has demonstrated seamless navigation in both indoor and outdoor environments.
“The ability to avoid thin obstacles and navigate tight spaces opens up new possibilities for applications like search and rescue, where every second counts. SUPER’s robustness in various lighting conditions, including nighttime, makes it a reliable tool for round-the-clock operations.” said Mr Yunfan Ren, the lead author of the research paper.
The research team envisions a wide range of applications for this innovative technology, including autonomous delivery, power line inspection, forest monitoring, autonomous exploration, and mapping. In search and rescue missions, MAVs equipped with SUPER technology could swiftly navigate disaster zones – such as collapsed buildings or dense forests – day and night, locating survivors or assessing hazards more efficiently than current drones. Moreover, in disaster relief scenarios, they could deliver crucial supplies to remote and inaccessible areas.
The research has been published in Science Robotics, titled as “Safety-assured high-speed navigation for MAVs”.
For details about the research article, please visit: https://www.science.org/doi/10.1126/scirobotics.ado6187.
Link to the video demo: https://youtu.be/GPHuzG0ANmI?si=hfIFcMye0XX708OX
About Professor Fu Zhang
Professor Fu Zhang is an Associate Professor of Department of Mechanical Engineering of Faculty of Engineering at HKU, and serves as the director of the HKU Mechatronics and Robotic Systems Lab (MaRS LAB). Professor Zhang received his B.E. degree in Automation from the University of Science and Technology of China (USTC) in 2011, and the Ph.D. degree in Controls from the University of California, Berkeley in 2015. His Ph.D. work focused on self-calibration and control of micro rate-integrating gyro sensors. In 2016, Professor Zhang shifted his research to the design and control of Unmanned Aerial Vehicles (UAVs) as a Research Assistant Professor in the Robotics Institute of the Hong Kong University of Science and Technology (HKUST). He joined the Faculty of Engineering at HKU as an Assistant Professor in the Department of Mechanical Engineering in August 2018. His research interests lie in robotics and controls, with a focus on UAV design, navigation, control, and lidar-based simultaneous localization and mapping.
About the research team
The HKU Mechatronics and Robotic Systems Lab (MaRS LAB) is dedicated to the study of general mechatronic systems and robotics, with a particular emphasis on their practical applications in real-world human environments and industries. Research areas include the design, planning, and control of aerial robots, as well as LiDAR-based simultaneous localization and mapping (SLAM) techniques. Mr Yunfan Ren is a PhD candidate at HKU, and a member of the MaRS LAB, focuses his research on autonomous navigation and swarm intelligence for aerial robots.
SUPER has undergone testing in a variety of real-world applications, including situations with complete darkness and cluttered environments.
System overview of SUPER
Credit
The University of Hong Kong
The University of Hong Kong
Journal
Science Robotics
Method of Research
Experimental study
Subject of Research
Not applicable
Article Title
Safety-assured high-speed navigation for MAVs
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