Ben M Chen

• PhD
• Professor (Full) at Chinese University of Hong Kong

Visual-based defect detection efficiently monitors the health and quality of construction and industrial products. However, current defect detection methods often improve detection accuracy at the cost of lower inference speeds or more parameters, struggle with complex data representation, emphasize target features while neglecting environmental in...

This article focuses on the challenge of accurate Micro Aerial Vehicle (MAV) detection under memory-constrained and lower computational cost conditions. A miniature MAV detection framework, DRNet, is proposed to address this issue. DRNet incorporates a Dual Skip Concatenation Network (DSC) and Squeezing Excitation Residual Networks (SER) for featur...

Accurately predicting ocean subsurface temperature is vital for advancing ocean and climate research, particularly given the sparse and costly nature of subsurface observations. This study introduces sparse-to-dense prediction of ocean subsurface temperature using multi-level spatiotemporal (ST) information fusion. The framework integrates interpre...

The misuse of drones can jeopardize public safety and privacy. The detection and catching of intruding drones are crucial and urgent issues to be investigated. This work proposes VDTNet, an accurate, lightweight, and fast network for visually detecting and tracking intruding drones. We first incorporate an SPP module into the first head of YOLOv4 t...

Multi-robot systems have increasingly become instrumental in tackling coverage problems. However, the challenge of optimizing task efficiency without compromising task success still persists, particularly in expansive, unstructured scenarios with dense obstacles. This paper presents an innovative , decentralized Voronoi-based coverage control appro...

The challenge of efficient target searching in vast natural environments has driven the need for advanced multi-UAV active search strategies. This paper introduces a novel method in which global and local information is adeptly merged to avoid issues such as myopia and redundant back-and-forth movements. In addition, a trajectory generation method...

Aerial object detection is crucial in various computer vision tasks, including video monitoring, early warning systems, and visual tracking. While current methods can accurately detect normal-sized objects, they face challenges distinguishing small objects from cluttered backgrounds. Developing methods that can be deployed on edge devices to achiev...

Despite promising SLAM research in both vision and robotics communities, which fundamentally sustains the autonomy of intelligent unmanned systems, visual challenges still threaten its robust operation severely. Existing SLAM methods usually focus on specific challenges and solve the problem with sophisticated enhancement or multi-modal fusion. How...

Unmanned aerial vehicles (UAVs) are emerging as a powerful tool for inspections and repair works in large-scale and unstructured 3D infrastructures, but current approaches take a long time to cover the entire area. Planning using UAVs for inspections and repair works puts forward a requirement of improving time efficiency in large-scale and cluster...

Due to the complementary properties between sensors, multi-sensor fusion can effectively promote accuracy and tackle the challenging scenes in simultaneous localization and mapping (SLAM) tasks. To this end, we propose a novel LiDAR-camera fused method for odometry and mapping using dense colored point clouds. With the camera well calibrated to the...

Underwater image enhancement (UIE) is crucial for high-level vision in underwater robotics. While convolutional neural networks (CNNs) have made significant achievements in UIE, the locality of convolution poses a challenge in capturing the global context. In contrast, transformer-based networks, adept at handling long-range dependencies, have show...

The underwater leveling motion control of a morphable unmanned aerial--aquatic vehicle (M-UAAV) is essential but lacks an elegant solution. In this article, a scheme named Aqua Slide is proposed for Mirs-Alioth, our predeveloped M-UAAV prototype, to achieve underwater leveling motions by utilizing singularity. For the first time, the singular thrus...

In this paper, we present in this work a fairly complete process for developing an unmanned aerial–aquatic vehicle system, TJ-FlyingFish, which includes an innovative design methodology of the aerial–aquatic platform and the cross-medium localization, dynamics modeling, and flight control systems. The development faces the challenge how to manipula...

This article investigates the practical scenarios of chasing an adversarial evader in an unbounded environment with cluttered obstacles. We propose a Voronoi-based decentralized algorithm for multiple pursuers to encircle and capture the evader by reacting to collisions. An efficient approach is presented for constructing an obstacle-aware evader-c...

Due to the critical role of pavement crack detection for road maintenance and eventually ensuring safety, remarkable efforts have been devoted to this research area, and such a trend is further intensified for the coming unmanned vehicle era. However, such crack detection task still remains unexpectedly challenging in practice since the appearance...

Autonomous navigation in unknown environments with obstacles remains challenging for micro aerial vehicles (MAVs) due to their limited onboard computing and sensing resources. Although various collision avoidance methods have been developed, it is still possible for drones to collide with unobserved obstacles due to unpredictable disturbances, sens...

We present in this paper a novel framework and distributed control laws for the formation of multiple unmanned rotorcraft systems, be it single-rotor helicopters or multi-copters, with physical constraints and with inter-agent collision avoidance, in cluttered environments. The proposed technique is composed of an analytical distributed consensus c...

Underwater image enhancement (UIE) is vital for high-level vision-related underwater tasks. Although learning-based UIE methods have made remarkable achievements in recent years, it's still challenging for them to consistently deal with various underwater conditions, which could be caused by: 1) the use of the simplified atmospheric image formation...

Aerial-aquatic vehicles are capable to move in the two most dominant fluids, making them more promising for a wide range of applications. We propose a prototype with special designs for propulsion and thruster configuration to cope with the vast differences in the fluid properties of water and air. For propulsion, the operating range is switched fo...

Traditional indoor facility inspections on pipelines and boilers are conducted manually and can be logistically challenging, labor-intensive, costly, and dangerous for the inspectors. With the maturity of unmanned technology, the unmanned aerial vehicle (UAV) is becoming a promising alternative to the problematic manual inspection. However, due to...

In this paper, distributed optimal solutions are designed for networked multiagent pursuit-evasion (MPE) games for capture and formation control. In the games, the pursuers aim to minimize the distance from their target evaders while the evaders attempt to maximize it, and at the same time, all players desire to maintain cohesion with their teammat...

In this article, we propose a distributed algorithm for cooperatively pursuing an adversarial evader in an unbounded environment with cluttered obstacles. The algorithm relies on constructing the buffered evader-centered bounded Voronoi cell (B-ECBVC) in real time for each pursuer to safely chase the evader among obstacles. Based on the B-ECBVC, an...

3-D reconstruction is essential to defect localization. This article proposes LCM-MVSNet, a novel multi-view stereo (MVS) network with learnable cost metric (LCM) for more accurate and complete dense point cloud reconstruction. To adapt to the scene variation and improve the reconstruction quality in non-Lambertian low-textured scenes, we propose L...

Local feature detection is a key ingredient of many image processing and computer vision applications, such as visual odometry and localization. Most existing algorithms focus on feature detection from a sharp image. They would thus have degraded performance once the image is blurred, which could happen easily under low-lighting conditions. To addr...

Deep learning breakthrough stimulates new research trends in civil infrastructure inspection, whereas the lack of quality-guaranteed, human-annotated, free-of-charge, and publicly available defect datasets with sufficient amounts of data hinders the progress of deep learning in defect inspection. To boost research in deep learning-based visual defe...

Current state-of-the-art 3D scene understanding methods are merely designed in a full-supervised way. However, in the limited reconstruction cases, only limited 3D scenes can be reconstructed and annotated. We are in need of a framework that can concurrently be applied to 3D point cloud semantic segmentation and instance segmentation, particularly...

Motivated by the importance of physical constraints of multi-agent systems, we investigate in this work the semi-global leader-following output consensus control of discrete-time heterogeneous linear systems subject to position and rate-limited actuators and directed switching networks. Based on a distributed observer, we designed a distributed con...

In this letter, we present a volumetric mapping system that effectively calculates Occupancy Grid Maps (OGMs) and Euclidean Distance Transforms (EDTs) with parallel computing. Unlike these mappers for high-precision structural reconstruction, our system incrementally constructs global EDT and outputs high-frequency local distance information for on...

In this paper, we consider the semi‐global leader–following output consensus of heterogeneous multi‐agent linear systems over a directed communication graph with both the leader agent and the follower agents subject to input saturation. Via the low gain feedback design technique, both the state feedback and output feedback consensus protocols are c...

The defect diagnosis of modern infrastructures is crucial to public safety. In this work, we propose an unsupervised domain adaptive crack recognition framework. To fulfill the unsupervised domain adaptation (UDA) task of cracks recognition in infrastructural inspections, we propose a robust unsupervised domain adaptive learning strategy termed Cr...

Motivated by the fact that physical systems are usually subject to actuator position and rate saturation, we consider in this paper the semi-global leader-following output consensus problem of a group of discrete-time heterogeneous linear systems with position and rate-limited actuators by output feedback control law. Distributed observers are desi...

We study in this paper a semi-global leader-following output consensus problem for multiple heterogeneous linear systems in the presence of actuator position and rate saturation over a directed topology. For each follower, via the low gain feedback design technique and output regulation theory, both a state feedback consensus protocol and an output...

Challenges in motion planning for multiple quadrotors in complex environments lie in overall flight efficiency and the avoidance of obstacles, deadlock, and collisions among themselves. In this paper, we present a gradient-free trajectory generation method for multiple quadrotors in dynamic obstacle-dense environments with the consideration of time...

In this paper, we present a trajectory generation method of a quadrotor, based on the optimal smoothing B-spline, for tracking a moving target with consideration of relative tracking pattern or limited field of view of the onboard sensor in cluttered environments. Compared to existing methods, safe flying zone, vehicle physical limits, and smoothne...

This paper addresses the challenging problem of chasing an escaping target using a quadrotor in cluttered environments. To tackle these challenges, we propose a guided time-optimal model predictive control (GTO-MPC) based practical framework to generate chasing trajectories for the quadrotor. A jerk limited approach is first adopted to find a time-...

In this paper, we investigate a formation control problem of multi-agent systems (specifically a group of unmanned aerial vehicles) based on a semi-global leader-following consensus approach with both the leader and the followers subject to input saturation. Utilizing the low gain feedback design technique, a distributed static control protocol and...

This work presents FG-Net, a general deep learning framework for large-scale point clouds understanding without voxelizations, which achieves accurate and real-time performance with a single NVIDIA GTX 1080 GPU. First, a novel noise and outlier filtering method is designed to facilitate subsequent high-level tasks. For effective understanding purpo...

As the development of mobile robots matures, there is an increasing amount of interest in expanding the functionality of such robots through developing multimodal locomotion. As compared to land–water or land–air hybrids, the design of air–water vehicles is much less straightforward due to the fact that both mediums are three-dimensional fluid spac...

Motivated by the promising applications of multiple Euler-Lagrange (EL) systems, we study, in this article, the formation-containment (FC) control problem for multiple EL systems of leaders with bounded unknown control inputs and with communication among each other over directed topologies, which can cooperatively generate safe trajectories to avoi...

Unmanned aerial systems provide many applications with the ability to perform flying tasks autonomously, and hence have received significant research and commercial attention in the past decade. One of the most popular unmanned aerial platforms for such tasks is the small-scale rotorcraft with multiple rotors, commonly known as multicopters. In ord...

Autonomous underwater vehicles (AUVs) highly depend on the quality of captured underwater images to perform a variety of tasks. However, compared with everyday images taken in air, underwater images are hazy, with color shift, and in relatively low quality, posing significant challenges to available mature vision algorithms to achieve expected perf...

In this article, we present a comprehensive design and implementation for a micro aerial vehicle (MAV) that is able to perform 3-D autonomous navigation and obstacle avoidance in cluttered and realistic unknown environments without the aid of global positioning system and other external sensors or markers. To achieve these autonomous missions, modu...