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PV-PASBLS: A Multimodal Point-View Fusion Model Based on Parameter Adaptive Stacked Broad Learning System for 3D Shape Recognition
Zhiyuan Liao;Chunquan Li;Hui Jin;Beike Li;Zhijun Zhang;Junzhi Yu;Peter X. Liu
IEEE Transactions on Instrumentation and Measurement
Year: 2025 | Early Access Article |
Most existing multimodal point-view fusion models for 3D shape recognition typically improve recognition accuracy through complex feature fusion mechanisms. However, these mechanisms significantly increase the model’s complexity and computational cost. To address this issue, a novel multimodal point-view fusion model based on a parameter adaptive stacked broad learning system (PV-PASBLS) for 3D sh...Show More
An Arbitrarily Predefined-Time Convergent RNN for Dynamic LMVE With Its Applications in UR3 Robotic Arm Control and Multiagent Systems
Zeroing neural network (ZNN), as a special type of recurrent neural network (RNN), is very competitive in solving time-varying linear matrix-vector equations. Recently, various ZNNs with predefined-time convergence (PTC) capabilities have been reported. Such ZNNs with PTC capabilities can achieve the predefined convergence time via explicitly presetting multiple parameters related to the upper bou...Show More
Rapid and Precise Online Surface Reconstruction Method for Digital Modeling of Bulk Material Flow
Wei Qiao;Chengcheng Hou;Xiaoyan Xiong;Huijie Dong;Yusong Pang;Junzhi Yu
IEEE Transactions on Industrial Informatics
Year: 2025 | Early Access Article |
Digital twins and visual monitoring of conveyor systems require accurate digital models of dynamic bulk material flows, but existing methods struggle to achieve both speed and precision. This study develops a rapid online method to reconstruct dynamic bulk material flows on conveyor belts. First, a standardized online reconstruction scheme using visual detection of material flow contour lines is p...Show More
Robust Practical Stabilization for Complex Dynamical Networks With DoS Attacks and Actuator Saturation
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Year: 2025 | Early Access Article |
This article addresses the problem of designing an attack-resilient adaptive event-triggered (AET) controller for complex dynamical networks (CDNs) under DoS attacks and actuator saturation, with a focus on robust practical stability (RPS). First, considering the impact of DoS attacks on closed-loop systems, an AET controller against DoS attacks is designed. Unlike other event-triggered controller...Show More
Decentralized Reinforcement Learning for Multiple Robotic Fish in Cooperative Pursuit Task
Yukai Feng;Zhengxing Wu;Jian Wang;Sijie Li;Yupei Huang;Junzhi Yu;Min Tan
IEEE Transactions on Cognitive and Developmental Systems
Year: 2025 | Early Access Article |
The control of multi-robot systems, particularly in the pursuit-evasion (PE) with multiple robots, has gained significant attention in both academic and non-academic settings. However, the collaborative operation of multi-robotic fish systems encounters substantial challenges due to the complex underwater environment and unique movement mode. In this paper, we propose a multi-agent reinforcement l...Show More
Contextual Multi-Armed Bandit-Based Dynamic Cooperative Link Configuration for AUV in UWASNs With Energy Harvesting
IEEE Transactions on Cognitive Communications and Networking
Year: 2025 | Early Access Article |
This paper investigates the cooperative link configuration problem for Autonomous Underwater Vehicle (AUV) in Underwater Acoustic (UWA) sensor networks with Energy Harvesting (EH), which aims to maximize long-term cumulative capacity by jointly optimizing cooperation relay, AUV transmission power, and relay transmission power.Subject to unknown time-varying Channel State Information (CSI), unpredi...Show More
Decentralized Multirobotic Fish Pursuit Control With Attraction-Enhanced Reinforcement Learning
Yukai Feng;Zhengxing Wu;Jian Wang;Junwen Gu;Fuyang Yu;Junzhi Yu;Min Tan
IEEE Transactions on Industrial Electronics
Year: 2025 | Early Access Article |
Adaptive and efficient cooperative control is a crucial capability for multirobotic fish systems, as it can substantially enhance their performance in complex underwater tasks. The pursuit and evasion dynamics in such topics have gained significant attention from the scientific community. In this article, we present a novel adaptive algorithm tailored specifically for cooperative pursuit among mul...Show More
Adjusting Distributed Cameras for Robust Moving Object Pose Estimation
Yaoqing Hu;Shaoan Wang;Dongyue Li;Xingyu Chen;Mingzhu Zhu;Zhanhua Xin;Junzhi Yu
IEEE Transactions on Automation Science and Engineering
Year: 2025 | Early Access Article |
Robust moving object pose estimation is crucial in fine manipulation tasks, such as surgical instrument tracking. This paper presents a distributed-camera system with robotic adjustments to maintain consistent tracking of moving objects, thus avoiding tracking failures. An integrated framework for camera adjustment and pose estimation is developed for this distributed-camera system. In each detect...Show More
Few-Shot Object Detection via Dual-Domain Feature Fusion and Patch-Level Attention
Guangli Ren;Jierui Liu;Mengyao Wang;Peiyu Guan;Zhiqiang Cao;Junzhi Yu
Few-shot object detection receives much attention with the ability to detect novel class objects using limited annotated data. The transfer learning-based solution becomes popular due to its simple training with good accuracy, however, it is still challenging to enrich the feature diversity during the training process. And fine-grained features are also insufficient for novel class detection. To d...Show More
Visual-Inertial-Acoustic Sensor Fusion for Accurate Autonomous Localization of Underwater Vehicles
Yupei Huang;Peng Li;Shaoxuan Ma;Shuaizheng Yan;Min Tan;Junzhi Yu;Zhengxing Wu
In this article, we propose a tightly coupled visual-inertial-acoustic sensor fusion method to improve the autonomous localization accuracy of underwater vehicles. To address the performance degradation encountered by existing visual or visual-inertial simultaneous localization and mapping systems when applied in underwater environments, we integrate the Doppler velocity log (DVL), an acoustic vel...Show More
Visual Sensor-Based Trajectory Multimodality Prediction via Anchor-Free Query Attention Network
As a core component of intelligent surveillance and autonomous driving systems, visual sensor-based trajectory multimodality prediction can significantly improve their perception and decision-making capabilities. Numerous existing trajectory prediction methods are dedicated to enhance prediction performance. However, they still fail to effectively model the complex spatiotemporal interactions amon...Show More
Deformation Control and Thrust Analysis of a Flexible Fishtail With Muscle-Like Actuation
Junwen Gu;Jian Wang;Zhijie Liu;Min Tan;Junzhi Yu;Zhengxing Wu
In nature, fish have evolved sophisticated muscular systems that enable them to dynamically regulate their body movements for efficient and agile swimming, which has inspired the development of compact and fast flexibility regulation mechanisms in robotic fish. While existing robotic fish have primarily relied on passive flexible mechanisms and tunable stiffness mechanisms, these approaches often ...Show More
An Innovative Visual Weighing Method: Measuring Bulk Material Mass Flows via Belt Deformation Field With Deep Learning
Wei Qiao;Xiaoyan Xiong;Chen Jie;Huijie Dong;Yusong Pang;Junzhi Yu
This article presents an innovative visual method for measuring material mass online by quantified conveyor belt deformation with deep learning, which offers a noncontact and safe alternative to traditional pressure- and radioactivity-based weighing techniques. The correlation between the belt deformation and the carried material mass is further investigated through finite element simulations. The...Show More
Hardness-Aware Metric Learning With Cluster-Guided Attention for Visual Place Recognition
Peiyu Guan;Zhiqiang Cao;Shengxuan Fan;Yuequan Yang;Junzhi Yu;Shuo Wang
Visual place recognition is crucial to accurate localization in large-scale environments. Existing methods combine convolutional neural network and deep metric learning to improve performance, however, it is still challenging to promote the adaptability of features under various environmental conditions. To address the problem, this paper proposes a hardness-aware metric learning method with clust...Show More
A Lightweight Integrated Positioning System With Occlusion-Aware Region-Based Pose Tracking for Oral and Maxillofacial Surgery
Dongyue Li;Yaoqing Hu;Shaoan Wang;Mingzhu Zhu;Fusong Yuan;Junzhi Yu
The development of an accurate and robust positioning system for oral and maxillofacial surgery (OMS) is a challenging task, primarily due to the oral space limitations and line-of-sight occlusions. This paper presents a novel lightweight integrated positioning system for OMS, which can provide practical guidance utilizing only a micro camera installed on the end of the surgical instrument. An eff...Show More
Robust Depth and Heading Control System for a Novel Robotic Dolphin With Multiple Control Surfaces
Sijie Li;Zhengxing Wu;Jian Wang;Changlin Qiu;Min Tan;Junzhi Yu
For field tasks, it is quite challenged to operate in a complex environment for the underwater robots, especially for those with multiple control surfaces due to different response and gain characteristics. To this end, this paper develops a highly integrated robotic dolphin followed by a robust motion control system. For better maneuverability and fault-tolerant capabilities, a newly-designed rob...Show More
Uncertainty-Aware Autonomous Robot Exploration Using Confidence-Rich Localization and Mapping
Information-based autonomous robot exploration methods, aiming to maximize the exploration rewards, e.g., mutual information (MI), get more prevalent in field robotics applications. However, most MI-based exploration methods assume known poses or use inaccurate pose uncertainty approximation, which may lead to deviation or even failure when exploring prior unknown environments. In this paper, we e...Show More
Accurate and Automatic Dental Crown Components Segmentation With Multi-Scale Attention Based U-Net and Hybrid Level Set Models
Dongyue Li;Mingzhu Zhu;Shaoan Wang;Yaoqing Hu;Fusong Yuan;Junzhi Yu
This paper presents a two-step method to automatically and accurately segment the dental crown components from CT images. Firstly, a multi-scale attention based U-Net model is proposed for pulp segmentation, which is embedded with global and local attention modules. The constructed attention modules can automatically aggregate pixel-wise contextual information and focus on catching the real dental...Show More
A Vision-Based Two-Stage Fruit Outer Diameter Detection Method
Yifei Hao;Shuaizheng Yan;Zhengxing Wu;Bingwei He;Chenghua Li;Junzhi Yu
2024 IEEE International Conference on Robotics and Biomimetics (ROBIO)
Year: 2024 | Conference Paper |
Regarding the mobile monitoring system in agricultural automation, the outer diameter monitoring of greenhouse vegetables has significant implications for accurately regulating fruit growth and cultivation plans. In this paper, a novel vision-based two-stage outer diameter detection method is proposed, including the segmentation and outer diameter calculation of greenhouse tomato images. To addres...Show More
Trajectory Planning Towards Water-Air Trans-Media Motion for Robotic Dolphin
2024 China Automation Congress (CAC)
Year: 2024 | Conference Paper |
Water-air trans-media navigators have multi-media motion modes, breaking through the limitation that traditional robots can only operate in a single medium. Autonomous navigation is an indispensable component of the process of transmedia motion. Most of the current work has only completed the development and testing of prototypes, and the problem of task-oriented motion planning and control needs ...Show More
Learning to Turn: Deformation Control of a Novel Flexible Fishtail Actuated by Artificial Muscles
2024 IEEE International Conference on Cyborg and Bionic Systems (CBS)
Year: 2024 | Conference Paper |
Achieving agile, fish-like turning remains a critical challenge in the development of robotic fish. The flexible deformation of a fish’s body significantly contributes to its turning ability. Consequently, researchers have devoted substantial efforts to enhancing the compliance and agility of robotic fish. This paper presents a novel flexible fishtail, inspired by the musculoskeletal structure of ...Show More
RIGNet: Robot Intention Grasp for Dense Stacked Targets With Multi-Task Siamese Schema Through RoIs Learning
Xungao Zhong;Tao Gong;Junzhi Yu;Chengxian Zhou;Xunyu Zhong;Qiang Liu
IEEE Transactions on Automation Science and Engineering
Year: 2024 | Early Access Article |
Autonomous grasping is a critical topic of robotic embodied intelligence. However, it remains challenging for robots to grasp an intended target, particularly in cluttered and densely stacked environments. This paper presents a novel solution by proposing a Robot Intention Grasp Network (RIGNet) with a multi-task siamese schema, which is based on an improved Region Proposal Network (RPN) and a Reg...Show More
An Extended Bandit-Based Game Scheme for Distributed Joint Resource Allocation in Underwater Acoustic Communication Networks
Jun Dai;Xinbin Li;Song Han;Junzhi Yu;Zhixin Liu;Tongwei Zhang
IEEE Transactions on Network and Service Management
Year: 2024 | Early Access Article |
This paper investigates a joint discrete-channel and continuous-power allocation problem for multi-user underwater acoustic communication networks. The unknown underwater acoustic Channel State Information (CSI) and the distributed optimization requirement make the proposed hybrid discrete-continuous optimization problem full of challenges. Firstly, an adversarial multi-player bandit game model is...Show More
Adaptive Trajectory Tracking Control for Small Unmanned Underwater Vehicles With Prescribed Performance and Dynamic Compensation
IEEE Transactions on Industrial Electronics
Year: 2024 | Early Access Article |
This article is concerned with the trajectory tracking control problem for small unmanned underwater vehicles (UUVs) with dynamic uncertainty, external disturbance, input saturation, and even unmeasured velocities. To guarantee transient and steady-state prescribed performance, a finite-time prescribed performance control (PPC) method is designed for the boundness and convergence of tracking error...Show More
Defocus Force-Guided Precision Autofocus of Hand–Eye Robot System
Xurong Gong;Xilong Liu;Zhiqiang Cao;Peiyu Guan;Liping Ma;Junzhi Yu
IEEE Transactions on Industrial Electronics
Year: 2024 | Early Access Article |
Autofocus is a crucial prerequisite for precision vision sensing of industrial workpieces. Existing methods mainly utilize image sharpness to guide single-axis camera adjustment for focusing. However, they fail to deal with larger workpieces with uneven surfaces, which require multidirection sensing. To solve this challenge, the focusing is abstracted as a force movement acting on the camera focus...Show More
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