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Spatial and Temporal Calibration of Self-built Panoramic LiDAR in Targetless Environments
IEEE Transactions on Instrumentation and Measurement
Year: 2025 | Early Access Article |
Compared to multi-line LiDAR, panoramic LiDAR offers a larger field of view (FOV) and is widely used for tracking and mapping applications. Accurate calibration is essential for acquiring precise panoramic point clouds. However, current calibration methods often depend on a calibration board and overlook the time offset between sensors. To address these limitations, we propose a novel spatiotempor...Show More
Density Adaptive Registration of Large-Scale Point Clouds in Diverse Outdoor Environments
IEEE Robotics and Automation Letters
Year: 2025 | Early Access Article |
Point cloud registration is the foundation of collaborative multi-robot mapping tasks in outdoor environments. Due to the dynamic changes in communication bandwidth, the density of point clouds transmitted from the robot to the server will also change simultaneously, which will significantly affect the point cloud registration accuracy and even lead to the failure of collaborative mapping. To addr...Show More
Insulators Defect Detection for Power Grid Based on Improved Yolov7 Algorithm
2025 13th International Conference on Intelligent Control and Information Processing (ICICIP)
Year: 2025 | Conference Paper |
High-current out-of-phase closed bus is an essential link in the transmission of electric energy and is widely used in thermal power stations, hydropower stations and nuclear power plants. Although these busbars have the advantages of excellent dustproof effect and strong magnetic shielding, they are susceptible to insulator aging and damage in long-term operation, posing a potential safety risk t...Show More
Low-Light Enhancement and Global-Local Feature Interaction for RGB-T Semantic Segmentation
The performance of RGB-T semantic segmentation tasks is affected by the quality of visible (VIS) and infrared (IR) images captured by sensor instruments. In low-light environments, various degradation factors lead to the poor quality of captured VIS and IR images, ultimately reducing the performance of subsequent semantic segmentation tasks. To address this issue, we propose a novel RGB-T semantic...Show More
CLID-SLAM: A Coupled LiDAR-Inertial Neural Implicit Dense SLAM With Region-Specific SDF Estimation
Junlong Jiang;Xuetao Zhang;Gang Sun;Yisha Liu;Xuebo Zhang;Yan Zhuang
This letter proposes a novel scan-to-neural model matching, tightly-coupled LiDAR-inertial Simultaneous Localization and Mapping (SLAM) system, which can achieve more accurate state estimation and incrementally reconstruct the dense map. Different from the existing methods, the key insight of the proposed approach is that region-specific Signed Distance Function (SDF) estimations supervise the neu...Show More
Semantic-Driven Informed Planning and 3D Reconstruction for the Quadrotor Unmanned Aerial Vehicle
Xiaotian Xu;Xuetao Zhang;Yisha Liu;Hanzhang Wang;Xuebo Zhang;Yan Zhuang
Autonomous aerial reconstruction tackles the problem of deploying the quadrotor unmanned aerial vehicle in an unknown environment for vision-based surface reconstruction. The state-of-the-art methods mainly extend the classic next-best-view (NBV) framework with the semantic information to concentrate on the reconstruction target. However, the greedy decision of the next viewpoint or branch without...Show More
A Multi-UAV Monitoring and Search Strategy Based on Multi-Agent Reinforcement Learning
Shuyi Guo;Xuetao Zhang;Hanzhang Wang;Gang Sun;Yisha Liu;Yan Zhuang
2024 IEEE International Conference on Unmanned Systems (ICUS)
Year: 2024 | Conference Paper |
Multiple UAVs have been widely used for targets search and monitoring. Nonetheless, in practice, this problem is challenging as targets usually move randomly, but the trajectories of the targets cannot be predicted in advance by UAV swarms. Moreover, the efficiency of exploration, which indirectly impacts monitoring, is low when the number of targets in the environment is unknown. A Search Extende...Show More
MUP-LIO: Mapping Uncertainty-aware Point-wise Lidar Inertial Odometry
Hekai Yao;Xuetao Zhang;Gang Sun;Yisha Liu;Xuebo Zhang;Yan Zhuang
2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2024 | Conference Paper |
This paper proposes a mapping uncertainty-aware point-wise Lidar Inertial Odometry (LIO), which synthesizes the point-wise point-to-plane match and map refreshment into a probabilistic model. As a result, it can address the issue of mismatching during point registration and remove in-frame motion distortion of Lidar sensors. Specifically, the uncertainty-aware map is designed to embody the uncerta...Show More
A Real-Time and Lightweight Monocular 3-D Object Detector on CPU-Based Edge Devices for UGV's Indoor SLAM Systems
IEEE/ASME Transactions on Mechatronics
Year: 2024 | Early Access Article |
In this article, we introduce RLMono3d, a real-time monocular 3-D object detector designed to run efficiently on edge devices with just one CPU. This approach is specifically applied to the indoor simultaneous localization and mapping (SLAM) system on the unmanned ground vehicle (UGV) platform. The spatial projection model for 3-D cuboids is proposed using projective geometry to determine the topo...Show More
CIGF-Net: Cross-Modality Interaction and Global-Feature Fusion for RGB-T Semantic Segmentation
IEEE Transactions on Emerging Topics in Computational Intelligence
Year: 2024 | Early Access Article |
RGB-T semantic segmentation aims to enhance the robustness of segmentation methods in complex environments by utilizing thermal information. To facilitate the effective interaction and fusion of multimodal information, we propose a novel Cross-modality Interaction and Global-feature Fusion Network, namely CIGF-Net. In each feature extraction stage, we propose a Cross-modality Interaction Module (C...Show More
Nonlinear Control of a Fully-Actuated Hexacopter with a Cable-Suspended Load
Zhicheng Li;Hanzhang Wang;Xuetao Zhang;Yisha Liu;Xuebo Zhang;Yan Zhuang
2024 14th Asian Control Conference (ASCC)
Year: 2024 | Conference Paper |
This paper introduces a novel nonlinear controller to address load transportation problems of fully-actuated un-manned aerial vehicle (UAV). Unlike existing controllers, this controller employs a layered structure, where the outer loop controls the payload and its speed, while the inner loop controls the attitude of the load. Given the full actuation of the UAV, translation and attitude are separa...Show More
A Novel Teacher–Student Framework With Degradation Model for Infrared–Visible Image Fusion
The fusion performance of infrared (IR) and visible (VIS) images depends on the quality of the source images, which are often affected by some factors in real-world scenarios, such as environmental changes, hardware limitations, and image compression. The influence of these factors can be minimized by training a neural network capable of generating high-quality (HQ) fused images from low-quality (...Show More
A Tightly-Coupled and Keyframe-Based Visual-Inertial-Lidar Odometry System for UGVs With Adaptive Sensor Reliability Evaluation
In this article, a novel visual-inertial-lidar odometry (VILO) system named TCK-VILO is proposed to assist unmanned ground vehicles in reaching high localization performance. We introduce an adaptive sensor reliability evaluation method to configure weights of visual and lidar measurements dynamically in the backend optimization, which can improve both the accuracy and robustness of the localizati...Show More
FLM PL-VIO: A Robust Monocular Point-Line Visual-Inertial Odometry Based on Fast Line Matching
Shuyue Lin;Xuetao Zhang;Yisha Liu;Hanzhang Wang;Xuebo Zhang;Yan Zhuang
This article proposes a monocular point-line visual-inertial odometry (VIO) with line filtering and fast line matching (FLM PL-VIO), improving the localization accuracy and robustness. Different from the existing point-line VIO frameworks, we construct a new line filter to make the line features uniformly distributed, providing better spatial geometric constraints. In addition, we propose a fast l...Show More
Safety-Driven and Localization Uncertainty-Driven Perception-Aware Trajectory Planning for Quadrotor Unmanned Aerial Vehicles
Recent advances in trajectory planning have enabled quadrotor unmanned aerial vehicles (UAVs) to navigate autonomously in complex environments. However, most of the existing methods do not consider the perception quality and the safety simultaneously. This article proposes a perception-aware trajectory planning strategy for quadrotors, which can ensure the safety and localization accuracy. In cont...Show More
FGIP: A Frontier-Guided Informative Planner for UAV Exploration and Reconstruction
Xuetao Zhang;Xiaotian Xu;Yisha Liu;Hanzhang Wang;Xuebo Zhang;Yan Zhuang
This article proposes a frontier-guided informative planner for unmanned aerial vehicle volumetric exploration and 3-D reconstruction, which can explore a complex unknown environment and provide the accurate truncated signed distance function reconstruction simultaneously. Different from the existing methods, the key insight of the proposed method is that the hybrid surface frontier is proposed to...Show More
Automated Model-Based Assurance Case Management Using Constrained Natural Language
Ran Wei;Zhe Jiang;Haitao Mei;Konstantinos Barmpis;Simon Foster;Tim Kelly;Yan Zhuang
Assurance cases are used to communicate and assess confidence in critical system properties, e.g., safety and security. Historically, assurance cases have been manually created documents, validated by engineers through lengthy and error-prone processes. Recently, system assurance practitioners have begun adopting model-based approaches to improve the efficiency and quality of system assurance acti...Show More
SVPTO: Safe Visibility-Guided Perception-Aware Trajectory Optimization for Aerial Tracking
In this article, we propose a safe visibility-guided perception-aware trajectory optimization method for aerial tracking, which can handle occlusion and collision in complex environments simultaneously. Different from the existing methods, the key idea of the proposed method is to actively adjust the relative distance and angle between the quadrotor and the target to avoid occlusion and collision ...Show More
Application of Improved MTP A Flux-weakening Control in Omnidirectional All-wheel Drive Robot
2023 3rd International Conference on Electrical Engineering and Control Science (IC2ECS)
Year: 2023 | Conference Paper |
The omnidirectional all-wheel drive mobile robot supports single-wheel independent drive and steering, so it can adapt to complex and changeable terrain conditions by multiple sports modes. In the design of omnidirectional all-wheel drive mobile robot, engineers usually use flux-weakening control to improve the dynamic performance of Permanent Magnet Synchronous Motor (PMSM), so as to achieve bett...Show More
MAPPG: Multi-Agent Phasic Policy Gradient
2023 62nd IEEE Conference on Decision and Control (CDC)
Year: 2023 | Conference Paper |
We propose a Multi-Agent Phasic Policy Gradient (MAPPG) algorithm, which can assist agents to further alleviate the non-stationarity of the environment. Different from the existing methods, the auxiliary phase is introduced to train the local policy directly by using the environment state, which can be naturally integrated into other algorithms. Specifically, the hidden layer feature sharing is pr...Show More
Semantic Topology and Global Descriptors Based Localization for UGV in Prior Air-View Map
2023 13th International Conference on Information Science and Technology (ICIST)
Year: 2023 | Conference Paper |
The localization for Unmanned Ground Vehicle (U G V) in prior aerial view map remains a challenging task due to the inherent difficulty in generating descriptors that are both effective and robust to occlusion and viewpoint changes. In contrast to the majority of existing methods that primarily concentrate on extracting local and global features from raw point clouds, our approach combines semanti...Show More
Weakly Supervised Semantic Segmentation for Point Clouds with Self-Purification on Pseudo Labels
2023 13th International Conference on Information Science and Technology (ICIST)
Year: 2023 | Conference Paper |
Currently, research in the field about point cloud semantic segmentation primarily focuses on fully supervised learning, which requires expensive manual point-level annotations. Weakly supervised learning is an approach to overcome the time and effort required for such annotations. However, for large-scale point clouds with limited labeled points, it is challenging for networks to learn the differ...Show More
Topology-Guided Perception-Aware Receding Horizon Trajectory Generation for UAVs
Gang Sun;Xuetao Zhang;Yisha Liu;Hanzhang Wang;Xuebo Zhang;Yan Zhuang
2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
The perception-aware motion planning method based on the localization uncertainty has the potential to improve the localization accuracy for robot navigation. How-ever, most of the existing perception-aware methods pre-build a global feature map and can not generate the perception- aware trajectory in real time. This paper proposes a topology- guided perception-aware receding horizon trajectory ge...Show More
Active Informative Receding Horizon Planning for Quadrotors
2023 42nd Chinese Control Conference (CCC)
Year: 2023 | Conference Paper |
Motion planning for quadrotors is still a challenging problem due to the uncertainty and complexity of the environment. In this context, we propose an active informative receding horizon trajectory generation method that incorporates the informative path planning and B-spline-based trajectory optimization to achieve a smooth, safe, and efficient trajectory for UAVs. The proposed method includes an...Show More
Point-Voxel Fusion for 3D Object Detection
2023 42nd Chinese Control Conference (CCC)
Year: 2023 | Conference Paper |
In 3D object detection, network prediction accuracy is greatly affected by point cloud's feature richness. However, the feature richness depends on fine-grained features extracted by the network. Currently some methods use voxel encoding approach continuously down-scaled by 3D convolution to improve the detection efficiency, but lose too many fine-grained features. Some methods directly inputting ...Show More
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