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Suresh Sundaram - IEEE Xplore Author Profile

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Author details

Suresh Sundaram

Also published under: S. Sundaram

Publications

102

Citations

868

Publications by Year

20072025

Co-Authors:

Srikrishna AcharyaAayush AgrawalBharadwaj AmruturPrahlad AnandAbhay M. S. Aradhya

Show All Co-Authors (144)

Suresh Sundaram

Also published under: S. Sundaram

Affiliation

Department of Aerospace Engineering

Indian Institute of Science

Bangalore, India

Publication Topics

Neural Network,
Control Input,
Convolutional Neural Network,
Obstacle Avoidance,
Autonomous Vehicles,
Semantic Segmentation,
Autonomous Underwater Vehicles,
Deep Neural Network,
Model Predictive Control,
Numerical Simulations,
Optimal Control,
Partial Differential Equations

Biography

Suresh Sundaram (Senior Member, IEEE) received the B.E degree in electrical and electronics engineering from Bharathiyar University, Coimbatore, India, in 1999, and the M.E. and Ph.D. degrees from Indian Institute of Science, Bangalore, India, in 2001 and 2005, respectively, both in aerospace engineering.,He was an Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore, till October 2018. He is currently working as an Associate Professor with the Department of Aerospace, Indian Institute of Science, Bangalore, India. His current research interest includes flight control, unmanned aerial vehicle design, machine learning, applied game theory, optimization, and computer vision.(Based on document published on 6 March 2020).

Publications

102

Citations

868

Publications by Year

20072025

Co-Authors:

Srikrishna Acharya
Aayush Agrawal
Bharadwaj Amrutur
Prahlad Anand
Abhay M. S. Aradhya

Show All Co-Authors (144)

Author's Published Works

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Showing 1-25 of 138 results

Conferences (68)

Journals (65)

Early Access Articles (5)

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Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China(18)
College of Artificial Intelligence, Nankai University, Tianjin, China(11)
Institute of Robotics and Automatic Information System, Nankai University, Tianjin, China(10)
School of Information Science and Technology, Dalian Maritime University, Dalian, China(10)
Institute of Robotics and Automatic Information System (IRAIS), Nankai University, Tianjin, China(8)
IEEE Transactions on Industrial Electronics(15)
IEEE/ASME Transactions on Mechatronics(11)
IEEE Transactions on Automation Science and Engineering(9)
IEEE Robotics and Automation Letters(6)
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Lateral Control for UGVs by ADRC With Modeling Compensation and Expanded Disturbance Observation

Chenyang Zhao;Baoquan Li;Changfu Zhu;Wuxi Shi;Xuebo Zhang

IEEE Transactions on Industrial Electronics

Year: 2025 | Early Access Article |

By improving observer estimation accuracy, an active disturbance rejection control (ADRC) strategy is proposed for an unmanned ground vehicle (UGV), where dynamic performance is enhanced by disturbance suppression during trajectory tracking. In the strategy, part information of the lateral control model is added to the state matrix, so as to compensate estimation bias of UGV states from an extende...Show More

Lateral Control for UGVs by ADRC With Modeling Compensation and Expanded Disturbance Observation

Chenyang Zhao;Baoquan Li;Changfu Zhu;Wuxi Shi;Xuebo Zhang

IEEE Transactions on Industrial Electronics

Year: 2025 | Early Access Article |

FSMP: A Frontier-Sampling-Mixed Planner for Fast Autonomous Exploration of Complex and Large 3-D Environments

Shiyong Zhang;Xuebo Zhang;Qianli Dong;Ziyu Wang;Haobo Xi;Jing Yuan

IEEE Transactions on Instrumentation and Measurement

Year: 2025 | Early Access Article |

In this paper, we propose a systematic framework for fast exploration of complex and large 3-D environments using micro aerial vehicles (MAVs). The key insight is the organic integration of the frontier-based and sampling-based strategies that can achieve rapid global exploration of the environment. Specifically, a field-of-view-based (FOV) frontier detector with the guarantee of completeness and ...Show More

FSMP: A Frontier-Sampling-Mixed Planner for Fast Autonomous Exploration of Complex and Large 3-D Environments

Shiyong Zhang;Xuebo Zhang;Qianli Dong;Ziyu Wang;Haobo Xi;Jing Yuan

IEEE Transactions on Instrumentation and Measurement

Year: 2025 | Early Access Article |

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

IEEE Robotics and Automation Letters

Year: 2025 | Volume: 10, Issue: 4 | Journal Article |

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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

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

IEEE Robotics and Automation Letters

Year: 2025 | Volume: 10, Issue: 4 | Journal Article |

Optimized Feature Points and Keyframe Methods for VSLAM in High-Dynamic Indoor Environments

Zhuhua Hu;Wenlu Qi;Kunkun Ding;Hao Qi;Yaochi Zhao;Xuebo Zhang;Mingfeng Wang

IEEE Transactions on Intelligent Transportation Systems

Year: 2025 | Volume: 26, Issue: 3 | Journal Article |

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VSLAM is one of the key technologies for indoor mobile robots, used to perceive the surrounding environment, achieve accurate positioning and mapping. However, traditional VSLAM algorithms based on the assumption of a static environment still face certain challenges. The movement, occlusion, and appearance changes of dynamic objects can lead to feature point-matching errors, making data associatio...Show More

Optimized Feature Points and Keyframe Methods for VSLAM in High-Dynamic Indoor Environments

Zhuhua Hu;Wenlu Qi;Kunkun Ding;Hao Qi;Yaochi Zhao;Xuebo Zhang;Mingfeng Wang

IEEE Transactions on Intelligent Transportation Systems

Year: 2025 | Volume: 26, Issue: 3 | Journal Article |

Adaptive Robust Interaction Force Control of a Robotic Manipulator in Uncertain Environments

Junsheng Huang;Mingxing Yuan;Zixuan Huo;Shuaikang Zhang;Xuebo Zhang

IEEE Transactions on Industrial Electronics

Year: 2025 | Early Access Article |

This article presents a novel adaptive robust interaction force control approach that aims to achieve accurate and robust force modulation of a robot manipulator in uncertain environments. First, a novel interaction model between manipulator and environment is developed that captures both structured and unstructured uncertainties. According to the developed interaction model, a two-loop control sc...Show More

Adaptive Robust Interaction Force Control of a Robotic Manipulator in Uncertain Environments

Junsheng Huang;Mingxing Yuan;Zixuan Huo;Shuaikang Zhang;Xuebo Zhang

IEEE Transactions on Industrial Electronics

Year: 2025 | Early Access Article |

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

IEEE Transactions on Vehicular Technology

Year: 2025 | Volume: 74, Issue: 3 | Journal Article |

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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

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

IEEE Transactions on Vehicular Technology

Year: 2025 | Volume: 74, Issue: 3 | Journal Article |

G²VD Planner: Efficient Motion Planning With Grid-Based Generalized Voronoi Diagrams

Jian Wen;Xuebo Zhang;Qingchen Bi;Hui Liu;Jing Yuan;Yongchun Fang

IEEE Transactions on Automation Science and Engineering

Year: 2025 | Volume: 22 | Journal Article |

Cited by: Papers (1)

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In this paper, an efficient motion planning approach with grid-based generalized Voronoi diagrams (G2VD) is newly proposed for mobile robots. Different from existing approaches, the novelty of this work is twofold: 1) a new state lattice-based path searching approach is proposed, in which the search space is reduced to a novel Voronoi corridor to further improve the search efficiency; 2) an effici...Show More

G²VD Planner: Efficient Motion Planning With Grid-Based Generalized Voronoi Diagrams

Jian Wen;Xuebo Zhang;Qingchen Bi;Hui Liu;Jing Yuan;Yongchun Fang

IEEE Transactions on Automation Science and Engineering

Year: 2025 | Volume: 22 | Journal Article |

SGS-Planner: A Skeleton-Guided Spatiotemporal Motion Planner for Flight in Constrained Space

Tianyi Li;Shiyong Zhang;Xuebo Zhang;Qianli Dong;Junsheng Huang

IEEE/ASME Transactions on Mechatronics

Year: 2025 | Volume: 30, Issue: 1 | Journal Article |

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This article proposes a skeleton-guided spatiotemporal motion planner (SGS-Planner) for safe and efficient aerial robot navigation in challenging constrained space. The planner takes advantage of a spatial-temporal hierarchical framework to generate a safer and more efficient trajectory rapidly. In spatial planning, different from existing approaches that either ignore the clearance between trajec...Show More

SGS-Planner: A Skeleton-Guided Spatiotemporal Motion Planner for Flight in Constrained Space

Tianyi Li;Shiyong Zhang;Xuebo Zhang;Qianli Dong;Junsheng Huang

IEEE/ASME Transactions on Mechatronics

Year: 2025 | Volume: 30, Issue: 1 | Journal Article |

Visibility-Enhanced Elastic Tracker Algorithm for Stable and Flexible Aerial Tracking

Ziyu Wang;Shiyong Zhang;Haobo Xi;Tianyi Li;Xuebo Zhang

2024 IEEE International Conference on Unmanned Systems (ICUS)

Year: 2024 | Conference Paper |

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This paper proposes the visibility-enhanced Elastic Tracker algorithm to address the line-of-sight occlusion problem presented in previous algorithms for target tracking with unmanned aerial vehicles (UAV). The path generated by the traditional A* algorithm often provides poor visibility for the UAV to track its target. To relieve this issue, we introduce a novel visibility heuristic function that...Show More

Visibility-Enhanced Elastic Tracker Algorithm for Stable and Flexible Aerial Tracking

Ziyu Wang;Shiyong Zhang;Haobo Xi;Tianyi Li;Xuebo Zhang

2024 IEEE International Conference on Unmanned Systems (ICUS)

Year: 2024 | Conference Paper |

LRAE: Large-Region-Aware Safe and Fast Autonomous Exploration of Ground Robots for Uneven Terrains

Qingchen Bi;Xuebo Zhang;Shiyong Zhang;Runhua Wang;Lun Li;Jing Yuan

IEEE Robotics and Automation Letters

Year: 2024 | Volume: 9, Issue: 12 | Journal Article |

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Ground robot autonomous exploration for uneven terrains is still challenging since the rugged terrain structures not only degrade the exploration performance but also threaten the navigation safety of the robot. In this letter, a novel exploration planner is proposed for safe and fast exploration in uneven terrains. To obtain high exploration efficiency, we propose a large-region-aware exploration...Show More

LRAE: Large-Region-Aware Safe and Fast Autonomous Exploration of Ground Robots for Uneven Terrains

Qingchen Bi;Xuebo Zhang;Shiyong Zhang;Runhua Wang;Lun Li;Jing Yuan

IEEE Robotics and Automation Letters

Year: 2024 | Volume: 9, Issue: 12 | Journal Article |

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 |

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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

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 |

TC$^{2}$LI-SLAM: A Tightly-Coupled Camera-LiDAR-Inertial SLAM System

Yunze Tong;Xuebo Zhang;Runhua Wang;Zhixing Song;Songyang Wu;Shiyong Zhang;Youwei Wang;Jing Yuan

IEEE Robotics and Automation Letters

Year: 2024 | Volume: 9, Issue: 9 | Journal Article |

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In this letter, we propose TC$^{2}$LI-SLAM, a novel and tightly-coupled camera-LiDAR-inertial SLAM system with a separated front end and a unified back end. The front end accepts non-identical frequency inputs and performs real-time pose estimation while incorporating different inputs into keyframes for the back end, benefiting from our novel keyframe-oriented data synchronization method. To impro...Show More

TC$^{2}$LI-SLAM: A Tightly-Coupled Camera-LiDAR-Inertial SLAM System

Yunze Tong;Xuebo Zhang;Runhua Wang;Zhixing Song;Songyang Wu;Shiyong Zhang;Youwei Wang;Jing Yuan

IEEE Robotics and Automation Letters

Year: 2024 | Volume: 9, Issue: 9 | Journal Article |

MPOC-SLAM: An RGB-D SLAM System With Motion Probability and Object Category in High Dynamic Environments

Songyang Wu;Xuebo Zhang;Shiyong Zhang;Zhixing Song;Runhua Wang;Jing Yuan

IEEE/ASME Transactions on Mechatronics

Year: 2024 | Early Access Article |

The performance of simultaneous localization and mapping (SLAM) is significantly impacted by dynamic objects. Existing dynamic SLAM methods still suffer from some major issues, such as insufficient use of semantic information, losing track when dynamic objects occupy the field of view, and inability to achieve real-time processing. In this article, we present SLAM with motion probability and objec...Show More

MPOC-SLAM: An RGB-D SLAM System With Motion Probability and Object Category in High Dynamic Environments

Songyang Wu;Xuebo Zhang;Shiyong Zhang;Zhixing Song;Runhua Wang;Jing Yuan

IEEE/ASME Transactions on Mechatronics

Year: 2024 | Early Access Article |

Target-Free and User-Friendly Online Extrinsic Calibration of LiDAR-IMU-Camera Systems Guided by Motion Excitation Assessment

Youwei Wang;Xuebo Zhang;Runhua Wang;Zhixing Song;Shiyong Zhang;Yunze Tong

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Early Access Article |

Cited by: Papers (1)

Robust and reliable calibration forms the foundation of efficient multi-sensor fusion. Most existing calibration methods are offline and rely on artificial targets, which is time consuming and unfriendly to non-expert users. To improve efficiency, robustness and user-friendliness, this paper proposes a novel target-free LiDAR-IMU-camera online extrinsic calibration framework. An IMU-centric motion...Show More

Target-Free and User-Friendly Online Extrinsic Calibration of LiDAR-IMU-Camera Systems Guided by Motion Excitation Assessment

Youwei Wang;Xuebo Zhang;Runhua Wang;Zhixing Song;Shiyong Zhang;Yunze Tong

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Early Access Article |

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

IEEE Transactions on Industrial Electronics

Year: 2024 | Volume: 71, Issue: 12 | Journal Article |

Cited by: Papers (1)

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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

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

IEEE Transactions on Industrial Electronics

Year: 2024 | Volume: 71, Issue: 12 | Journal Article |

Manipulability-Augmented Next-Best-Configuration Exploration Planner for High-DoF Manipulators

Xin Liu;Xuebo Zhang;Shiyong Zhang;Mingxing Yuan;Jingjin Yu

IEEE Robotics and Automation Letters

Year: 2024 | Volume: 9, Issue: 5 | Journal Article |

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This letter presents MA-NBCP, a novel hierarchical framework targeting autonomous exploration and inspection for high-DoF manipulators. MA-NBCP iteratively selects the manipulability-augmented next-best-configuration for exploring unknown regions surrounding a manipulator, while providing collision-avoidance guarantee. Toward developing MA-NBCP, an efficient exploration information system (EIS) is...Show More

Manipulability-Augmented Next-Best-Configuration Exploration Planner for High-DoF Manipulators

Xin Liu;Xuebo Zhang;Shiyong Zhang;Mingxing Yuan;Jingjin Yu

IEEE Robotics and Automation Letters

Year: 2024 | Volume: 9, Issue: 5 | Journal Article |

Safety-Driven and Localization Uncertainty-Driven Perception-Aware Trajectory Planning for Quadrotor Unmanned Aerial Vehicles

Gang Sun;Xuetao Zhang;Yisha Liu;Xuebo Zhang;Yan Zhuang

IEEE Transactions on Intelligent Transportation Systems

Year: 2024 | Volume: 25, Issue: 8 | Journal Article |

Cited by: Papers (1)

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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

Safety-Driven and Localization Uncertainty-Driven Perception-Aware Trajectory Planning for Quadrotor Unmanned Aerial Vehicles

Gang Sun;Xuetao Zhang;Yisha Liu;Xuebo Zhang;Yan Zhuang

IEEE Transactions on Intelligent Transportation Systems

Year: 2024 | Volume: 25, Issue: 8 | Journal Article |

Autopilot Controller of Fixed-Wing Planes Based on Curriculum Reinforcement Learning Scheduled by Adaptive Learning Curve

Lun Li;Xuebo Zhang;Chenxu Qian;Runhua Wang;Minghui Zhao

IEEE Transactions on Emerging Topics in Computational Intelligence

Year: 2024 | Volume: 8, Issue: 3 | Journal Article |

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In this paper, we present a novel curriculum reinforcement learning method that can automatically generate a high-performance autopilot controller for a 6-degree-of-freedom (6-DOF) aircraft with an unknown dynamic model, which is difficult to be handled using traditional control methods. In this method, a sigmoid-like learning curve is elegantly introduced to generate goals (the desired heading, a...Show More

Autopilot Controller of Fixed-Wing Planes Based on Curriculum Reinforcement Learning Scheduled by Adaptive Learning Curve

Lun Li;Xuebo Zhang;Chenxu Qian;Runhua Wang;Minghui Zhao

IEEE Transactions on Emerging Topics in Computational Intelligence

Year: 2024 | Volume: 8, Issue: 3 | Journal Article |

LIVER: A Tightly Coupled LiDAR-Inertial-Visual State Estimator With High Robustness for Underground Environments

Tianci Wen;Yongchun Fang;Biao Lu;Xuebo Zhang;Chaoquan Tang

IEEE Robotics and Automation Letters

Year: 2024 | Volume: 9, Issue: 3 | Journal Article |

Cited by: Papers (3)

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In this letter, we propose a tightly coupled LiDAR-inertial-visual (LIV) state estimator termed LIVER, which achieves robust and accurate localization and mapping in underground environments. LIVER starts with an effective strategy for LIV synchronization. A robust initialization process that integrates LiDAR, vision, and IMU is realized. A tightly coupled, nonlinear optimization-based method achi...Show More

LIVER: A Tightly Coupled LiDAR-Inertial-Visual State Estimator With High Robustness for Underground Environments

Tianci Wen;Yongchun Fang;Biao Lu;Xuebo Zhang;Chaoquan Tang

IEEE Robotics and Automation Letters

Year: 2024 | Volume: 9, Issue: 3 | Journal Article |

FGIP: A Frontier-Guided Informative Planner for UAV Exploration and Reconstruction

Xuetao Zhang;Xiaotian Xu;Yisha Liu;Hanzhang Wang;Xuebo Zhang;Yan Zhuang

IEEE Transactions on Industrial Informatics

Year: 2024 | Volume: 20, Issue: 4 | Journal Article |

Cited by: Papers (4)

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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

FGIP: A Frontier-Guided Informative Planner for UAV Exploration and Reconstruction

Xuetao Zhang;Xiaotian Xu;Yisha Liu;Hanzhang Wang;Xuebo Zhang;Yan Zhuang

IEEE Transactions on Industrial Informatics

Year: 2024 | Volume: 20, Issue: 4 | Journal Article |

CVR-LSE: Compact Vectorized Representation of Local Static Environments for Reliable Obstacle Detection

Haiming Gao;Qibo Qiu;Wei Hua;Xuebo Zhang;Zhiyi Su;Shun Zhang

IEEE Transactions on Industrial Electronics

Year: 2024 | Volume: 71, Issue: 8 | Journal Article |

Cited by: Papers (1)

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This article proposes a compact vectorized representation approach to realize reliable obstacle detection for autonomous ground vehicles. Bridging the gap between the advantage of occupancy grid map in general obstacle detection and its shortcomings in memory-consuming and computational cost, a novel obstacle representation by multiple convex polygons is first proposed. Specially, to overcome the ...Show More

CVR-LSE: Compact Vectorized Representation of Local Static Environments for Reliable Obstacle Detection

Haiming Gao;Qibo Qiu;Wei Hua;Xuebo Zhang;Zhiyi Su;Shun Zhang

IEEE Transactions on Industrial Electronics

Year: 2024 | Volume: 71, Issue: 8 | Journal Article |

NALO-VOM: Navigation-Oriented LiDAR-Guided Monocular Visual Odometry and Mapping for Unmanned Ground Vehicles

Ziqi Hu;Jing Yuan;Yuanxi Gao;Boran Wang;Xuebo Zhang

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Volume: 9, Issue: 1 | Journal Article |

Cited by: Papers (8)

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Monocular visual odometry (VO) is a fundamental technique for unmanned ground vehicle (UGV) navigation. However, traditional monocular VO methods always suffer from sparse environment maps which cannot be directly used for navigation because of the lack of structural information. In this article, we propose a navigation-oriented LiDAR-guided monocular visual odometry and mapping (NALO-VOM) to obta...Show More

NALO-VOM: Navigation-Oriented LiDAR-Guided Monocular Visual Odometry and Mapping for Unmanned Ground Vehicles

Ziqi Hu;Jing Yuan;Yuanxi Gao;Boran Wang;Xuebo Zhang

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Volume: 9, Issue: 1 | Journal Article |

Visual Servoing Trajectory Tracking and Depth Identification for Mobile Robots With Velocity Saturation Constraints

Runhua Wang;Zhejin Zhu;Xuebo Zhang;Yongchun Fang;Baoquan Li

IEEE Transactions on Industrial Electronics

Year: 2024 | Volume: 71, Issue: 6 | Journal Article |

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This article proposes a novel visual servoing trajectory tracking controller satisfying velocity saturation constraints for mobile robots, which can simultaneously realize the unknown image depth identification. Compared with existing saturation controllers, the boundness of velocity commands can be explicitly determined, although the control law is coupled with the unknown depth. In addition, the...Show More

Visual Servoing Trajectory Tracking and Depth Identification for Mobile Robots With Velocity Saturation Constraints

Runhua Wang;Zhejin Zhu;Xuebo Zhang;Yongchun Fang;Baoquan Li

IEEE Transactions on Industrial Electronics

Year: 2024 | Volume: 71, Issue: 6 | Journal Article |

CURE: A Hierarchical Framework for Multi-Robot Autonomous Exploration Inspired by Centroids of Unknown Regions

Qingchen Bi;Xuebo Zhang;Jian Wen;Zhangchao Pan;Shiyong Zhang;Runhua Wang;Jing Yuan

IEEE Transactions on Automation Science and Engineering

Year: 2024 | Volume: 21, Issue: 3 | Journal Article |

Cited by: Papers (12)

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In this paper, a novel multi-robot autonomous exploration approach CURE is proposed based on dynamic Voronoi diagrams and centroids of unknown connected regions. Compared with existing approaches, the novelty of this work is twofold: 1) Dynamic Voronoi diagram is used for partition of the space being explored to improve the efficiency of multi-robot exploration, and then a new parameter-insensitiv...Show More

CURE: A Hierarchical Framework for Multi-Robot Autonomous Exploration Inspired by Centroids of Unknown Regions

Qingchen Bi;Xuebo Zhang;Jian Wen;Zhangchao Pan;Shiyong Zhang;Runhua Wang;Jing Yuan

IEEE Transactions on Automation Science and Engineering

Year: 2024 | Volume: 21, Issue: 3 | Journal Article |

SVPTO: Safe Visibility-Guided Perception-Aware Trajectory Optimization for Aerial Tracking

Hanzhang Wang;Xuetao Zhang;Yisha Liu;Xuebo Zhang;Yan Zhuang

IEEE Transactions on Industrial Electronics

Year: 2024 | Volume: 71, Issue: 3 | Journal Article |

Cited by: Papers (5)

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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

SVPTO: Safe Visibility-Guided Perception-Aware Trajectory Optimization for Aerial Tracking

Hanzhang Wang;Xuetao Zhang;Yisha Liu;Xuebo Zhang;Yan Zhuang

IEEE Transactions on Industrial Electronics

Year: 2024 | Volume: 71, Issue: 3 | Journal Article |

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