Article
Robotics
Daniil Lisus, Charles Champagne Cossette, Mohammed Shalaby, James Richard Forbes
Summary: This letter demonstrates how to estimate robot heading using UWB range and RSS measurements, by learning a data-driven relationship and combining with a gyroscope and an invariant extended Kalman filter.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Robotics
Kailai Li, Ziyu Cao, Uwe D. Hanebeck
Summary: We present a novel framework for continuous-time ultra-wideband-inertial sensor fusion for motion estimation in real-time. This framework utilizes quaternion-based cubic cumulative B-splines for continuous parameterization of motion states. Additionally, systematic derivations for analytic kinematic interpolations and spatial differentiations are provided. The proposed system, SFUISE, is evaluated using public data sets and experiments, showcasing superior performance compared to state-of-the-art discrete-time schemes. The source code and experimental data are available at https://github.com/KIT-ISAS/SFUISE.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Chemistry, Analytical
Chunxu Li, Henry Bulman, Toby Whitley, Shaoxiang Li
Summary: This paper explores the use of beacon-based localization with ultra-wideband technology for a robot to work within its environment and with other robots. The author presents an innovative solution for a sensor fusion platform and successfully tests it in different environments.
Article
Robotics
Sven Pfeiffer, Christophe de Wagter, Guido C. H. E. de Croon
Summary: Our computationally efficient moving horizon estimator enables real-time localization on small quadrotors using Ultra-Wideband measurements, outperforming the state-of-the-art Extended Kalman Filter in handling heavy-tailed noise commonly encountered in Ultra-Wideband ranging. Additionally, the algorithm's performance is analyzed when reducing the number of beacons for measurements, and it is successfully implemented on a 30 g Crazyflie drone to demonstrate its ability to run on computationally limited devices.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Robotics
Cedric Le Gentil, Teresa Vidal-Calleja, Shoudong Huang
Summary: This article introduces an offline probabilistic framework for localization, mapping, and extrinsic calibration based on a 3-D lidar and a six-degree-of-freedom inertial measurement unit. The proposed method leverages preintegration and full batch optimization to eliminate motion distortion, achieving automatic calibration and registration of lidar data.
IEEE TRANSACTIONS ON ROBOTICS
(2021)
Article
Remote Sensing
Abhishek Gupta, Xavier Fernando
Summary: This article surveys the use of SLAM and data fusion techniques in UAVs for object detection and environmental scene perception. It evaluates current SLAM implementations and their applicability in robotics and autonomous vehicles for UAV navigation. The findings highlight the crucial role of SLAM and data fusion for UAV navigation and suggest future research avenues in this area.
Article
Computer Science, Artificial Intelligence
Fabrizio Romanelli, Francesco Martinelli, Simone Mattogno
Summary: This paper discusses a solution to the Simultaneous Localization and Mapping (SLAM) problem for a moving agent using Visual Odometry (VO) and Ultra Wide Band (UWB) antennas. The proposed approach utilizes a switching observer and a Robust EKF algorithm to achieve comparable performance to a VO algorithm even before closing the loop. It also includes a resilient module to evaluate the reliability of the position estimation. The approach is robust to unmodeled disturbances and adapts to sensor failures.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2023)
Article
Robotics
Yan Wang, Hongwei Ma
Summary: We propose mVIL-Fusion, a three-level multisensor fusion system that achieves robust state estimation and globally consistent mapping in perceptually degraded environments. Our system uses LiDAR depth-assisted visual-inertial odometry (VIO) as the frontend, with synchronous prediction and distortion correction functions. It also applies a novel double-sliding-window-based optimization to enhance state estimation accuracy and robustness. Loop closures and pose-only factor graph smoothing are used in the backend to generate a global map. The system has been validated on public datasets and self-collected sequences.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Automation & Control Systems
Fabrizio Romanelli, Francesco Martinelli, Emidio Di Giampaolo
Summary: This article discusses an indoor simultaneous localization and mapping problem for a mobile robot using passive radio ultra high frequency identification (ID) tags. The solution approach involves a multihypothesis extended Kalman filter to estimate the range and bearing of the observed tags, and an extended Kalman filter to solve the SLAM problem. Experimental results show that the proposed approach is robust against various disturbances.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Ang Liu, Shiwei Lin, Jianguo Wang, Xiaoying Kong
Summary: This study proposes a fusion mechanism that integrates UWB with an odometer sensor to achieve high-precision indoor positioning in complex environments. The sliding window method is used to effectively identify NLOS anchors and a loosely coupled approach named DDF is designed to correct cumulative errors and improve positioning accuracy.
Article
Robotics
Jinxin Liu, Guoqiang Hu
Summary: Most distributed algorithms for robot coordination rely on relative location information, which remains a primary challenge in multi-robot applications. In this study, we propose the use of a rotating ultra-wideband tag to provide persistent excitation and two estimation algorithms for obtaining relative locations in a distributed manner. Our approach only requires on-board sensors and a single ultra-wideband tag per robot, eliminating the need for ground anchors and enabling deployment in GNSS-denied environments without range restrictions. The effectiveness of our proposed approach is validated through simulations and experiments.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Chemistry, Analytical
Anweshan Das, Jos Elfring, Gijs Dubbelman
Summary: In this study, a real-time multi-sensor fusion framework based on pose-graph optimization for vehicle positioning using low-cost sensors was proposed and evaluated. The framework outperformed automotive-grade GNSS receivers by reducing localization error standard deviation by 20.86% and significantly decreasing outliers.
Article
Computer Science, Artificial Intelligence
Vu Phi Tran, Matthew A. Garratt, Kathryn Kasmarik, Sreenatha G. Anavatti, Alex S. Leong, Mohammad Zamani
Summary: This paper presents a novel flocking control strategy for multi-robot exploration and gas field mapping, which includes an active sensing mechanism and a collaborative sequential Monte Carlo information fusion approach. The proposed strategy outperforms recent single-agent and centralized sequential Monte Carlo-based gas concentration mapping in terms of estimate accuracy, convergence time, and mapping error.
INFORMATION FUSION
(2023)
Article
Automation & Control Systems
Wenhan Zhang, Wei Cui, Xingguang Li, Mingzhi Xu, Chensong Wang
Summary: In indoor environments with attenuated GPS signals, UWB and 2D lidar are commonly used for autonomous positioning of mobile platforms. However, NLOS environments can cause large errors in UWB positioning, while 2D lidar can increase cumulative error in sparsely textured scenes. To address this, a UWB and 2D lidar fusion positioning algorithm based on a few landmarks is proposed, along with a Kalman filter algorithm that considers lidar location data noise. Experimental results show that the proposed fusion algorithm significantly improves localization accuracy compared to single localization methods.
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
(2023)
Article
Chemistry, Physical
Zhipeng Zheng, Ying Zheng, Yao Luo, Zao Yi, Jianguo Zhang, Zhimin Liu, Wenxing Yang, Yang Yu, Xianwen Wu, Pinghui Wu
Summary: This study proposes a terahertz metamaterial absorber that combines metamaterial structures and a VO2 film. Flexible switching of absorption performance and an ultra-broadband perfect absorption with a bandwidth of 3.3 THz can be achieved through temperature adjustment. The study also highlights the wide thermal tuning range of spectral absorbance.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2022)
Article
Computer Science, Artificial Intelligence
Kun Cao, Lihua Xie
Summary: This paper proposes a game-theoretic inverse reinforcement learning framework that aims to learn the parameters of multistage games from demonstrated trajectories. The framework differentiates the Pontryagin's maximum principle equations of open-loop Nash equilibrium to solve the problem and can be solved through explicit recursions. Simulation examples demonstrate the effectiveness of the proposed algorithms.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Engineering, Aerospace
Dadong Fan, Kexin Guo, Shangke Lyu, Xiang Yu, Lihua Xie, Lei Guo
Summary: In this article, a safety control scheme is proposed for quadrotor to ensure collision resilience like flying insects. The direction and magnitude of contact wrench are analyzed quantitatively based on the compliant contact wrench model. A nonlinear disturbance observer is developed to estimate the contact wrench exerted on the quadrotor, enabling effective collision detection. A tilt-torsion decomposition-based attitude controller is then developed to prioritize horizontal posture correction. The effectiveness of the proposed collision resilience control scheme is demonstrated through simulations and flight experiments.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2023)
Article
Automation & Control Systems
Ci Chen, Lihua Xie, Yi Jiang, Kan Xie, Shengli Xie
Summary: In this article, the optimal output tracking problem for linear discrete-time systems with unknown dynamics is investigated using reinforcement learning (RL) and robust output regulation theory. Different from most existing works, which depend on the state of the system, this problem only utilizes the outputs of the reference system and the controlled system. The proposed off-policy RL algorithm allows for solving the output tracking problem using only measured output data and the reference output, without requiring complete and accurate system dynamics knowledge.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Robotics
Kun Cao, Xiuxian Li, Lihua Xie
Summary: This article studies the problem of distributed framework matching and proposes algorithms for different types of frameworks. It demonstrates the effectiveness of these algorithms in formation control and object matching problems through simulations.
IEEE TRANSACTIONS ON ROBOTICS
(2023)
Article
Computer Science, Information Systems
Jianfei Yang, Xinyan Chen, Han Zou, Dazhuo Wang, Lihua Xie
Summary: Wi-Fi sensing technology has been proven superior in smart homes due to its cost-effectiveness and privacy-preserving nature. This article introduces AutoFi, a Wi-Fi sensing model based on a novel geometric self-supervised learning algorithm, which effectively utilizes randomly captured low-quality CSI samples and achieves cross-task knowledge transfer.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
He Huang, Jianfei Yang, Xu Fang, Hao Jiang, Lihua Xie
Summary: Accurate indoor pedestrian localization and tracking are crucial. A novel approach called VariFi, which incorporates variational inference techniques, is proposed. VariFi utilizes a signal map to provide conditional RSS distribution and applies a filtering mechanism to reduce local optimum cases. Experimental results show that VariFi outperforms mainstream approaches in terms of both localization accuracy and robustness, and can enhance the accuracy when combined with existing approaches.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Automation & Control Systems
Shanshan Hong, Maopeng Ran, Lihua Xie, Yu Zhang
Summary: This paper addresses the coordination problem of uncertain high-order nonlinear multi-agent systems using cloud-based event-triggered control. Communication is achieved through indirect and asynchronous access to a shared cloud database. The proposed approach includes a self-triggered extended state observer (ESO) for uncertainty estimation and an event-triggered controller based on the ESO output. The paper proves that the multi-agent system can track a virtual leader without any Zeno behavior from output sampling or controller update. Numerical and vehicle platoon examples are provided to verify the theoretical results.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Xu Fang, Lihua Xie
Summary: This article proposes a distributed output feedback formation maneuver controller for leader-follower multiagent systems with high-order integrator dynamics. The proposed method allows manipulation of the scale, orientation, translation, and shape of the formation continuously, without the need for followers to know the time-varying maneuver parameters known only to the leaders. The advantages of this method are that it is output feedback based and demonstrates how to achieve different types of formation shape.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Muqing Cao, Kun Cao, Xiuxian Li, Lihua Xie
Summary: This article addresses the problem of using a multirobot system to conduct sweep coverage over a region with uneven and unknown workload distribution. It proposes a distributed workload allocation algorithm that ensures convergence to optimal workload assignment and considers the practical constraint of limited sensor range. Simulations and flight experiments validate the theoretical results.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Computer Science, Information Systems
Yunjiao Zhou, He Huang, Shenghai Yuan, Han Zou, Lihua Xie, Jianfei Yang
Summary: This article proposes a WiFi-based Internet of Things-enabled human pose estimation scheme for metaverse avatar simulation. By mapping the channel state information of WiFi signals to human pose landmarks through self-attention, it effectively explores the spatial information of human pose. WiFi-based human poses, due to the ubiquity of WiFi and robustness to various illumination conditions, are suitable for instructing the movement of digital avatars in the metaverse, promoting avatar applications in smart homes.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Automation & Control Systems
Yang Lyu, Muqing Cao, Shenghai Yuan, Lihua Xie
Summary: In this article, the focus is on enabling the autonomous perception and control of a small unmanned aerial vehicle (UAV) for a facade inspection task. The perception is simplified as a plane pose estimation problem, and an adaptive observer is proposed for fast and noise-insensitive estimation. An MPC controller is designed to achieve stable plane following and smooth transition in a multiple-plane scenario, while satisfying the PE condition and maneuver constraints of the UAV. The proposed methods are tested in simulation and practical scenarios, demonstrating their effectiveness and practicability.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Xia Jiang, Xianlin Zeng, Lihua Xi, Jian Sun
Summary: This letter presents a variance-reduced shuffling gradient descent algorithm with Nesterov's momentum for smooth convex finite-sum optimization. The proposed algorithm converges at a rate of O(1/T) and is not affected by gradient variance, which outperforms most existing shuffling gradient algorithms.
IEEE CONTROL SYSTEMS LETTERS
(2023)
Article
Automation & Control Systems
Haozhi Cao, Yuecong Xu, Kezhi Mao, Lihua Xie, Jianxiong Yin, Simon See, Qianwen Xu, Jianfei Yang
Summary: This article introduces a self-supervised method that utilizes incoherence detection for video representation learning. The method constructs incoherent clips by hierarchically sampling multiple subclips of various lengths from the same raw video. The network is trained to predict the location and length of incoherence in order to learn high-level representation. Intravideo contrastive learning is also introduced to maximize mutual information between incoherent clips. Extensive experiments on action recognition and video retrieval demonstrate the remarkable performance of the proposed method across different backbone networks and datasets compared to previous coherence-based methods.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Kun Cao, Muqing Cao, Lihua Xie
Summary: This article investigates the similar formation control problem for multirobot systems. Specifically, an integrated relative localization and similar formation control scheme is proposed based on range measurements between robots and landmarks, as well as odometry measurements of robots themselves. To achieve precise relative localization, a persistent excitation (P.E.) signal is introduced in the controller, which is generated by a carefully designed function of range measurements. The proposed scheme is proven to solve the similar formation control problem with global asymptotic convergence for directed acyclic graphs (DAGs). Numerical simulation and physical experiments are conducted to validate the effectiveness of the theoretical findings.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Computer Science, Artificial Intelligence
Yucheng Wang, Min Wu, Ruibing Jin, Xiaoli Li, Lihua Xie, Zhenghua Chen
Summary: Remaining useful life (RUL) prediction is crucial for prognostics and health management of a system. Deep learning models have emerged as leading solutions due to their powerful ability in nonlinear modeling and capturing temporal dependencies. However, existing methods have limitations in effectively modeling and capturing spatial dependencies. To overcome these limitations, we propose a novel framework that combines both local and global information to accurately predict RUL.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
