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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

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A SINS Error Correction Approach Based on Dual-Threshold ZV ...

2023 IEEE International Conference on systems, Man, and cybernetics, SMC 2023

作者： Xu, Ruijie Chen, Shichao Sun, Wenqiao Lv, Yisheng Luo, Jialiang Tang, Ying Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences China University of Geosciences Beijing School of Information Engineering The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Rowan University Department of Electrical and Computer Engineering Glassboro United States

ISBN: (纸本)9798350337020

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation System (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance. © 2023 IEEE.

关键词： Cubature Kalman Filter Inertial Pedestrian Navigation Zero-Velocity Update

Fast Path Planning for Autonomous Vehicle Parking with Safety-Guarantee using Hamilton-Jacobi Reachability

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arXiv 2023年

作者： Chi, Xuemin Zeng, Jun Huang, Jihao Liu, Zhitao Su, Hongye State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Hybrid Robotics Group the Department of Mechanical Engineering UC Berkeley United States

We present a fast planning architecture called Hamilton-Jacobi-based bidirectional A* (HJBA*) to solve general tight parking scenarios. The algorithm is a two-layer composed of a high-level HJ-based reachability analysis and a lower-level bidirectional A* search algorithm. In high-level reachability analysis, a backward reachable tube (BRT) concerning vehicle dynamics is computed by the HJ analysis and it intersects with a safe set to get a safe reachable set. The safe set is defined by constraints of positive signed distances for obstacles in the environment and computed by solving QP optimization problems offline. For states inside the intersection set, i.e., the safe reachable set, the computed backward reachable tube ensures they are reachable subjected to system dynamics and input bounds, and the safe set guarantees they satisfy parking safety with respect to obstacles in different shapes. For online computation, randomized states are sampled from the safe reachable set, and used as heuristic guide points to be considered in the bidirectional A* search. The bidirectional A* search is paralleled for each randomized state from the safe reachable set. We show that the proposed two-level planning algorithm is able to solve different parking scenarios effectively and computationally fast for typical parking requests. We validate our algorithm through simulations in large-scale randomized parking scenarios and demonstrate it to be able to outperform other state-of-the-art parking planning algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

Velocity Obstacle for Polytopic Collision Avoidance for Distributed Multi-robot systems

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arXiv 2023年

作者： Huang, Jihao Zeng, Jun Chi, Xuemin Sreenath, Koushil Liu, Zhitao Su, Hongye State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Hybrid Robotics Group The Department of Mechanical Engineering UC Berkeley United States

Obstacle avoidance for multi-robot navigation with polytopic shapes is challenging. Existing works simplify the system dynamics or consider it as a convex or non-convex optimization problem with positive distance constraints between robots, which limits real-time performance and scalability. Additionally, generating collision-free behavior for polytopic-shaped robots is harder due to implicit and non-differentiable distance functions between polytopes. In this paper, we extend the concept of velocity obstacle (VO) principle for polytopic-shaped robots and propose a novel approach to construct the VO in the function of vertex coordinates and other robot’s states. Compared with existing work about obstacle avoidance between polytopic-shaped robots, our approach is much more computationally efficient as the proposed approach for construction of VO between polytopes is optimization-free. Based on VO representation for polytopic shapes, we later propose a navigation approach for distributed multi-robot systems. We validate our proposed VO representation and navigation approach in multiple challenging scenarios including large-scale randomized tests, and our approach outperforms the state of art in many evaluation metrics, including completion rate, deadlock rate, and the average travel distance. Copyright © 2023, The Authors. All rights reserved.

关键词： Multipurpose robots

Adaptive Power Regulation control for Floating Wind Turbines with Guaranteed Transient Performance

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 15588-15598页

作者： Gong, Yingjie Meng, Wenchao Geng, Hua Yang, Qinmin Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310027 China Tsinghua University Beijing National Research Center for Information Science and Technology Department of Automation Beijing100084 China Huzhou Industrial Control Technology Research Institute Huzhou313000 China

Floating offshore wind turbines (FOWTs) hold significant potential for developing wind energy in deep-sea areas. However, they are prone to additional motions, heavy workloads, and undesirable fluctuations under combined wind-wave loads. To tackle these issues, this paper presents a novel adaptive blade pitch control strategy with guaranteed transient performance for FOWTs operating in above-rated wind speed regions. This strategy effectively suppresses platform pitch motion to enhance system stability while maintaining the power output at its rated value. Specifically, this method initiates by defining a filtered regulation error to solve the non-affine nature of its model. An adaptive blade pitch controller is subsequently proposed, integrating an online learning approximator to cope with the unknown dynamics caused by unmeasurable external environmental inputs and model uncertainties. To further mitigate approximation errors, a nonlinear robust control law with adaptive gains is employed, enhancing the robustness and adaptive capabilities of the controller. Superior to the traditional adaptive controllers, a significant advantage of this strategy is its ability to quantify and ensure regulatory performance within predefined constraints during both transient and steady-state stages, thereby achieving high-performance control in power regulation. Finally, simulation studies are conducted using the OpenFAST software to show the capability of the presented blade pitch controller, which guarantees stable power generation with guaranteed transient performance. © 2004-2012 IEEE.

关键词： Robust control

CT-NeRF: Incremental Optimization of Neural Radiance Field and Camera Poses with Complex Trajectory

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IEEE Transactions on Circuits and systems for Video technology 2025年

作者： Ran, Yunlong Li, Yanxu Ye, Qi Huo, Yuchi Cui, Zhaopeng Bai, Zechun Sun, Jiahao Chen, Jiming Zhejiang University College of Control Science and Engineering Hangzhou China Zhejiang University College of Control Science and Engineering State Key Laboratory of Industrial Control Technology China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province China Zhejiang University State Key Lab of CAD and CG China

Neural radiance field (NeRF) has achieved impressive results in high-quality 3D scene reconstruction. However, NeRF heavily relies on precise camera poses. While recent works like BARF have introduced camera pose optimization within NeRF, their applicability is limited to simple trajectory scenes. Existing methods struggle while tackling complex trajectories involving large rotations. To address this limitation, we propose CT-NeRF, an incremental reconstruction and optimization pipeline using only RGB images without pose and depth input. In this pipeline, we first propose a local-global bundle adjustment under a pose graph connecting neighboring frames to enforce the consistency between poses to escape the local minima caused by only pose consistency with the scene structure. Further, we instantiate the consistency between poses as a reprojection error constraint resulting from pixel-level correspondences between input image pairs. Through the incremental reconstruction, CT-NeRF enables the recovery of both camera poses and scene structure and is capable of handling scenes with complex trajectories. We evaluate the performance of CT-NeRF on two real-world datasets, NeRF-Buster and Free-Dataset, which feature complex trajectories. Results show CT-NeRF outperforms existing methods in novel view synthesis and pose estimation accuracy. © 1991-2012 IEEE.

关键词： 3D Reconstruction bundle adjustment NeRF novel view synthesis structure from motion

All-weather,natural silent speech recognition via machine-learning-assisted tattoo-like electronics

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npj Flexible Electronics 2021年第1期5卷 183-191页

作者： Youhua Wang Tianyi Tang Yin Xu Yunzhao Bai Lang Yin Guang Li Hongmiao Zhang Huicong Liu YongAn Huang State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhanChina Flexible Electronics Research Center Huazhong University of Science and TechnologyWuhanChina School of Mechanical and Electric Engineering Jiangsu Provincial Key Laboratory of Advanced RoboticsSoochow UniversitySuzhouChina State Key Laboratory of Industrial Control Technologyg Institute of Cyber Systems and ControlZhejiang UniversityHangzhouChina

The internal availability of silent speech serves as a translator for people with aphasia and keeps human–machine/human interactions working under various *** paper develops a silent speech strategy to achieve all-weather,natural *** strategy requires few usage specialized skills like sign language but accurately transfers high-capacity information in complicated and changeable daily *** the strategy,the tattoo-like electronics imperceptibly attached on facial skin record high-quality bio-data of various silent speech,and the machine-learning algorithm deployed on the cloud recognizes accurately the silent speech and reduces the weight of the wireless acquisition module.A series of experiments show that the silent speech recognition system(SSRS)can enduringly comply with large deformation(~45%)of faces by virtue of the electricitypreferred tattoo-like electrodes and recognize up to 110 words covering daily vocabularies with a high average accuracy of 92.64%simply by use of small-sample machine *** successfully apply the SSRS to 1-day routine life,including daily greeting,running,dining,manipulating industrial robots in deafening noise,and expressing in darkness,which shows great promotion in real-world applications.

关键词： translator weather silent

Safe and Agile Transportation of Cable-Suspended Payload via Multiple Aerial Robots

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arXiv 2025年

作者： Wang, Yongchao Wang, Junjie Zhou, Xiaobin Yang, Tiankai Xu, Chao Gao, Fei School of Aeronautic Science and Engineering Beihang University Beijing100191 China Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Huzhou Institute Zhejiang University Huzhou313000 China

Transporting a heavy payload using multiple aerial robots (MARs) is an efficient manner to extend the load capacity of a single aerial robot. However, existing schemes for the multiple aerial robots transportation system (MARTS) still lack the capability to generate a collision-free and dynamically feasible trajectory in real-time and further track an agile trajectory especially when there are no sensors available to measure the states of payload and cable. Therefore, they are limited to low-agility transportation in simple environments. To bridge the gap, we propose complete planning and control schemes for the MARTS, achieving safe and agile aerial transportation (SAAT) of a cable-suspended payload in complex environments. Flatness maps for the aerial robot considering the complete kinematical constraint and the dynamical coupling between each aerial robot and payload are derived. To improve the responsiveness for the generation of the safe, dynamically feasible, and agile trajectory in complex environments, a real-time spatio-temporal trajectory planning scheme is proposed for the MARTS. Besides, we break away from the reliance on the state measurement for both the payload and cable, as well as the closed-loop control for the payload, and propose a fully distributed control scheme to track the agile trajectory that is robust against imprecise payload mass and non-point mass payload. The proposed schemes are extensively validated through benchmark comparisons, ablation studies, and simulations. Finally, extensive real-world experiments are conducted on a MARTS integrated by three aerial robots with onboard computers and sensors. The result validates the efficiency and robustness of our proposed schemes for SAAT in complex environments. Copyright © 2025, The Authors. All rights reserved.

关键词： Robust control

Towards Two-view 6D Object Pose Estimation: A Comparative Study on Fusion Strategy

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arXiv 2022年

作者： Wu, Jun Liu, Lilu Wang, Yue Xiong, Rong The State Key Laboratory of Industrial Control Technology Institue of Cyber-Systems and Control Zhejiang University Zhejiang China

Current RGB-based 6D object pose estimation methods have achieved noticeable performance on datasets and real world applications. However, predicting 6D pose from single 2D image features is susceptible to disturbance from changing of environment and textureless or resemblant object surfaces. Hence, RGB-based methods generally achieve less competitive results than RGBD-based methods, which deploy both image features and 3D structure features. To narrow down this performance gap, this paper proposes a framework for 6D object pose estimation that learns implicit 3D information from 2 RGB images. Combining the learned 3D information and 2D image features, we establish more stable correspondence between the scene and the object models. To seek for the methods best utilizing 3D information from RGB inputs, we conduct an investigation on three different approaches, including Early-Fusion, Mid-Fusion, and Late-Fusion. We ascertain the Mid-Fusion approach is the best approach to restore the most precise 3D keypoints useful for object pose estimation. The experiments show that our method outperforms state-of-the-art RGB-based methods, and achieves comparable results with RGBD-based methods. © 2022, CC BY.

关键词： Textures

Advancing Virtual Reality Interaction: A Ring-Shaped controller and Pose Tracking

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Advancing Virtual Reality Interaction: A Ring-Shaped Control...

IEEE International Conference on Robotics and Automation (ICRA)

作者： Zhuqing Zhang Dongxuan Li Jiayao Ma Yijia He Pan Ji Rong Xiong Hongdong Li Yue Wang State Key Laboratory of Industrial Control Technology and Institute of Cyber-Systems and Control Zhejiang University Zhejiang China Tencent Holdings Tencent XR Vision Labs Shenzhen China College of Engineering and Computer Science Australian National University Canberra

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Ensuring robust tracking of controllers’ movement is critical for human-robot interaction in virtual reality (VR) scenarios. This paper proposes a robust tracking algorithm based on a novel wearable ring-shaped controller equipped with an inertial measurement unit (IMU) and a light-emitting diode (LED). This novel controller design allows users to free up their hands for more immersive experiences. To track the controller’s motion accurately and robustly, we resort to various forms of visual measurements, including 6 DoF and 5 DoF pose measurements from hand gesture detection, as well as 3 DoF position measurement and 2 DoF image measurement derived from the LED. We theoretically analyze the performances of these observation models and propose an optimal observation model combination scheme. Moreover, the necessity and rationale of online estimating system gravity are illustrated. The effectiveness of our tracking method is validated through extensive experiments.

关键词： Solid modeling Analytical models Visualization Measurement units Tracking Virtual reality Inertial navigation