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IEEE International Conference on robotics and Biomimetics

作者： Lin Chen Yaonan Wang Zhiqiang Miao Yang Mo Mingtao Feng Zhen Zhou School of Electrical and Information Engineering Hunan University Changsha China National Engineering Research Center for Robot Visual Perception and Control Technology Changsha China School of Computer Science and Technology Xidian University Xian China

ISBN: (纸本)9781665481106

Multi-Agent Path Finding is a problem of finding the optimal set of paths for multiple agents from the starting position to the goal without conflict, which is essential to large-scale robotic systems. Imitation and reinforcement learning are applied to solve the MAPF problem and have achieved certain results, which provides a feasible solution for the path planning problem of large-scale robot systems. The current method improves the performance of distributed strategy-guided agent planning paths in complex environments by introducing the communication between graph neural networks and agents but dramatically reduces the system's robustness. This paper develops a novel imitation reinforcement learning framework by introducing Transformer, which enables algorithms to perform well in complex environments without relying on communication between agents. Compared with its counterparts, experiments show that the policy trained by our method guides the agent to drive from the initial position to the goal without collision and achieve better performance.

关键词： Learning systems robot kinematics Biomimetics Reinforcement learning Transformers Robustness Path planning

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Learning compliant grasping and manipulation by teleoperation with adaptive force control

arXiv

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arXiv 2021年

作者： Zeng, Chao Li, Shuang Jiang, Yiming Li, Qiang Chen, Zhaopeng Yang, Chenguang Zhang, Jianwei Department of Informatics Universiẗat Hamburg Germany National Engineering Laboratory for Robot Visual Perception and Control Hunan University China Center for Cognitive Interaction Technology Bielefeld University Germany Bristol Robotics Laboratory University of the West of England United Kingdom

In this work, we focus on improving the robot's dexterous capability by exploiting visual sensing and adaptive force control. TeachNet, a vision-based teleoperation learning framework, is exploited to map human hand postures to a multifingered robot hand. We augment TeachNet, which is originally based on an imprecise kinematic mapping and position-only servoing, with a biomimetic learning-based compliance control algorithm for dexterous manipulation tasks. This compliance controller takes the mapped robotic joint angles from TeachNet as the desired goal, computes the desired joint torques. It is derived from a computational model of the biomimetic control strategy in human motor learning, which allows adapting the control variables (impedance and feedforward force) online during the execution of the reference joint angle trajectories. The simultaneous adaptation of the impedance and feedforward profiles enables the robot to interact with the environment in a compliant manner. Our approach has been verified in multiple tasks in physics simulation, i.e., grasping, opening-a-door, turning-a-cap, and touching-a-mouse, and has shown more reliable performances than the existing position control and the fixed-gain-based force control approaches. Copyright © 2021, The Authors. All rights reserved.

关键词： Remote control

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PVPUFormer: Probabilistic visual Prompt Unified Transformer for Interactive Image Segmentation

arXiv

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arXiv 2023年

作者： Zhang, Xu Yang, Kailun Lin, Jiacheng Yuan, Jin Li, Zhiyong Li, Shutao College of Computer Science and Electronic Engineering Hunan University Changsha410082 China School of Robotics The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China College of Electrical and Information Engineering The Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province Hunan University Changsha410082 China

Integration of diverse visual prompts like clicks, scribbles, and boxes in interactive image segmentation significantly facilitates users’ interaction as well as improves interaction efficiency. However, existing studies primarily encode the position or pixel regions of prompts without considering the contextual areas around them, resulting in insufficient prompt feedback, which is not conducive to performance acceleration. To tackle this problem, this paper proposes a simple yet effective Probabilistic visual Prompt Unified Transformer (PVPUFormer) for interactive image segmentation, which allows users to flexibly input diverse visual prompts with the probabilistic prompt encoding and feature post-processing to excavate sufficient and robust prompt features for performance boosting. Specifically, we first propose a Probabilistic Prompt-unified Encoder (PPuE) to generate a unified one-dimensional vector by exploring both prompt and non-prompt contextual information, offering richer feedback cues to accelerate performance improvement. On this basis, we further present a Prompt-to-Pixel Contrastive (P2C) loss to accurately align both prompt and pixel features, bridging the representation gap between them to offer consistent feature representations for mask prediction. Moreover, our approach designs a Dual-cross Merging Attention (DMA) module to implement bidirectional feature interaction between image and prompt features, generating notable features for performance improvement. A comprehensive variety of experiments on several challenging datasets demonstrates that the proposed components achieve consistent improvements, yielding state-of-the-art interactive segmentation performance. Our code is available at https://***/XuZhang1211/PVPUFormer. Copyright © 2023, The Authors. All rights reserved.

关键词： Pixels

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Geometric Formation Tracking of Aerial robot Swarms Without Linear Velocity Measurements Over Directed Networks

Geometric Formation Tracking of Aerial Robot Swarms Without ...

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IEEE International Conference on robotics and Biomimetics

作者： Jie Lin Yaonan Wang Zhiqiang Miao Rafael Fierro College of Electrical and Information Engineering Hunan University Changsha China The National Engineering Laboratory for Robot Visual Perception and Control Changsha China MARHES Lab University of New Mexico Albuquerque New Mexico USA

ISBN: (纸本)9781665405362

This paper focuses on the formation tracking problem of aerial robot swarms without linear velocity measurements over directed interaction topologies. A distributed formation controller is designed for a quadrotor swarm under a directed graph using the hierarchical control structure. First, the outer-loop controller governs the translational motion to achieve the desired formation, where the filter-like auxiliary dynamic system is designed for each quadrotor to overcome the lack of the linear velocity measurements. Next, based on the geometric attitude representing, an almost-global inner-loop controller is proposed to regulate the attitude of each quadrotor, which is not only coordinate-free but also the strongest possible controller in terms of the region of convergence. Furthermore, necessary and sufficient conditions for the formation tracking problem over the directed graph are presented so that the stability analysis is guaranteed. Finally, simulation results are provided to show the effectiveness of the proposed control algorithms.

关键词： Sufficient conditions Attitude control Tracking Simulation robot kinematics Directed graphs Autonomous aerial vehicles

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Adaptive Safety control of a Constrained Uncertain robotic System

Adaptive Safety Control of a Constrained Uncertain Robotic S...

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Automation, control and robotics engineering (CACRE), International Conference on

作者： Haijing Wang Jinzhu Peng Fangfang Zhang Yaonan Wang School of Electrical and Information Engineering Zhengzhou University Zhengzhou China National Engineering Laboratory for Robot Visual Perception and Control Hunan University Changsha China College of Electrical and Information Engineering Hunan University Changsha China

The safety control problem of a constrained uncertain robotic system is investigated in this paper. First, the high-order control barrier functions (HoCBFs) are introduced to deal with the output constraints for he system. And to solve the uncertain problem and revisit the HoCBF-based framework, an adaptive approach is proposed to updating the unknown parameters online. In this way, the system safety can be achieved adaptively by keeping the system output within the predefined constrained region even in the presence of parametric uncertainty. Finally, simulation tests are carried out to verify the validity of the proposed controller.

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Distributed Resilient Estimator for Networked Systems Under Deception Attacks

Distributed Resilient Estimator for Networked Systems Under ...

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International Conference on control, Automation, robotics and Vision (ICARCV)

作者： Weiwei Zhan Zhiqiang Miao Yang Hu Yizong Chen Yanjie Chen Yaonan Wang College of Electrical and Information Engineering Hunan University Changsha China National Engineering Research Center of Robot Visual Perception and Control Technology Changsha China School of Mechanical Engineering and Automation Fuzhou University Fuzhou China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

Deception attacks are employed to compromise cyber-physical systems through fake data injection. This paper concentrates on the distributed resilient estimation issue of multi-sensor networked systems under deception attacks. In order to detect deception attacks, we utilize Kullback-Leibler(K-L) divergence as a criterion to distinguish the discrepancy between the deceived information and the estimated information. When the attack does not exist, the transmitted information can be restored to ensure the resilient estimation performance. Based on the extended Kalman filter design method, a distributed resilient estimation with a dual-gain mechanism is developed. This advanced approach dynamically adjusts the weighting balance between the predictive model and sensor data inputs, achieving the optimal estimation during the shutdown and activation of spoofing attacks. Finally, numerical simulations are provided to further illustrate the results.

关键词： Measurement Fault tolerance Design methodology Buildings Estimation Predictive models Cyber-physical systems robot sensing systems Numerical simulation Kalman filters

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An Improved SCA-BP Delay Prediction Method for Networked control Systems

An Improved SCA-BP Delay Prediction Method for Networked Con...

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Chinese Automation Congress (CAC)

作者： Jiayin Xie Yaonan Wang Haoran Tan You Wu Bowen Zhou National Engineering Research Center for Robot Visual Perception and Control College of Electrical and Information Engineering Hunan University Changsha China Hunan Retoo Intelligent Technology Co. Ltd. Changsha China

A networked control system is a system that uses communication networks to connect the various parts. However, network delay affects the performance and stability of the networked control system. In order to eliminate the impact of network delay on the control system, an improved SCA-BP delay prediction method is proposed in this paper. The proposed method optimizes the initial weights and biases of the BP neural network, and further optimizes them through backpropagation gradient descent, obtaining the final prediction model. The proposed method introduces a random perturbation factor in the sine and cosine functions, which increases the explorability and diversity of the method. And they are sorted and grouped according to the fitness values of the candidate solutions. At the same time, different update strategies are adopted based on the different groups, enabling the method to perform global and local search simultaneously. In the update strategy, a linear function is also introduced in addition to the sine and cosine functions, enabling the method to maintain the direction of the current optimal solution to a certain extent. Finally, the superiority and effectiveness of the method compared with traditional methods are verified through some comparative simulations, indicating that the method has a strong delay prediction ability.

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Minimalist and High-Quality Panoramic Imaging with PSF-aware Transformers

arXiv

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arXiv 2023年

作者： Jiang, Qi Gao, Shaohua Gao, Yao Yang, Kailun Yi, Zhonghua Shi, Hao Sun, Lei Wang, Kaiwei The State Key Laboratory of Modern Optical Instrumentation The National Engineering Research Center of Optical Instrumentation Zhejiang University Hangzhou310027 China The School of Robotics The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China

High-quality panoramic images with a Field of View (FoV) of 360° are essential for contemporary panoramic computer vision tasks. However, conventional imaging systems come with sophisticated lens designs and heavy optical components. This disqualifies their usage in many mobile and wearable applications where thin and portable, minimalist imaging systems are desired. In this paper, we propose a Panoramic Computational Imaging Engine (PCIE) to achieve minimalist and high-quality panoramic imaging. With less than three spherical lenses, a Minimalist Panoramic Imaging Prototype (MPIP) is constructed based on the design of the Panoramic Annular Lens (PAL), but with low-quality imaging results due to aberrations and small image plane size. We propose two pipelines, i.e. Aberration Correction (AC) and Super-Resolution and Aberration Correction (SR&AC), to solve the image quality problems of MPIP, with imaging sensors of small and large pixel size, respectively. To leverage the prior information of the optical system, we propose a Point Spread Function (PSF) representation method to produce a PSF map as an additional modality. A PSF-aware Aberration-image Recovery Transformer (PART) is designed as a universal network for the two pipelines, in which the self-attention calculation and feature extraction are guided by the PSF map. We train PART on synthetic image pairs from simulation and put forward the PALHQ dataset to fill the gap of real-world high-quality PAL images for low-level vision. A comprehensive variety of experiments on synthetic and real-world benchmarks demonstrates the impressive imaging results of PCIE and the effectiveness of the PSF representation. We further deliver heuristic experimental findings for minimalist and high-quality panoramic imaging, in terms of the choices of prototype and pipeline, network architecture, training strategies, and dataset construction. Our dataset and code will be available at https://***/zju-jiangqi/PCIE-PART. Copyrig

关键词： Optical transfer function

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A Muti-stage Selection Filter Based on Wavelet Packet and2DCNN for Fault Diagnosis of Rotating Machinery

A Muti-stage Selection Filter Based on Wavelet Packet and2DC...

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第42届中国控制会议

作者： Wenbin He Jianxu Mao Li Liu Zhe Li Miao Yang Yaonan Wang College of Electrical and Information Engineering Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University State Grid Hunan Electric Power Company Limited Research Institute

Fault information of rotating machinery is often drowned in strong noise signals, so it is crucial to accurately identify faults from high-intensity noise signals. In this article, an end-to-end fault diagnosis model is developed, which consists of a multi-stage selection filter based on wavelet packet and 2D-CNN. First, the original measured mechanical signals were processed by the three-level wavelet packet decomposition to obtain eight sub-bands with coefficient matrices. Second, the signal is reconstructed using different numbers of sub-bands, where the number is increased by one at a time to obtain eight different multi-stage reconstructed signals. Third, the reconstructed signals are reorganized into 2D signal maps;and a parallel training network is constructed using signal maps and 2D-CNN to achieve fault classification. Then, guided by the training results, eight parallel classification results are compared, so as to train the best fault diagnosis model. Finally, the simulation experiment based on a bearing data set illustrates the proposed multi-stage selection filter is effective and feasible in application.

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无人飞行器在不确定扰动下的动态目标跟踪

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engineering 2024年第4期35卷 74-85页

作者： Yanjie Chen Yangning Wu Limin Lan Hang Zhong Zhiqiang Miao Hui Zhang Yaonan Wang School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou 350108China Department of Computer Science Aberystwyth UniversityAberystwyth SY233DBUK School of Robotics Hunan UniversityChangsha 410082China College of Electrical and Information Engineering Hunan UniversityChangsha 410082China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan UniversityChangsha 410082China

This study proposes an image-based visual servoing(IBVS)method based on a velocity observer for an unmanned aerial vehicle(UAV)for tracking a dynamic target in Global Positioning System(GPS)-denied *** proposed method derives the simplified and decoupled image dynamics of underactuated UAVs using a constructed virtual camera and then considers the uncertainties caused by the unpredictable rotations and velocities of the dynamic target.A novel image depth model that extends the IBVS method to track a rotating target with arbitrary orientations is *** depth model ensures image feature accuracy and image trajectory smoothness in rotating target *** relative velocities of the UAV and the dynamic target are estimated using the proposed velocity *** to the velocity observer,translational velocity measurements are not required,and the control chatter caused by noise-containing measurements is *** integral-based filter is proposed to compensate for unpredictable environmental disturbances in order to improve the antidisturbance *** stability of the velocity observer and IBVS controller is analyzed using the Lyapunov *** simulations and multistage experiments are conducted to illustrate the tracking stability,anti-disturbance ability,and tracking robustness of the proposed method with a dynamic rotating target.

关键词： Unmanned aerial vehicle visual servoing Velocity observer Target tracking

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