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Cooperative attack–defense decision-making of multi-UAV using satisficing decision-enhanced wolf pack search algorithm

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Soft Computing 2024年第17-18期28卷 9575-9586页

作者： Zhou, Tongle Chen, Mou Wang, Yuhui Zhu, Ronggang Yang, Chenguang College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Key Laboratory of Avionics System Integrated Technology Shanghai200241 China Science and Technology on Electro-optic Control Laboratory Luoyang Institute of Electro-Optical Equipment of Avic Luoyang471000 China Bristol Robotics Laboratory University of the West of England BristolBS16 1QY United Kingdom

Unmanned aerial vehicles (UAVs) have shown their superiority for applications in complicated military missions. A cooperative attack–defense decision-making method based on satisficing decision-enhanced wolf pack search (SDEWPS) algorithm is developed for multi-UAV air combat in this paper. Firstly, the multi-UAV air combat mathematical model is provided and the attack–defense decision-making constraints are defined. Besides the traditional air combat situation, the capability of UAVs and target information including target type and target intention are all considered in this paper to establish the air combat superiority function. Then, the wolf pack search (WPS) algorithm is used to solve the attack decision problem. To improve efficiency, the satisficing decision theory is employed to enhance the WPS to obtain the satisficing solution rather than optimal solution. The simulation results show that the developed method can realize the cooperative attack decision-making. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Decision making

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Active Camera View Planning Based on Deep Reinforcement Learning in Indoor Exploration 42

Active Camera View Planning Based on Deep Reinforcement Lear...

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42nd Chinese Control Conference, CCC 2023

作者： Wang, Hao-Yu Meng, Qing-Hao Dai, Xu-Yang Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Tianjin300072 China

ISBN: (纸本)9789887581543

In the last decades, significant progress has been made in the field of active vSLAM (visual simultaneous localization and mapping). However, the majority of active vSLAM methods suffer from the problem of coupling the camera's viewpoint to the robot's motion, which limits the initiative during the exploration of unknown environments. To address this issue, this study proposes a camera view planning method based on deep reinforcement learning (DRL), which makes the camera rotate independently. First, feature encoding is performed on the reconstructed navigation map using a multi-layer convolutional neural network (CNN). Second, the DRL-based camera view planning method is trained through the proximal policy optimization (PPO) algorithm. Last, a significant number of tests is performed on a public dataset of indoor environments. The simulation results show that the proposed camera view planning method improves the exploration coverage by an average of 4% (33.86 m2 for traditional vs. 35.21 m2 for the suggested method). Meanwhile, the kind of semantic information newly observed in each step increases by 21% (2.9 for traditional vs. 3.5 for the proposed method) on average, indicating the improvement in the efficiency of information acquisition. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Reinforcement learning

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Feature Space Augmentation and Old Class Space Preservation for Class Incremental Learning 42

Feature Space Augmentation and Old Class Space Preservation ...

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42nd Chinese Control Conference, CCC 2023

作者： Zeng, Ming Li, Siying Liu, Jiazhe Li, Yuanhao Institute of Robotics and Automation Systems School of Electrical and Information Engineering Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Tianjin University Tianjin300072 China

ISBN: (纸本)9789887581543

The ability of continuously learning new knowledge without forgetting old ones is crucial to adapt to an ever-changing world. This scenario becomes more challenging when the previous data are not available. Current class incremental learning (CIL) approaches tend to incorporate new classes with backward compatibility, i.e., maintaining discriminability of old ones. By contrast, we focus on the extensibility and compatibility for future new classes in the early stage. Our proposed method achieves this by augmenting feature space. In detail, a large number of pseudo-new classes are generated via real example mixture and then train the initial spatially augmented model using pseudo-new classes and the base classes. Besides, considering the fact that it is impossible to maintain backward compatibility with only one prototype for each old class, the updated model also needs to preserve old class space in incremental stages. We employ a certain perturbation to the old class prototypes to effectively avoid old class space from being over-squeezed by the samples of new classes. The experiments on CIFAR-100 and ImageNet-Subset (100 classes) demonstrate that our method substantially reduces the overlap of old and new classes, outperforming state-of-the-art various baselines. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Catastrophic forgetting Class incremental learning Feature space augmentation Old class space preservation Pseudo-new classes

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Motion Capture and Gait Analysis of Ants with Leg Injuries 42

Motion Capture and Gait Analysis of Ants with Leg Injuries

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42nd Chinese Control Conference, CCC 2023

作者： Zeng, Ming Li, Yuanhao Meng, Chang Zhong, Shutong Wang, Zhijing Zhao, Feng Institute of Robotics and Automation Systems School of Electrical and Information Engineering Tianjin University Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Tianjin300072 China

ISBN: (纸本)9789887581543

Many insects in nature, such as ants, recover quickly after sustaining leg injuries. If this capability could be imparted to multi-legged robots, it would drastically enhance their ability to resist destruction and adapt to the environment. In this paper, the Camponotus Japonicus is used as the research object, and its locomotive patterns are studied under different leg-loss conditions. To facilitate this, a high-speed acquisition system, with a dual-view (bottom view and side view) setup, is designed to analyze the ant's linear gaits. Subsequently, the pivotal gait characteristics of the injured ants are extracted by keyframe annotation technology, including the gait phase diagram, duty factor, angle before support, angle before swing, and leg swing range. Lastly, according to the obtained gait characteristics, the general and specific laws of gait adjustment in the absence of one or two legs are systematically analyzed, which provides the basis for parametric settings and strategy optimization of robotic injured gait self-adjustment. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Gait analysis

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On-Orbit Thermal Analysis of Ring Truss-Type Deployable Antenna 23rd

On-Orbit Thermal Analysis of Ring Truss-Type Deployable Ante...

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23rd IFToMM China International Conference on Mechanism and Machine Science and engineering, IFToMM CCMMS 2022

作者： Zhang, Xiong Kang, Xi Huang, Hailin Li, Bing State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China

ISBN: (纸本)9789811993978

As space antenna tends to be large-scale, deployable antenna is more and more widely used. As a key part of antenna structure, the antenna profile will be deformed due to uneven heating during on-orbit operation, which affects the service performance of the antenna. In this paper, the thermal effect mode of space environment on the on-orbit antenna is analyzed firstly, and the differential heat conduction equation is obtained by taking the profile as research object. Then, thermal simulation of the ring truss-type deployable antenna in the sun-synchronous orbit is carried out by using the NX-TMG software. The temperature characteristics of the antenna profile and the influence law of material parameters on the profile temperature during on-orbit operation are analyzed. It is concluded that temperature of antenna profile changes in one orbital period. The selection of low absorption rate and high density materials can reduce the profile temperature difference, which provides the reference for ring truss-type deployable antenna design. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Antennas

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Analysis of normal force of wheel-sand interaction for planetary rovers with active suspension

Analysis of normal force of wheel-sand interaction for plane...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Wang, Zhengyin Yang, Huaiguang Ding, Liang Lan, Qingning Gao, Haibo Terze, Zdravko Deng, Zongquan Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150001 China University of Zagreb Faculty of Mechanical Engineering and Naval Architecture Zagreb10000 Croatia

ISBN: (纸本)9798350325706

The planetary rover with active suspension can climb steeper slopes and cross bigger obstacles in a wheel-step motion mode, which enables the planetary rover to perform more complex exploration tasks. However, wheel-step motion requires coordinated movement of the suspension and the wheels: the suspension can determine the wheel's sinkage depth and translation speed. Matching up with the wheel rotation speed can actively construct the slip ratio. The forces exerted on the wheels by sand during this process are a key index for motion control. This poses new challenges to existing wheel-sand interaction models. In this paper, dynamic normal force tests are carried out. The dynamic variation of wheel normal force with slip ratio is investigated at different sinkage depths. It is found that the normal force exerted on the wheel increases firstly and then decreases with the slip ratio, and reaches the maximum value near s=0. The distributed stresses of the wheel were analysed by discrete element method (DEM) simulation, and the phenomenon of the distribution stress reconstruction of the wheel is found. Further, by analyzing the local particles in contact with the wheel, it is found that the particle movement direction and morphology vary with slip ratio. The analysis of the wheel's normal force and the granular material variation with slip ratio provides the basis for establishing a physics-based wheel-sand interaction model. © 2023 IEEE.

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Multi-DoF Continuous Estimation for Wrist Torques Using Convolutional Neural Network

Multi-DoF Continuous Estimation for Wrist Torques Using Conv...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Fang, Yun Yu, Yang Guo, Weichao Sheng, Xinjun School of Mechanical Engineering Shanghai Jiao Tong University State Key Laboratory of Mechanical System and Vibration Shanghai200240 China Meta Robotics Institute Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781665481090

Using surface electromyography (sEMG) signals for simultaneous and proportional control (SPC) is appealing for natural control in human-machine interaction (HMI). Introducing spatial information across sEMG channels in the decoding process provides a more complete approach than methods that focus only on time and frequency domain features. In this article, we proposed an sEMG-based model for thesi-multaneous estimation of two degree-of-freedom (DoF) wrist torques, namely, Pro-Sup and Fle-Ext. Specifically, the 8 × 24 channels sEMG signals were transformed into images, which further served as inputs in a 29-layer convolutional neural network to estimate multi-DoF wrist torques. To prove the superiority of the CNN-based model, comparisons with other regression methods were performed on eight healthy subjects and two amputees in terms of the determination coefficient (R2) and normalized root mean square error (nRMSE). The results demonstrated that the CNN-based model (CNN-WAF) outperformed two conventional regression methods on estimation accuracy (R2: 0.851 ± 0.024 for Pro-Sup and 0.863 ± 0.016 for Fle-Ext;nRMSE: 6.933% ± 0.872% for Pro-Sup and 6.830% ± 0.856% for Fle-Ext). The average filtering in data preprocessing greatly improves (p © 2024 IEEE.

关键词： Convolutional neural networks

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Crosstalk-Free Dual-Mode Tactile Skin Based on 3D-Constrained Electric Field and Isolated Porous Iontronic Dielectric

Crosstalk-Free Dual-Mode Tactile Skin Based on 3D-Constraine...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Zhao, Yanchao Guo, Weichao Sheng, Xinjun School of Mechanical Engineering Shanghai Jiao Tong University State Key Laboratory of Mechanical System and Vibration Shanghai200240 China Meta Robotics Institute Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781665481090

Proximity-pressure dual-mode capacitive sensor is a novel sensing form to simultaneously detect distance and pressure information through a single device. In recent years, much effort has been devoted to improve its performance. However, it still suffers from robustness issues such as crosstalk and noise in practical applications. Electromagnetic coupling crosstalk caused by the outward electric fields as well as the response from unexpected directions also limit its distributed or array arrangements. In this regard, this paper proposes 3D-shielding structure as well as isolated iontronic dielectric designs to reduce the effects of electromagnetic/mechanical crosstalk. Through simulations and experiments, we demonstrate the effectiveness of the proposed design and optimise the structural parameters. The finally obtained sensing skin has an excellent crosstalk rejection ratio (15.68 dB, approximately three times improvement) while maintaining high response sensitivity. © 2024 IEEE.

关键词： Crosstalk

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An Efficient Planner for Dual-Arm Massage Robots in Constrained State

An Efficient Planner for Dual-Arm Massage Robots in Constrai...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Xu, Yuan Wang, Wenxiao Zhou, Lechuan Guo, Weichao Sheng, Xinjun Shanghai Jiao Tong University State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai200240 China Shanghai Jiao Tong University Meta Robotics Institute Shanghai200240 China

ISBN: (纸本)9781665481090

Dual-arm massage robots necessitate reaching the massage pose along an optimal collision-free path in constrained state, where traditional path planning methods often exhibit inefficiency. This paper proposes a sampling-based planning algorithm that integrates lazy evaluation, transition testing, and bidirectional Rapidly-exploring Random Tree to reduce computational load, enhance planning efficiency, and improve the planner's ability to effectively explore the state space, avoid local minima, and converge to high-quality solutions. Comparative experiments conducted on a simulation platform across multiple algorithms have demonstrated the efficacy of the proposed planner, achieving a 95 % planning success rate within 1 second. The paths generated by the algorithm exhibit superior quality and enhanced consistency. In summary, the proposed algorithm is capable of producing asymptotically optimal, collision-free paths for a dual-arm massage robot. © 2024 IEEE.

关键词： Robot programming

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A High-Speed Centerline Extraction Method for Multiple Laser Stripe based on Hessian Matrix

A High-Speed Centerline Extraction Method for Multiple Laser...

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International Conference on Biomimetic Intelligence and robotics & Medical robotics Forum, ICBIR+MRF 2024

作者： Shi, Juntian Guo, Weichao Sheng, Xinjun State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Meta Robotics Institute Shanghai Jiao Tong University Shanghai200240 China

Laser centerline extraction is a critical step in the machine vision-aided measurement process, especially in the field of aerospace drilling and riveting. We propose a novel and efficient algorithm for the extraction of multiple laser centerlines, which consists of three major parts: laser linewidth estimation, ROI (Region of Interest) extraction, and precise positioning. In the linewidth estimation part, a method based on second-order moment is used to estimate the linewidth, and the scanning frame to linewidth ratio is adopted as the convergence condition to achieve a stable estimation result. In the ROI extraction part, we use a scanning frame to perform raster scanning on the entire image, and calculate the feature function threshold based on the sampling and grayscale volume method to complete ROI extraction. In the precise positioning part, we employ an improved method based on the Hessian matrix to reduce computation time, and use a λ filtering method to eliminate noise. Finally, the K-means method is used to classify the center points belonging to different laser centerlines, and RANSAC is utilized to perform line fitting. The final results demonstrate that the proposed algorithm has certain improvements in accuracy and also exhibits high computational efficiency. © 2024 The Authors.

关键词： Linewidth

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