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27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024

作者： Long, Tingting Zong, Mengru Zhang, Chi Liu, Yuehu Ma, Shuangxun Li, Li National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence Shaanxi Xi'an China School of Electrical Engineering Xi' An Jiaotong University Shaanxi Xi'an China School of Future Transportation Changan University Xi'an710064 China BNRist Tsinghua University Department of Automation Beijing100084 China

ISBN: (纸本)9798331505929

Validating safe and reliable interaction with vulnerable road users (VRUs) is imperative for autonomous vehicles, especially in simulation testing procedures before on-road applications. However, existing VRU agents are either with predefined routes or with collision-oriented behaviors, which limits the fidelity and diversity of scenarios. Bridging the gap between the simulated world and reality requires realistic VRU behaviors. In this paper, we apply social force to capture natural human behavior, considering how individuals are influenced by their surroundings and adhere to real-world rules. To this end, we propose HybridSFM, an improved social force model designed for characterizing human-vehicle interacting behavior. Specifically, the steering and acceleration of the VRUs are parameterized and integrated with social norms to forecast trajectories. Based on this, we further implement a gradient optimization framework for generating VRU-AV safety-critical scenarios. Firstly, VRUs are positioned randomly around the ego-agent. Differentiable simulation updates states and unrolls trajectories while backpropagation optimizes the actions of VRUs. The modified scenario is further optimized in the subsequent time step until a collision happens. The experiments demonstrate that our approach can enhance realistic safety-critical scenarios at intersection scenarios, facilitating the testing of interaction capabilities for autonomous vehicles. © 2024 IEEE.

关键词： Autonomous vehicles

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Safety-Critical Scenario Generation by Causal Influence Detection 27

Safety-Critical Scenario Generation by Causal Influence Dete...

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27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024

作者： Yang, Yibing Zhang, Chi Xu, Linhai Ma, Shuangxun Li, Li Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications Shaanxi Xi'an China School of Future Transportation Chang'an University Xi'an710064 China Tsinghua University BNRist Department of Automation Beijing100084 China

ISBN: (纸本)9798331505929

Appropriate behavior intervention for a specific background vehicle at the right moment is a crucial step in identifying safety-critical scenarios. Existing methods generate scenarios by estimating the data distribution, but when noise interventions are present, the emergence of safety-critical scenarios becomes colinearity with the noise interventions, potentially resulting in unnecessary interventions and unrealistic vehicle behaviors. To address this, we propose to integrate the causal relationship between the background vehicle behavior and the safety status of ego-vehicle as a prior into scenario generation. In this notion, we present a reinforcement learning framework with a causal influence detection module (CausalID). Specifically, we employ conditional mutual information to quantify the causal influence between vehicle sequential behaviors, and intervene on the background vehicle's behavior when the causal influence exceeds a certain threshold. Additionally, to prevent unrealistic collision-oriented driving, we sample the final intervention action from a set of candidate actions according to their probabilities of occurring in natural driving scenarios. Our experiments in 3-lane highway scenarios with multiple vehicles validate the effectiveness of the proposed framework. © 2024 IEEE.

关键词： Vehicle safety

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Torque Optimization Strategy for Hip and Knee Joint of Passive Lower Limb Exoskeleton*

Torque Optimization Strategy for Hip and Knee Joint of Passi...

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Yafei Ou Guangkui Song Rui Huang Chaobin Zou Zhinan Peng Xingzhong Xiong Jing Qiu Hong Cheng Artificial Intelligence Key Laboratory of Sichuan Province (AIKLSP) School of Automation and Information Engineering Sichuan University of Science and Engineering Yibin China Center for Robotics School of Automation Engineering University Electronic Science and Technology of China Chengdu China school of Mechanical Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Passive Lower Limb Exoskeleton (PLLE) have attracted extensive attention because it can help to participate in the application scenarios related to human functions. For the scenario of assisted stair climbing, the exoskeleton should have favorable and assisted torque to improve energy utilization efficiency. This paper studies a genetic algorithm-based auxiliary torque optimization strategy to find the optimal auxiliary torque of the exoskeleton hip joint and knee joint. And the simulation experiment based on the exoskeleton system verifies the effectiveness of the proposed strategy.

关键词： Legged locomotion Knee Torque Mechatronics Exoskeletons Stairs Springs Optimization Hip Robots

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Logarithmic Sliding-Mode Control for High-Precision Rigid-Body Attitude Tracking 49

Logarithmic Sliding-Mode Control for High-Precision Rigid-Bo...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Dong, Hanlin Yang, Xuebo Chen, Zhongbo Liu, Xiyao School of Automation Northwestern Polytechnical University Xi'an China Research Institute of Intelligent Control Systems Harbin Institute of Technology Harbin China College of Control Science and Engineering Bohai University Jinzhou China Northwestern Polytechnical University Research Center for Intelligent Robotics Xi'an China

ISBN: (纸本)9798350331820

The problem of high-precision attitude tracking is studied in this paper under model uncertainty and external disturbance risk. First of all, the kinematics and dynamics model of rigid body is derived based on the quaternion theory. Then, a standard logarithmic sliding-mode function is constructed using the attitude quaternion and its derivatives of the rigid spacecraft, and the corresponding logarithmic sliding-mode controller is also derived. Finally, the stability of the controlled closed-loop system is demonstrated. Consistenting with theoretical proof, the numerical simulation results showed that the controlled rigid body can quickly track its desired attitude command, even if there are model uncertainty and external disturbance risks. © 2023 IEEE.

关键词： Disturbance rejection

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Gesture Control Method for Oral Blood Mixed Liquid Removal Robot∗ 5

Gesture Control Method for Oral Blood Mixed Liquid Removal R...

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5th World Robot Conference Symposium on Advanced robotics and automation, WRC SARA 2023

作者： Ma, Xudong Kuang, Ziao Li, Han Chen, Anqi Li, Changsheng Liu, Wenyong Wang, Junchen Hu, Yida David Gao, Li Su, Bai-Quan Beijing University of Posts and Tele-communications Medical Robotics Laboratory School of Automation Beijing100876 China Beijing University of Posts and Tele-communications School of Computer Beijing100876 China Beijing Institute of Technology School of Mechatronical Engineering Beijing100081 China Beihang University Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry Beijing Advanced Innovation Centre for Biomedical Engineering School of Biological Science and Medical Engineering Beijing100083 China Beihang University School of Mechanical Engineering and Automation Beijing100083 China Brigham and Women's Hospital Harvard Medical School BostonMA02115 United States Peking University School and Hospital of Stomatology National Clinical Research Center for Oral Diseases National Stomatological Center Department of Periodontology Beijing China

ISBN: (纸本)9798350307320

All of oral surgeries are accompanied by bleeding. Manual removal of blood is carried out by a nurse and dozens of repetitive blood suction operations are implemented by the nurse during a single oral surgery. In our previous work, a robot for removal of blood-water mixed liquid is designed. However, the robot requires an initial order to autonomous removal of blood mixed liquid. In this paper, a hand gesture control method for typical operations of the robot is developed. Gesture dataset are developed at first and a deep learning neural network is trained for detection of hand gesture. The gesture control procedures for four typical operations are provided in detail. In a group of experiments, it's demonstrated that an oral surgeon controls the robot's motion by presenting prescribed hand gesture. The proposed method could be an alternative manner for blood mixed liquid removal. © 2023 IEEE.

关键词： Blood

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A Novel Gas Classification Method Based on The Improved GasNet

A Novel Gas Classification Method Based on The Improved GasN...

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第43届中国控制会议

作者： Xiaolin Qin Lei Cheng Xiang Tao Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology School of Information Science and Engineering Wuhan University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Accurately and promptly identifying harmful gases in the environment can effectively prevent many accidents. Most existing pattern recognition methods are focused on addressing gas classification problems in static scenarios, but the real world is a dynamic and changing environment. Therefore, researching gas classification in continuous learning scenarios will better meet the needs of suddenly emerging gas classification tasks in real-world environments. To address this issue, an incremental learning model was introduced into gas classification, and an improved deep convolutional network was proposed for gas image feature extraction. The proposed model and other baseline methods experimented on an open-source gas dataset. The proposed model reduces knowledge loss due to catastrophic forgetting and effectively classifies the 10 gas samples in the dataset in continuous learning scenarios compared to non-incremental methods. It outperforms other baseline incremental methods by optimizing the network's shortcut connections, making the feature extraction network easier to train and improving gas classification performance. In dynamic learning scenarios, the proposed model achieved a classification accuracy of 86.30% for 10 gas *** experimental results demonstrate that the proposed method effectively mitigates catastrophic forgetting interference and completes gas classification tasks in continuous learning scenarios.

关键词： Gas classification Incremental learning Shortcut connection Catastrophic forgetting

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Gas Source Localization for UAV Using Infotaxis-Based Three-Dimensional Algorithm and Particle Filtering

Gas Source Localization for UAV Using Infotaxis-Based Three-...

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第43届中国控制会议

作者： Duan He Cheng Lei Wang Rong Zhang Yu Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology School of Information Science and Engineering Wuhan University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Unmanned aerial vehicles(UAVs) are extensively utilized in gas source localization tasks due to their payload capacity and maneuverability. This paper presents a UAV gas source localization algorithm that utilizes three-dimensional Infotaxis and particle filter. The algorithm is designed for gas source localization of UAVs in dynamic outdoor airflow *** source localization process comprises UAV search area partitioning, particle filter initialization, observation and update of probability map, entropy calculation and direction selection, particle direction and weight update, and UAV movement. To validate the effectiveness of the algorithm, we build a CFD gas environment and UAV source localization platform, and compare it with traditional Infotaxis-based source localization algorithms. The proposed algorithm based on three-dimensional Infotaxis and particle filter demonstrates higher accuracy.

关键词： infotaxis particle filtering gas source localization olfactory drone path planning

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Research on Path Planning of Mobile Robots Based on Snow Ablation Optimizer

Research on Path Planning of Mobile Robots Based on Snow Abl...

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第43届中国控制会议

作者： Wenlong Chen Zile Wang Yuhang Yang Siqi Wang Heng Wang Yasar Ayaz School of Automation and Electrical Engineering University of Science and Technology Beijing National Center of Artificial Intelligence (NCAI) Department of Robotics and Artificial Intelligence National University of Sciences and Technology (NUST)

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Path planning is one of the key technologies for mobile robots. Metaheuristic algorithms hold significant promise in generating an effective and reliable path for mobile robots. However, most metaheuristic algorithms do not balance exploration and exploitation in the solution space, which may lead to premature convergence and cannot guarantee to find a satisfying *** ablation optimizer(SAO) is a novel metaheuristic technique based on the sublimation and melting phenomenon of snow,which can overcome the shortcomings of most other metaheuristic algorithms. This paper proposes a path planning method for mobile robots based on the SAO algorithm and undertakes a comparative study with the planning method based on particle swarm optimization(PSO) using simulation experiments. The results show that the proposed path planner is superior to the PSO-based path planner in both planning speed and path quality.

关键词： Path Planning Mobile Robots Snow Ablation Optimizer Particle Swarm Optimization

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Fractional-Order Fast Terminal Sliding Mode Control for Quadrotor UAV under Actuator Saturation

Fractional-Order Fast Terminal Sliding Mode Control for Quad...

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2023 China automation Congress, CAC 2023

作者： Li, Changjun Chen, Zhihuan Zhu, Zhenhua Wuhan University of Science and Technology Eng. Res. Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9798350303759

In this study, a delicate fractional-order fast terminal sliding mode controller is proposed for the position and attitude tracking of a quadrotor UAV under actuator saturation. In this controller, the fractional order calculus is incorporated to the fast terminal sliding mode surface design, which can enhance the convergence speed of the controlled UAV system. Meanwhile, to solve the problem of actual control input limitation, a RBF-based estimator is designed to evaluate the error between the virtual control input and actual control output. The stability of the controlled system is proved by using Lyapunov theorem, where the validity and effectiveness of the proposed controllers and estimator are verified by a detailed numerical simulation. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Optimal Bioprinting Parameters and Experimental Investigation of Acellular Dermal Matrix Scaffold

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Journal of Renewable Materials 2021年第1期9卷 1-16页

作者： Qingxi Hu Yiming Wang Dongchao Yang Haiguang Zhang Zhicheng Song Yan Gu Rapid Manufacturing Engineering Center School of Mechatronic Engineering and AutomationShanghai UniversityShanghaiChina Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai UniversityShanghaiChina National Demonstration Center for Experimental Engineering Training Education Shanghai UniversityShanghaiChina Shanghai Ninth People’s Hospital Shanghai JiaoTong University School of MedicineShanghai200011China

Acellular dermal matrix(ADM)as a biomaterial is currently believed to be promising tissue repair *** the development of tissue engineering,ADM is increasingly used as biological *** explored the feasibility and performance of ADM biological scaffolds that fabricated by 3D *** paper presented our study on the printability of 3D printed ADM scaffolds,with a focus on identifying the influence of printing parameters/conditions on *** characterize the printability,we examined the fiber morphology,pore size,strand diameter,and mechanical property of the printed *** results revealed that the printability could be affected by a number of factors and among them,the most considerable one was related to the nozzle diameter and the composition of *** then evaluated the biocompatibility in terms of cytotoxicity,cell proliferation and *** vitro evaluation of the ADM scaffolds was carried out and the experimental results indicated that cells were viable and proliferative during the period of *** vivo results also indicated that the defect area was well repaired without any noticeable infection,hematoma and other *** conclusion,ADM could be reconstructed with 3D printing technology and ADM biological scaffold has potential applications for tissue engineering.

关键词： Bioprinting acellular dermal matrix scaffolds printability tissue engineering

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