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DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition

DeepRING: Learning Roto-translation Invariant Representation...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Sha Lu Xuecheng Xu Li Tang Rong Xiong Yue Wang State Key Laboratory of Industrial Control and Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Alibaba Group Hangzhou China

LiDAR based place recognition is popular for loop closure detection and re-localization. In recent years, deep learning brings improvements to place recognition by learnable feature extraction. However, these methods degenerate when the robot re-visits previous places with a large perspective difference. To address the challenge, we propose DeepRING to learn the roto-translation invariant representation from LiDAR scan, so that robot visiting the same place with a different perspective can have similar representations. There are two keys in DeepRING: the feature is extracted from sinogram, and the feature is aggregated by magnitude spectrum. The two steps keep the final representation with both discrimination and roto-translation invariance. Moreover, we state place recognition as a one-shot learning problem with each place being a class, leveraging relation learning to build representation similarity. Substantial experiments are carried out on public datasets, validating the effectiveness of each proposed component, and showing that DeepRING outperforms the comparative methods, especially in dataset level generalization.

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Incremental Nonlinear Dynamic Inversion for a Dual-Ducted-Fan UAV Attitude control under In-Ground-Effect

Incremental Nonlinear Dynamic Inversion for a Dual-Ducted-Fa...

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Intelligent robotics and Automatic control (IRAC), International Conference on

作者： Zixiao Cheng Hailong Pei Kai Fang College of Automation Science and Engineering South China University of Technology Guangzhou China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangzhou China Guangdong Engineering Technology Research Center of Unmanned Aerial Vehicle Systems Guangzhou China

ISBN: (数字)9798350389807

ISBN: (纸本)9798350389814

This paper is aimed at modeling and attitude control of a dual-ducted-fan UAV under in-ground-effect(IGE). As the UAV flies and hovers over ground or above obstacles, the IGE can cause changes in thrust/torque that drastically affects flight behavior, especially during takeoff/landing. To address this problem, the paper derives a six degree-of-freedom model of the aircraft dynamics firstly. Then, key parameters and in-ground-effect features are obtained through measurements. In order to achieve stable attitude tracking control with in-ground-effect adapting, an incremental nonlinear dynamic inversion(INDI) based cascade controller is designed. Finally, the performance of the designed INDI controller is verified by stability proof, simulations and real flight experiments.

关键词： Adaptation models Fans Attitude control Atmospheric modeling Autonomous aerial vehicles Stability analysis Data models Nonlinear dynamical systems Motion measurement Aircraft

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Learning to Turn: Deformation control of a Novel Flexible Fishtail Actuated by Artificial Muscles

Learning to Turn: Deformation Control of a Novel Flexible Fi...

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IEEE International Conference on Cyborg and Bionic systems (CBS)

作者： Junwen Gu Yukai Feng Zhengxing Wu Jian Wang Junzhi Yu Key Laboratory of Cognition and Decision Intelligence for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Department of Advanced Manufacturing and Robotics State Key Laboratory for Turbulence and Complex Systems College of Engineering Peking University Beijing China

ISBN: (数字)9798350388039

ISBN: (纸本)9798350388046

Achieving agile, fish-like turning remains a critical challenge in the development of robotic fish. The flexible deformation of a fish’s body significantly contributes to its turning ability. Consequently, researchers have devoted substantial efforts to enhancing the compliance and agility of robotic fish. This paper presents a novel flexible fishtail, inspired by the musculoskeletal structure of real fish, which can control the deformation of its flexible components during turns, improving the turning performance of robotic fish. The fishtail primarily consists of a carbon fiber plate with attached artificial muscles. These muscles can contract and stretch, causing the carbon fiber tail to bend and deform. To enable precise deformation control, a dynamic model of the fishtail is established based on Hamilton’s principle. Subsequently, deep reinforcement learning methods such as deep deterministic policy gradient and soft actor-critic are employed to develop a deformation controller under joint deflection. Cross-validation ensures the controller’s accuracy and robustness. The experimental results demonstrate that this controller facilitates the deformation control of the flexible tail across various turning amplitudes and speeds, allowing the fishtail to exhibit adjustable compliance or resistance to fluids during turning motion. Consequently, this enhances the agility of the robotic fish.

关键词： Artificial muscles Deformation Tail Learning (artificial intelligence) Muscles Turning Fish Robustness Carbon Robots

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Intention-Aware Planner for Robust and Safe Aerial Tracking

Intention-Aware Planner for Robust and Safe Aerial Tracking

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Qiuyu Ren Huan Yu Jiajun Dai Zhi Zheng Jun Meng Li Xu Chao Xu Fei Gao Yanjun Cao The State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China The Robotics Institute of Zhejiang University Yuyao China Huzhou Institute Zhejiang University Huzhou China Huzhou Laboratory of Autonomous Intelligent Systems Huzhou China College of Electrical Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Autonomous target tracking with quadrotors has wide applications in many scenarios, such as cinematographic follow-up shooting or suspect chasing. Target motion prediction is necessary when designing the tracking planner. However, the widely used constant velocity or constant rotation assumption can not fully capture the dynamics of the target. The tracker may fail when the target happens to move aggressively, such as sudden turn or deceleration. In this paper, we propose an intention-aware planner by additionally considering the intention of the target to enhance safety and robustness in aerial tracking applications. Firstly, a designated intention prediction method is proposed, which combines a user-defined potential assessment function and a state observation function. A reachable region is generated to speci cally evaluate the turning intentions. Then we design an intention-driven hybrid A* method to predict the future possible positions for the target. Finally, an intention-aware optimization approach is designed to generate a spatial-temporal optimal trajectory, allowing the tracker to perceive unexpected situations from the target. Benchmark comparisons and real-world experiments are conducted to validate the performance of our method.

关键词： Target tracking Semantics Prediction methods Turning Prediction algorithms Robustness Safety Planning Trajectory optimization Quadrotors

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An Optimal control Based Trajectory Planning Method for Cooperative Merging Maneuvers

An Optimal Control Based Trajectory Planning Method for Coop...

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Intelligent robotics and systems (ISoIRS), International Symposium on

作者： Qi Wang Hao Ge Xuting Duan Jianshan Zhou State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control State Key Laboratory of Air Traffic Management System and Technology School of Transportation Science and Engineering Beihang University Beijing China State Key Laboratory of Air Traffic Management System and Technology Nanjing Research Institute of Electronic Engineering Nanjing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China

Due to the prediction errors and diverse driving styles of surrounding vehicles, traffic congestion and even accidents can occur in the traffic bottleneck area where vehicles merge into the main road. To ensure that connected and automated vehicles (CAVs) can quickly and efficiently merge into the main road, this paper proposes a cooperative trajectory planning method based on optimal control for vehicle cut-in scenarios. A optimal control model is constructed, and a quintic polynomial is used to generate the initial solution of the optimal control problem to accelerate the solution process and improve the success rate. Finally, The obtained merging trajectory is then synchronized with the movement of vehicles on the main road to optimize their actions and ensure a safe merging process. Joint simulation with Robot Operating System (ROS) and RVIZ is utilized, and the results show that the proposed algorithm can quickly obtain cooperative results, the locally successful merging trajectory meets the requirements of smoothness and safety, and if the solution does not allow merging, the merging vehicle is instructed to terminate the execution.

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Research on Sensorless control of Pulse Generator based on Sliding Mode Observer

Research on Sensorless Control of Pulse Generator based on S...

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Artificial Intelligence and Automation control (AIAC), International Conference on

作者： Hui Zhang Zhiguo Wu Bopi Jin Shengxuan Yang Guoliang Yin College of Electrical and Control Engineering Shenyang Jianzhu University Shenyang China Shenyang Institute of Automation & Institutes of Robotics and Intelligent Manufacturing Chinese Academy of Sciences College of Electrical and Control Engineering Shenyang Jianzhu University & State Key Laboratory of Robotics Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences & Institutes of Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

To address the problems of chattering and slow response in the sliding mode control system of surface-mounted permanent magnet synchronous motor (SPMSM), a novel sliding mode controller combined with an enhanced sliding mode observer is proposed. A new reaching law of sliding mode is designed, which uses the tanh function as the switching function of the control system to smooth the switching process. The terminal attractor is introduced to improve the convergence speed and control quality of the system. An improved sliding mode observer is developed, which replaces the sign function with a continuous function, compensates for the observation error, reduces the chattering effect, and improves the observation accuracy. A simulation model of double closed-loop speed control system based on the proposed sliding mode controller and observer is established, and a simulation experiment is conducted to compare it with the PI control system and the sliding mode control system based on exponential reaching law. The simulation results show that the proposed control strategy can effectively diminish the chattering effect, enhance the system convergence, and better track the given signal.

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Optimization of Simulation Parameters of Input Shaper Based on Genetic Algorithm 2

Optimization of Simulation Parameters of Input Shaper Based ...

引用

2nd IEEE International Conference on Advanced Technologies in Intelligent control, Environment, Computing and Communication Engineering, ICATIECE 2022

作者： Yi, Tao Pei, Quanshen Li, Deying Wei, Shugong Jia, Danping Zhang, Hualiang Hunan University of Information Changsha China School of Information Science and Engineering Shenyang University of Technology Shenyang China College of Physics and Electronic Engineering Guangxi Normal University for Nationalities Chongzuo China Chinese Academy of Sciences Shenyang Institute of Automation Key Laboratory of Networked Control Systems Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China

ISBN: (纸本)9781665493963

In the motion control system, input shaper is often used to suppress the residual oscillation of high-precision positioning system, but the selection of input shaper parameters is difficult. In view of the difficulty of selecting input shaper parameters, this paper proposes to use genetic algorithm to select the parameters of input shaper. Firstly, the input shaper is designed in the light of the three-loop mathematical model of motor;Secondly, because the genetic algorithm directly optimizes the output of the motor and the algorithm can reduce the influence of the deviation of generator parameters on the parameter selection of the input shaper to a certain extent, the parameters of the input shaper are selected by the genetic algorithm to optimize the output of the motor;In the finish, a comparative experiment between a system with input shaper and a system with simple PID control is carried out. The results show that the optimized system can obtain higher robustness and smaller tracking deviation. © 2022 IEEE.

关键词： Genetic algorithms

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SlowFast GCN Network for Quantification of Parkinsonian Gait Using 2D Videos 12

SlowFast GCN Network for Quantification of Parkinsonian Gait...

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12th International Conference on CYBER Technology in Automation, control, and Intelligent systems, CYBER 2022

作者： Zeng, Qingyi Liu, Peipei Bai, Ying Yu, Huan Sun, Xiaoyi Han, Jianda Wu, Jialing Yu, Ningbo College of Artificial Intelligence Nankai University Haihe Education Park Tianjin300350 China Tianjin Key Laboratory of Intelligent Robotics Nankai University Haihe Education Park Tianjin300350 China Department of Neurology Tianjin Huanhu Hospital Tianjin300350 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institute of Intelligence Technology and Robotics Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Parkinson's disease(PD) is a progressive neu-rodegenerative disease defined by clinical syndrome including bradykinesia, tremor and postural instability. The PD-related disability and impairment are usually monitored by clinicals using the MDS-UPDRS scale. However, due to COVID-19, it became much harder for the patients to reach hospitals and obtain necessary assessment and treatment. Nowadays, 2D videos are easily accessible and can be a promising so-lution for on-site and remote diagnosis of movement disorder. Inspired by the frequency-based video processing mechanism of human visual system, we propose a video-based SlowFast GCN network to quantify the gait disorder. The model consists of two parts: the fast pathway and the slow pathway. The former detects characteristics such as tremor and bilateral asymmetry, while the latter extracts characteristics such as bradykinesia and freezing of gait. Furthermore, in order to investigate the influence of age on the model performance, an aged control group and a young control group were set up for verification. The proposed model was evaluated on a video dataset collected from 68 participants. We achieved a balanced accuracy of 87.5% and precision of 87.9%, which outperformed existing competing methods. When replacing the young healthy controls with the same number of older controls, the balanced accuracy and precision were decreased by 10.4% and 9.7%, which indicates that age has a significant effect on the model perfomance. © 2022 IEEE.

关键词： COVID-19

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Design of an Acupuncture Robot with Vision-Guided Positioning and Force Compliance control

Design of an Acupuncture Robot with Vision-Guided Positionin...

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robotics & Intelligent Manufacturing Technology (ISRIMT), International Symposium on

作者： Zhengtao Chen Bochen Li Yanhao Feng Genliang Chen Hao Wang Shanghai Key Laboratory of Digital Manufacturing for Thin-Walled Structures Shanghai Jiao Tong University Shanghai China Meta Robotics Institute Shanghai Jiao Tong University Shanghai China State Key Laboratory of Mechanical Systems and Vibration Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331528942

ISBN: (纸本)9798331528959

Acupuncture is a classic treatment method in traditional Chinese medicine. At present, it mainly relies on experienced doctors for manual treatment. The inheritance of skills and the guarantee of treatment effects require lots of training to guarantee, which is far from meeting needs. In this paper, an acupuncture robot system was designed to ensure the accuracy of acupoint positioning and safety during needle insertion, making robot-assisted acupuncture treatment a feasible alternative. The acupuncture robot has an acupoint marking and visual guidance system. According to the location of the acupoints accurately marked by the doctor on the patient's 3D reconstructed model, the robot is accurately guided to perform acupuncture treatment. The positioning error of this system is within 1.5mm, which meets the needs of acupuncture. In addition, a terminal needle-punching manipulator with compliant needle insertion force control, needle insertion depth feedback, and continuous needle insertion functions is designed. Through the closed-loop control of the needle-punching manipulator, the safety and accuracy of the acupuncture robot are fully guaranteed. Finally, an acupuncture experiment was designed to verify the accuracy and safety of the acupuncture robot.

关键词： Training Visualization Accuracy Three-dimensional displays Medical services Needles Manipulators Acupuncture Safety Force control

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Design and Implementation of OpenWSN Hardware Platform

Design and Implementation of OpenWSN Hardware Platform

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Algorithms, High Performance Computing and Artificial Intelligence (AHPCAI), International Conference on

作者： Shusheng Zhang Chuang Xie Jun Liu Chun Zhao Zhijia Yang Jizhi Mao College of Automation and Electrical Engineering Shenyang Ligong University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

This paper proposes a new wireless sensor network hardware platform based on OpenWSN project launched by the University of California, Berkeley. The hardware platform's processor uses a 32-bit microcontroller (STM32F103RCT6) produced by STMicroelectronics (ST), and the wireless module uses the WISA470 chip. The final experimental results show that this platform can support the Open WSN project very well.

关键词： Wireless communication Radio frequency Wireless sensor networks Protocols Power supplies Microcontrollers Hardware

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