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Chinese Automation Congress (CAC)

作者： Wei Li Lei Xie Hongye Su State Key Laboratory of Industrial Control Technology and Institute of Cyber-systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

In the automatic driving of vehicles, it is a very common way to separate the motion control into two levels, the first is trajectory planning and the next is path tracking. In this paper, we introduce a fast cornering way for the vehicle based on the two steps. First, choosing a better trajectory rather than centerline of the road to follow in order to reduce the passing time. The desired trajectory is described as the optimal linear combination of the shortest path and the fastest speed path. It was expressed as a bounded optimal problem to solve. Once the trajectory has been determined, it is necessary to design a path tracker. We construct a controller based on vehicle's dynamics and environmental conditions using model predictive control (MPC). Then an experiment was implemented on CARSIM and MATLAB joint simulation. And the results showed that the presented approach is able to reduce the passing time and keep the vehicle within the lane.

关键词： Trajectory Roads Predictive models Mathematical model Optimization Vehicle dynamics Trajectory planning

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PREGAN: Pose randomization and estimation for weakly paired image style translation

arXiv

引用

arXiv 2020年

作者： Chen, Zexi Guo, Jiaxin Xu, Xuecheng Wang, Yunkai Wang, Yue Xiong, Rong State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang China

Utilizing the trained model under different conditions without data annotation is attractive for robot applications. Towards this goal, one class of methods is to translate the image style from another environment to the one on which models are trained. In this paper, we propose a weakly-paired setting for the style translation, where the content in the two images is aligned with errors in poses. These images could be acquired by different sensors in different conditions that share an overlapping region, e.g. with LiDAR or stereo cameras, from sunny days or foggy nights. We consider this setting to be more practical with: (i) easier labeling than the paired data;(ii) better interpretability and detail retrieval than the unpaired data. To translate across such images, we propose PREGAN to train a style translator by intentionally transforming the two images with a random pose, and to estimate the given random pose by differentiable non-trainable pose estimator given that the more aligned in style, the better the estimated result is. Such adversarial training enforces the network to learn the style translation, avoiding being entangled with other variations. Finally, PREGAN is validated on both simulated and real-world collected data to show the effectiveness. Results on down-stream tasks, classification, road segmentation, object detection, and feature matching show its potential for real applications. Code is available here. Copyright © 2020, The Authors. All rights reserved.

关键词： Stereo image processing

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Distributed Adaptive Cooperative control for a Class of Nonlinear Multi-Agent systems with Input Saturation

Distributed Adaptive Cooperative Control for a Class of Nonl...

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IEEE Conference on industrial Electronics and Applications (ICIEA)

作者： Ming Xiao Zhitao Liu Hongye Su State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9781728151694

ISBN: (纸本)9781728151700

In this paper, the consensus control for a class of nonlinear multi-agent systems with input saturation is considered. A smooth function is used to approximate the saturation function for every agent, then by combining the adaptive backstepping method and Nussbaum function, a new distributed adaptive cooperative control method is proposed for the multi-agent system with input saturation. The consensus tracking errors of the multi-agent system are bounded, and the closed-loop system is globally stable. Simulation results of three-agents with input saturation shows the effectiveness and performance of the proposed method.

关键词： industrial electronics Backstepping Simulation Conferences Stability analysis Tuning Multi-agent systems

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Radar-on-Lidar: metric radar localization on prior lidar maps

Radar-on-Lidar: metric radar localization on prior lidar map...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Huan Yin Yue Wang Li Tang Rong Xiong State Key Laboratory of Industrial Control and Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

Radar and lidar, provided by two different range sensors, each has pros and cons of various perception tasks on mobile robots or autonomous driving. In this paper, a Monte Carlo system is used to localize the robot with a rotating radar sensor on 2D lidar maps. We first train a conditional generative adversarial network to transfer raw radar data to lidar data, and achieve reliable radar points from generator. Then an efficient radar odometry is included in the Monte Carlo system. Combining the initial guess from odometry, a measurement model is proposed to match the radar data and prior lidar maps for final 2D positioning. We demonstrate the effectiveness of the proposed localization framework on the public multisession dataset. The experimental results show that our system can achieve high accuracy for long-term localization in outdoor scenes.

关键词： Laser radar Radar Sensors Radar imaging Robots Three-dimensional displays Two dimensional displays

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Multi-Objective Optimization of the Wireless Power Transfer System for Electric Vehicles

Multi-Objective Optimization of the Wireless Power Transfer ...

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IEEE Wireless Power Transfer Conference (WPTC)

作者： Ze Zhou Zhitao Liu Hongye Su State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9781728142388

ISBN: (纸本)9781728142395

Wireless power transfer (WPT) technology is an effective charging method for electric vehicles. However, when the output power reaches a certain grade, the efficiency decreases with an increase in the output power. Based on this problem, we establish the loss power model of the WPT system, and analyze the efficiency of the WPT system in detail, as well as proposes a multi-objective optimization method to find an optimal control target between the output power and efficiency. Finally, simulation results illustrate that the output power is 10.4 kW and the efficiency is 92.97 % when the system is in the optimal solution state.

关键词： Power generation Simulation Inverters Wireless power transfer Mathematical model MOSFET Immune system

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Efficient Planar Pose Estimation via UWB Measurements

Efficient Planar Pose Estimation via UWB Measurements

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Haodong Jiang Wentao Wang Yuan Shen Xinghan Li Xiaoqiang Ren Biqiang Mu Junfeng Wu Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS) School of Data Science the Chinese University of HongKong Shenzhen P. R. China College of Control Science and Engineering and the State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou P. R. China School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing P. R. China School of Mechatronic Engineering and Automation Shanghai University Shanghai P. R. China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing P. R. China

state estimation is an essential part of autonomous systems. Integrating the Ultra-Wideband (UWB) technique has been shown to correct the long-term estimation drift and bypass the complexity of loop closure detection. However, few works on robotics treat UWB as a stand-alone state estimation solution. The primary purpose of this work is to investigate planar pose estimation using only UWB range measurements. We prove the excellent property of a two-step scheme, which says we can refine a consistent estimator to be asymptotically efficient by one step of Gauss-Newton iteration. Grounded on this result, we design the GN-ULS estimator, which reduces the computation time significantly compared to previous methods and presents the possibility of using only UWB for real-time state estimation.

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A Closed-Loop control Strategy of Maximum Efficiency Point Tracking for Wireless Power Charging System

A Closed-Loop Control Strategy of Maximum Efficiency Point T...

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IEEE Wireless Power Transfer Conference (WPTC)

作者： Jia Liu Zhitao Liu Hongye Su State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9781728142388

ISBN: (纸本)9781728142395

In recent decades, the wireless power transfer (WP-T) has drawn increasing attention of researchers, and the transfer efficiency is one of the most concern aspect. In this paper, a closed-loop control strategy of maximum efficiency point (MEP) tracking is proposed. During the wireless power charging process, the transfer efficiency decreases according to the various load condition and mutual inductor. With the analysis of the optimal load condition and the real-time estimation of mutual inductor, the impedance matching for MEP tracking can be achieved. The buck converter is added to obtain the optimal load condition and the boost converter is inserted to achieve the constant output voltage. By the simulation results, the performance of the closed-loop MEP tracking control strategy has been verified.

关键词： Inductors Resistors Buck converters Voltage control Inductive charging Transmitters Receivers

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CORAL: Colored structural representation for bi-modal place recognition

arXiv

引用

arXiv 2020年

作者： Pan, Yiyuan Xu, Xuecheng Li, Weijie Cui, Yunxiang Wang, Yue Xiong, Rong The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang China

Place recognition is indispensable for a drift-free localization system. Due to the variations of the environment, place recognition using single-modality has limitations. In this paper, we propose a bi-modal place recognition method, which can extract a compound global descriptor from the two modalities, vision and LiDAR. Specifically, we first build the elevation image generated from 3D points as a structural representation. Then, we derive the correspondences between 3D points and image pixels that are further used in merging the pixel-wise visual features into the elevation map grids. In this way, we fuse the structural features and visual features in the consistent bird-eye view frame, yielding a semantic representation, namely CORAL. And the whole network is called CORAL-VLAD. Comparisons on the Oxford RobotCar show that CORAL-VLAD has superior performance against other state-of-the-art methods. We also demonstrate that our network can be generalized to other scenes and sensor configurations on cross-city datasets. © 2020, CC BY.

关键词： Pixels

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External forces resilient safe motion planning for quadrotor

arXiv

引用

arXiv 2021年

作者： Wu, Yuwei Ding, Ziming Xu, Chao Gao, Fei State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States

Adaptive autonomous navigation with no prior knowledge of extraneous disturbance is of great significance for quadrotors in a complex and unknown environment. The mainstream approach that considers external disturbance is to implement disturbance-rejected control and path tracking. However, the robust control to compensate for tracking deviations is not well-considered regarding energy consumption, and even the reference path will become risky and intractable with disturbance. As recent external forces estimation advances, it is possible to incorporate a real-time force estimator to develop more robust and safe planning frameworks. This paper proposes a systematic (re)planning framework that can resiliently generate safe trajectories under volatile conditions. Firstly, a front-end kinodynamic path is searched with force-biased motion primitives. Then we develop a nonlinear model predictive control (NMPC) as a local planner with Hamilton-Jacobi (HJ) forward reachability analysis for error dynamics caused by external forces. It guarantees collision avoidance by constraining the ellipsoid of the quadrotor body expanded with the forward reachable sets (FRSs) within safe convex polytopes. Our method is validated in simulations and real-world experiments with different sources of external forces. Copyright © 2021, The Authors. All rights reserved.

关键词： Collision avoidance

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A Human-Robot Collaboration System for Object Handover

A Human-Robot Collaboration System for Object Handover

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IEEE International Conference on Robotics and Biomimetics

作者： Yifei Yang Longzhong Lin Yifan Zhang Zhongxiang Zhou Yue Wang Rong Xiong State Key Laboratory of Industrial Control Technology and Institute of Cyber-Systems and Control of Zhejiang Province Zhejiang University Hangzhou P.R. China College of Electrical Engineering Zhejiang University Hangzhou P.R. China

ISBN: (纸本)9781665405362

Humans and robots are the two main labor in industry, and they have respective advantages. Human-Robot Collaboration combines the advantages of humans and robots, which makes it a research hotspot. While there are a lot of research and developments in the field of Human-Robot Collaboration, how to apply and optimize existing technologies to realize a complete Human-Robot Collaboration system is not a very focused problem. So, we realize a Human-Robot Collaboration system for object handover: the human holds a container (denoted as ContainerA), and the robot holds the other container (denoted as ContainerB) with some contents as a collaborator; the robot uses computer vision to detect ContainerA and estimate position and orientation of it; then the robot plans and controls the motion of the robot arm based on the visual information, and hand over the contents in ContainerB to ContainerA. For computer vision, we use Fast- SCNN for semantic segmentation and REDE for pose estimation, which can obtain the accurate pose of the hand-held container in real time. In terms of robot arm motion planning and control, we perform speed control based on artificial potential field and admittance control to achieve a smooth follow-up movement.

关键词： Visualization Service robots Semantics Pose estimation Collaboration Object segmentation Containers

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