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arXiv 2022年

作者： Drummond, Ross Duncan, Stephen R. Turner, Matthew C. Pauli, Patricia Allgöwer, Frank Department of Engineering Science University of Oxford 17 Parks Road OxfordOX1 3PJ United Kingdom Department of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart70569 Germany

There is a growing debate on whether the future of feedback control systems will be dominated by data-driven or model-driven approaches. Each of these two approaches has their own complimentary set of advantages and disadvantages, however, only limited attempts have, so far, been developed to bridge the gap between them. To address this issue, this paper introduces a method to bound the worst-case error between feedback control policies based upon model predictive control (MPC) and neural networks (NNs). This result is leveraged into an approach to automatically synthesize MPC policies minimising the worst-case error with respect to a NN. Numerical examples highlight the application of the bounds, with the goal of the paper being to encourage a more quantitative understanding of the relationship between data-driven and model-driven control. © 2022, CC BY.

关键词： Model predictive control

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A distributed optimization algorithm for Nash bargaining in multi-agent systems ⁎

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IFAC-PapersOnLine 2020年第2期53卷 2684-2689页

作者： Andrea Camisa Philipp N. Köhler Matthias A. Müller Giuseppe Notarstefano Frank Allgöwer Department of Electrical Electronic and Information Engineering Alma Mater Studiorum Università di Bologna Bologna Italy Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany Institute of Automatic Control Leibniz University Hannover Hannover Germany

In this paper, we consider a multi-objective optimization problem over networks in which agents aim to maximize their own objective function, while satisfying both local and coupling constraints. This set up includes, e.g., the computation of optimal steady states in multi-agent control systems. Since fairness is a key feature required for the solution, we resort to Cooperative Game theory and search for the Nash bargaining solution among all the efficient (or Pareto optimal) points of a bargaining game. We propose a negotiation mechanism among the agents to compute such a solution in a distributed way. The problem is reformulated as the maximization of a properly weighted sum of the objective functions. The proposed algorithm is then a two step procedure in which local estimates of the Nash bargaining weights are updated online and existing distributed optimization algorithms are applied. The proposed method is formally analyzed for a particular case, while numerical simulations are provided to corroborate the theoretical findings and to demonstrate its efficacy

关键词： Cooperative game theory Distributed optimization Multi-Objective optimization Nash bargaining Distributed model predictive control Network games

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Radar-based Dynamic Occupancy Grid Mapping and Object Detection

Radar-based Dynamic Occupancy Grid Mapping and Object Detect...

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International Conference on Intelligent Transportation

作者： Christopher Diehl Eduard Feicho Alexander Schwambach Thomas Dammeier Eric Mares Torsten Bertram Institute of Control Theory and Systems Engineering Dortmund TU Germany HELLA Aglaia Mobile Vision GmbH Berlin Germany

ISBN: (数字)9781728141497

ISBN: (纸本)9781728141503

Environment modeling utilizing sensor data fusion and object tracking is crucial for safe automated driving. In recent years, the classical occupancy grid map approach, which assumes a static environment, has been extended to dynamic occupancy grid maps, which maintain the possibility of a lowlevel data fusion while also estimating the position and velocity distribution of the dynamic local environment. This paper presents the further development of a previous approach. To the best of the author's knowledge, there is no publication about dynamic occupancy grid mapping with subsequent analysis based only on radar data. Therefore in this work, the data of multiple radar sensors are fused, and a grid-based object tracking and mapping method is applied. Subsequently, the clustering of dynamic areas provides high-level object information. For comparison, also a lidar-based method is developed. The approach is evaluated qualitatively and quantitatively with real-world data from a moving vehicle in urban environments. The evaluation illustrates the advantages of the radar-based dynamic occupancy grid map, considering different comparison metrics.

关键词： Vehicle dynamics Sensors Particle measurements Atmospheric measurements Radar Laser radar Heuristic algorithms

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Interaction-Aware Trajectory Prediction based on a 3D Spatio-Temporal Tensor Representation using Convolutional–Recurrent Neural Networks

Interaction-Aware Trajectory Prediction based on a 3D Spatio...

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IEEE Symposium on Intelligent Vehicle

作者： Martin Krüger Anne Stockem Novo Till Nattermann Torsten Bertram Institute of Control Theory and Systems Engineering TU Dortmund University Dortmund Germany ZF Group Düsseldorf Germany

ISBN: (数字)9781728166735

ISBN: (纸本)9781728166742

Predicting the future trajectories for all vehicles relevant to the ego vehicle is a crucial, yet unsolved challenge to master automated driving. This paper proposes a combination of two lines of research for predicting all the trajectories of a group of vehicles of arbitrary size, considering the mutual interactions possible. Treating the prediction of other vehicles as a planning task for themselves enables the application of the artificial potential field approach. Modeling the driving situation as a potential field turns the trajectory prediction problem back to its original domain - utility space. Humans generate trajectories (that should be predicted) during driving by balancing costs and rewards, which lead to a total utility. The main difficulty inherent to the potential field approach is the hard problem of parameter tuning. Therefore, it is not directly used for prediction. Instead, the potential field representation is used as input for a neural network, which predicts a distribution over trajectories based on distinct maneuvers. This allows a multi-modal prediction for each vehicle and reflects the pattern recognition character.

关键词： Trajectory Three-dimensional displays Tensors Two dimensional displays Predictive models Planning Kernel

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Design of a Capsule Robot System for Gastric Hemorrhage Detection using Luminol

Design of a Capsule Robot System for Gastric Hemorrhage Dete...

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IEEE International Conference on Mechatronics and Automation

作者： Yuchen Mao Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Application Complicated Systems and Intelligent Robot Laboratory School of Electrical Engineering and Automation Tianjin University of Technology Binshui Xidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5 Zhongguancun South Street Beijing China

Gastric hemorrhage in upper gastrointestinal bleeding is an obvious indicator of deteriorating gastric disease. This paper proposes a capsule robot system for detecting bleeding in the stomach. The patient ingests a capsule robot containing luminol reagent, which detects bleeding in the stomach via chemiluminescence. The MCU receives the optical sensor signal, and the data is transmitted via radio frequency. The external lower computer receives and forwards the data to the upper computer for processing and display. The data is used to determine the presence and amount of stomach bleeding. Chemiluminescence is an excellent sensor, requiring no external energy supply, and demonstrating excellent sensitivity and selectivity. Combining chemical and electronic sensors presents opportunities for further development. Capsule robot detection reduces the discomfort and risk of secondary injury associated with traditional endoscopy. This paper establishes an experimental platform using porcine blood to simulate human blood, demonstrating the feasibility of the system.

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SLAM-Based Joint Calibration of Differential RSS Sensor Array and Source Localization

SLAM-Based Joint Calibration of Differential RSS Sensor Arra...

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Annual Conference of Industrial Electronics Society

作者： Linya Fu Xu Qiao Shoudong Huang Guoqiang Mao Zhiyun Lin Youfu Li He Kong Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern Uni. of Sci. and Tech. Shenzhen China Robotics Institute Uni. of Technology Sydney Sydney Australia State Key Laboratory of Integrated Services Networks Xidian University China Department of Mechanical Engineering City University of Hong Kong China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern Uni. of Sci. and Tech. Shenzhen China

Sensor arrays generating differential received signal strength (DRSS) measurements have found many applications in robotics. However, accurate calibration of these sensor arrays remains a challenge. Most existing methods are impractical in that they assume to know signal source positions or certain parameters (i.e., path loss exponent), and try to estimate the others. In this paper, we adopt graph simultaneous localization and mapping (SLAM) as a general framework for jointly estimating the source positions and parameters of the DRSS sensor array. Our contributions are twofold. On the one hand, by using a Fisher information matrix approach, we conduct a systematic observability analysis of the corresponding SLAM setup for the calibration problem. On the other hand, we propose an effective procedure to select the initial value which is fed to Levenberg-Marquardt iterations for further improving optimization accuracy and convergence. Extensive simulation and hardware experiments show that the proposed method renders high-quality calibration results. All the codes and data are publicly available at https://***/SUSTech2022/DRSS-sensor-array-calibration.

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Constrained extremum seeking: A modified-barrier function approach 11

Constrained extremum seeking: A modified-barrier function ap...

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11th IFAC Symposium on Nonlinear control systems, NOLCOS 2019

作者： Labar, Christophe Garone, Emanuele Kinnaert, Michel Ebenbauer, Christian Department of Control Engineering and System Analysis Université libre de Bruxelles Brussels1050 Belgium Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart70569 Germany

In this paper, we address the problem of steering the input of a convex function to a value that minimizes the function under a convex constraint. We consider the case where the constraint cannot be violated of more than a user-defined value during the whole transient phase. The mathematical expression of both the cost function and the constraint are assumed to be unknown. The only information available are the on-line values of the cost and the constraint. To tackle this problem, an optimization law, based on a modified-barrier function, and involving the gradient of both the cost function and the constraint, is firstly designed. The Lie bracket formalism is then exploited to approximate this law, by combining time-periodic signals with the on-line measurements of both the cost and the constraint. The stability property of the resulting constrained extremum seeking system is proved, and its effectiveness is shown in simulation. © 2019, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Cost functions

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Economic model predictive control for obstacle-aided snake robot locomotion

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IFAC-PapersOnLine 2020年第2期53卷 9702-9708页

作者： Evan Müller Philipp N. Köhler Kristin Y. Pettersen Frank Allgöwer Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany. Center for Autonomous Marine Operations and Systems Department of Engineering Cybernetics Norwegian University of Science and Technology Trondheim Norway.

This paper studies the application of economic model predictive control (MPC) to snake robot locomotion. The proposed MPC algorithm integrates the gait pattern creation into the closed loop by maximizing the forward snake velocity. We consider both purely planar locomotion as well as obstacle-aided locomotion. A compliant obstacle-snake contact model is introduced, rendering the interaction dynamics considered in the optimal control problem smooth. We illustrate the efficacy of the scheme by numerical simulations. The emerging gait patterns are undulatory and can make simultaneous use of anisotropic ground friction and obstacles.

关键词： Model Predictive control Mobile robots Obstacles Trajectory planning

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Study on 6D Pose Estimation System of Occlusion Targets for the Spherical Amphibious Robot based on Neural Network

Study on 6D Pose Estimation System of Occlusion Targets for ...

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IEEE International Conference on Mechatronics and Automation

作者： Chaofeng Du Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Applications in Complicated systems and Intelligent Robot Laboratory Tianjin University of Technology BinshuiXidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5 Zhongguancun South Street Beijing China

The amphibious robot needs to accurately estimate the 6D pose of the target in tasks such as target tracking, docking with the recovery module, and target grasping. The current research on target 6D pose estimation is mainly applied to unoccluded targets, but when the target is occluded, the target’s pose cannot be accurately identified. Compared with other algorithms, the PVNet algorithm shows better robustness when target is occluded, but the accuracy is still low. To improve the accuracy of the PVNet algorithm, this paper adds the confidence score prediction of the prediction vector at the last layer of the PVNet network, and designs a vector confidence score loss function to train the network. Before generating the hypothetical keypoints, the pixels whose confidence score is lower than the set threshold are screened out, so that the generated hypothetical 2D keypoints are closer to the true 2D keypoints. Finally, the method in this paper is compared with the Tekin, PoseCNN, Oberweger and Pvnet algorithm, and demonstrate the superiority of the proposed method.

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Study on control Strategy of the Vascular Interventional Surgical Robot Based on LADRC

Study on Control Strategy of the Vascular Interventional Sur...

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IEEE International Conference on Mechatronics and Automation

作者： Wenqiang Zhang Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Applications In Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Binshui Xidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5Zhongguancun South Street Beijing China

As a medical device used in surgery, the vascular interventional surgical robot itself needs to have good control accuracy to ensure the safety of the surgery process. Given this security problem, this paper selects the Line Active Disturbance Rejection control (LADRC) as the control strategy of the vascular interventional robot, aiming at improving the master-slave tracking accuracy of the vascular interventional robot. This article compares the LADRC and PID(Proportional-Integral-Derivative) control strategies through simulation and experiments. The experimental results show that LADRC has good control performance for master-slave tracking and can be applied to the vascular interventional surgical robots.

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