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TransForce: Transferable Force Prediction for Vision-based Tactile Sensors with Sequential Image Translation

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arXiv 2024年

作者： Chen, Zhuo Ou, Ni Zhang, Xuyang Luo, Shan The Robot Perception Lab Centre for Robotics Research Department of Engineering King's College London LondonWC2R 2LS United Kingdom The State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

Vision-based tactile sensors (VBTSs) provide high-resolution tactile images crucial for robot in-hand manipulation. However, force sensing in VBTSs is underutilized due to the costly and time-intensive process of acquiring paired tactile images and force labels. In this study, we introduce a transferable force prediction model, TransForce, designed to leverage collected image-force paired data for new sensors under varying illumination colors and marker patterns while improving the accuracy of predicted forces, especially in the shear direction. Our model effectively achieves translation of tactile images from the source domain to the target domain, ensuring that the generated tactile images reflect the illumination colors and marker patterns of the new sensors while accurately aligning the elastomer deformation observed in existing sensors, which is beneficial to force prediction of new sensors. As such, a recurrent force prediction model trained with generated sequential tactile images and existing force labels is employed to estimate higher-accuracy forces for new sensors with lowest average errors of 0.69N (5.8% in full work range) in x-axis, 0.70N (5.8%) in y-axis, and 1.11N (6.9%) in z-axis compared with models trained with single images. The experimental results also reveal that pure marker modality is more helpful than the RGB modality in improving the accuracy of force in the shear direction, while the RGB modality show better performance in the normal direction. Copyright © 2024, The Authors. All rights reserved.

关键词： RGB color model

Distributed Cooperative Attitude Tracking for Multiple Flexible Spacecraft under a Directed Graph

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Distributed Cooperative Attitude Tracking for Multiple Flexi...

第三十八届中国控制会议

作者： Lei Wang Zhuoyue Song Housheng Su Yiqun Zou Xiafei Tang State Key Laboratory of Intelligent Control and Decision of Complex Systems and School of Automation Beijing Institute of Technology School of Automation Huazhong University of Science and Technology School of Automation Central South University School of Electrical and Information Engineering Changsha University of Science and Technology

This paper is concerned with the problem of cooperative attitude tracking and vibration reduction for multiple flexible spacecraft without modal variable measurement under a directed communication topology. Firstly, a distributed attitude synchronization control law for MRPs representation is proposed in the absence of external disturbances, where the modal information is obtained using a modal variable estimator. To deal with a more practical case that the spacecraft are affected by external disturbances, the control law is further modified by integrating a disturbance observer and a feedforward compensating scheme,in which the lumped disturbances including the external disturbances and errors of the estimated modal information are observed and compensated in finite time. Under this enhanced control scheme, the attitude tracking errors and vibration variables will converge to zero even in the presence of external disturbances, and the controller is continuous and chattering-free. Besides,compared with the existing results, the communication graph in this paper is assumed to be directed and contain a spanning tree with the virtual leader as the root node. A numerical example is illustrated to demonstrate the effectiveness of the proposed results.

关键词： Attitude tracking Multiple flexible spacecraft Directed graph External disturbance

Marker or Markerless? Mode-Switchable Optical Tactile Sensing for Diverse Robot Tasks

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arXiv 2024年

作者： Ou, Ni Chen, Zhuo Luo, Shan The State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China The Robot Perception Lab. Centre for Robotics Research Department of Engineering King’s College London LondonWC2R 2LS United Kingdom

Optical tactile sensors play a pivotal role in robot perception and manipulation tasks. The membrane of these sensors can be painted with markers or remain markerless, enabling them to function in either marker or markerless mode. However, this uni-modal selection means the sensor is only suitable for either manipulation or perception tasks. While markers are vital for manipulation, they can also obstruct the camera, thereby impeding perception. The dilemma of selecting between marker and markerless modes presents a significant obstacle. To address this issue, we propose a novel mode-switchable optical tactile sensing approach that facilitates transitions between the two modes. The marker-to-markerless transition is achieved through a generative model, whereas its inverse transition is realized using a sparsely supervised regressive model. Our approach allows a single-mode optical sensor to operate effectively in both marker and markerless modes without the need for additional hardware, making it well-suited for both perception and manipulation tasks. Extensive experiments validate the effectiveness of our method. For perception tasks, our approach decreases the number of categories that include misclassified samples by 2 and improves contact area segmentation IoU by 3.53%. For manipulation tasks, our method attains a high success rate of 92.59% in slip detection. Code, dataset and demo videos are available at the project website https://***/Marker-Markerless-Transition/ Copyright © 2024, The Authors. All rights reserved.

关键词： Tactile sensors

Event-triggered Observability: A Set-membership Perspective

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arXiv 2022年

作者： Zheng, Kaikai Shi, Dawei Chen, Tongwen State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 1H9 Canada

This work attempts to discuss the observability of linear time-invariant systems with event-triggered measurements. A new notion of observability, namely, ǫ-observability is defined with parameter ǫ, which relates to the worst-case performance of inferring the initial state based on not only the received measurement but also the implicit information in the event-triggering conditions at no-event instants. A criterion is developed to test the proposed ǫ-observability of discrete-time linear systems, based on which an iterative event-triggered set-membership observer is designed to evaluate a set containing all possible values of the state. The proposed set-membership observer is designed as the outer approximation of the ellipsoids predicted based on previous state estimates and the ellipsoids inferred by fusing the received measurement and communication conditions, which is optimal in the sense of trace at each step and is proved to be asymptotically bounded. The efficiency of the proposed event-triggered set-membership state observer is verified by numerical experiments. © 2022, CC BY.

关键词： state estimation

An Adaptive Disturbance Rejection controller for Artificial Pancreas

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IFAC-PapersOnLine 2020年第2期53卷 16372-16379页

作者： Deheng Cai Wei Liu Eyal Dassau Francis J. Doyle Iii Xiaoling Cai Junzheng Wang Linong Ji Dawei Shi State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing 100081 China Department of Endocrine and Metabolism Peking University People’s Hospital Beijing China. Harvard John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge MA 02138 USA.

Artificial pancreas (AP) systems are designed to automate glucose management for patients with type 1 diabetes. In this work, we propose an adaptive disturbance rejection control approach for AP systems to achieve safe and effective glucose regulation. The controller is built within the framework of active disturbance rejection control, but incorporates safety operation constraints, and glucose- and velocity-dependent parameter adaptation modules for the key control parameters. In silico performance comparison between the proposed controller and an adaptive zone model predictive controller (MPC) (Shi, Dassau, and Doyle III, 2019a) is conducted on the 10-adult cohort of the FDA-accepted UVA/Padova T1DM simulator. For both announced and unannounced meals, the controller achieves comparable glucose regulation performance in terms of mean glucose (134.9 mg/dL vs. 135.4 mg/dL, p < 0.001; 149.7 mg/dL vs. 151.7 mg/dL, p < 0.001, respectively) and percentage time in [70, 180] mg/dL (93.8% vs. 92.4%, p < 0.001; 76.0% vs. 72.4%, p < 0.001, respectively) without increasing the risk of hypoglycemia. The results indicate the feasibility of achieving comparable glucose regulation performance through a non-optimization control law for AP systems.

关键词： Artificial pancreas Active disturbance rejection control Adaptive control Glucose regulation

Dual adaptive control of bimanual manipulation with online fuzzy parameter tuning

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Dual adaptive control of bimanual manipulation with online f...

IEEE International Symposium on intelligent control (ISIC)

作者： Alex Smith Chenguang Yang Hongbin Ma Phil Culverhouse Angelo Cangelosi Etienne Burdet Center for Robotics and Neural Systems Plymouth University Devon UK Key Laboratory of Autonomous System and Network Control South China University of Technology Guangzhou P. R. China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing P. R. China Department of Bioengineering Imperial College London UK

A biomimetic controller with online adaptation of impedance and force is applied to a full kinematic and dynamic model of the Baxter bimanual robot. A set of fuzzy logic engines are proposed to infer the values of tuning gains which affect the control performance and control effort of the controller, which would conventionally be set to a static value based on expert knowledge of the controller; the aim of this being to avoid the use of arbitary values to set these values. A simulated experiment is carried out, where the Baxter robot is required to move an object through a trajectory while subjected to two different disturbance forces in four phases. The controller with fuzzy inferred control gains is compared against the same controller with fixed gains to gauge the effectiveness of the new method. Results show that fuzzy inference of control gains impart an improvement in both tracking error and control effort.

关键词： Trajectory Fuzzy logic Force Dynamics Mathematical model Manipulators

state Estimation of Finite-state Hidden Markov Models Subject to Stochastically Event-triggered Measurements

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State Estimation of Finite-State Hidden Markov Models Subjec...

IEEE Annual Conference on decision and control

作者： Wentao Chen Junzheng Wang Ling Shi Dawei Shi State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing 100081 P.R. China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

ISBN: (纸本)9781479978878

We consider the event-triggered state estimation of a finite-state hidden Markov model with a general stochastic event-triggering condition. Utilizing the change of probability measure approach and the event-triggered measurement information available to the estimator, analytical expressions for the conditional probability distributions of the states are obtained, based on which the minimum mean square error event-based state estimates are further calculated. We show that the results also cover the case of packet dropout, under a special parameterization of the event-triggering conditions. With the results on state estimation, a closed-form expression of the average sensor-to-estimator communication rate is also presented. The effectiveness of the proposed results is illustrated by a numerical example and comparative simulations.

关键词： state estimation Hidden Markov models Event trigger Probability distribution Mean square error numerical example

Open-/Closed-loop Active Learning for Data-driven Predictive control

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arXiv 2024年

作者： Feng, Shilun Shi, Dawei Shi, Yang Zheng, Kaikai The State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing Institute of Technology Beijing100081 China The Department of Mechanical Engineering Faculty of Engineering University of Victoria VictoriaBCV8N 3P6 Canada

An important question in data-driven control is how to obtain an informative dataset. In this work, we consider the problem of effective data acquisition of an unknown linear system with bounded disturbance for both open-loop and closed-loop stages. The learning objective is to minimize the volume of the set of admissible systems. First, a performance measure based on historical data and the input sequence is introduced to characterize the upper bound of the volume of the set of admissible systems. On the basis of this performance measure, an open-loop active learning strategy is proposed to minimize the volume by actively designing inputs during the open-loop stage. For the closed-loop stage, an closed-loop active learning strategy is designed to select and learn from informative closed-loop data. The efficiency of the proposed closed-loop active learning strategy is proved by showing that the unselected data cannot benefit the learning performance. Furthermore, an adaptive predictive controller is designed in accordance with the proposed data acquisition approach. The recursive feasibility and the stability of the controller are proved by analyzing the effect of the closed-loop active learning strategy. Finally, numerical examples and comparisons illustrate the effectiveness of the proposed data acquisition strategy. Copyright © 2024, The Authors. All rights reserved.

关键词： Active learning

Solving almost all systems of random quadratic equations

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arXiv 2017年

作者： Wang, Gang Giannakis, Georgios B. Saad, Yousef Chen, Jie Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States State Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Department of Computer Science and Engineering University of Minnesota MinneapolisMN55455 United States

This paper deals with finding an n-dimensional solution x to a system of quadratic equations of the form yi = jhai;xij2 for 1 ≤ i ≤ m, which is also known as phase retrieval and is NP-hard in general. We put forth a novel procedure for minimizing the amplitude-based least-squares empirical loss, that starts with a weighted maximal correlation initialization obtainable with a few power or Lanczos iterations, followed by successive refinements based upon a sequence of iteratively reweighted (generalized) gradient iterations. The two (both the initialization and gradient flow) stages distinguish themselves from prior contributions by the inclusion of a fresh (re)weighting regularization technique. The overall algorithm is conceptually simple, numerically scalable, and easy-to-implement. For certain random measurement models, the novel procedure is shown capable of finding the true solution x in time proportional to reading the data f(ai;yi)g1≤i≤m. This holds with high probability and without extra assumption on the signal x to be recovered, provided that the number m of equations is some constant c > 0 times the number n of unknowns in the signal vector, namely, m > cn. Empirically, the upshots of this contribution are: I) (almost) 100% perfect signal recovery in the high-dimensional (say e.g., n ≥2;000) regime given only an information-theoretic limit number of noiseless equations, namely, m = 2n - 1 in the real-valued Gaussian case;and, ii) (nearly) optimal statistical accuracy in the presence of additive noise of bounded support. Finally, substantial numerical tests using both synthetic data and real images corroborate markedly improved signal recovery performance and computational efficiency of our novel procedure relative to state-of-the-art approaches. Copyright © 2017, The Authors. All rights reserved.

关键词： Computational efficiency