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arXiv 2023年

作者： Pauli, Patricia Wang, Ruigang Manchester, Ian R. Allgöwer, Frank The Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart70569 Germany The Australian Centre for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Australia

We establish a layer-wise parameterization for 1D convolutional neural networks (CNNs) with built-in end-to-end robustness guarantees. In doing so, we use the Lipschitz constant of the input-output mapping characterized by a CNN as a robustness measure. We base our parameterization on the Cayley transform that parameterizes orthogonal matrices and the controllability Gramian of the state space representation of the convolutional layers. The proposed parameterization by design fulfills linear matrix inequalities that are sufficient for Lipschitz continuity of the CNN, which further enables unconstrained training of Lipschitz-bounded 1D CNNs. Finally, we train Lipschitz-bounded 1D CNNs for the classification of heart arrythmia data and show their improved robustness. Copyright © 2023, The Authors. All rights reserved.

关键词： State space methods

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Sample Efficient Dynamics Learning for Symmetrical Legged Robots: Leveraging Physics Invariance and Geometric Symmetries

Sample Efficient Dynamics Learning for Symmetrical Legged Ro...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jee-eun Lee Jaemin Lee Tirthankar Bandyopadhyay Luis Sentis Department of Aerospace Engineering and Engineering Mechanics Human Centered Robotics Laboratory The University of Texas at Austin USA Department of Mechanical and Civil Engineering California Institute of Technology Pasadena CA USA Robotics and Autonomous Systems Group Data61 CSIRO QLD Australia Faculty of Department of Aerospace Engineering and Engineering Mechanics The University of Texas at Austin USA

Model generalization of the underlying dynamics is critical for achieving data efficiency when learning for robot control. This paper proposes a novel approach for learning dynamics leveraging the symmetry in the underlying robotic system, which allows for robust extrapolation from fewer samples. Existing frameworks that represent all data in vector space fail to consider the structured information of the robot, such as leg symmetry, rotational symmetry, and physics invariance. As a result, these schemes require vast amounts of training data to learn the system's redundant elements because they are learned independently. Instead, we propose considering the geometric prior by representing the system in symmetrical object groups and designing neural network architecture to assess invariance and equivariance between the objects. Finally, we demonstrate the effectiveness of our approach by comparing the generalization to unseen data of the proposed model and the existing models. We also implement a controller of a climbing robot based on learned inverse dynamics models. The results show that our method generates accurate control inputs that help the robot reach the desired state while requiring less training data than existing methods.

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Fractional-Order Global Fast Terminal Sliding Mode Control Strategy for Fractional-Order Hydraulic Turbine Regulating System

Fractional-Order Global Fast Terminal Sliding Mode Control S...

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Chinese Control Conference (CCC)

作者： Shiyu Xi Zhihuan Chen Engineering Research 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

Hydraulic turbine regulating system (HTRS) directly affects the safety and stability of hydro-generator units. In this paper, the control and modeling problems of the HTRS are mainly investigated based on the fractional-order theory, aiming to design a novel control strategy to raise the dynamic response of the HTRS and ensure the frequency stability of the hydro-generator units. Firstly, a nonlinear model of the fractional-order HTRS is established mathematically. Secondly, a fractional-order global fast terminal sliding mode controller is designed to improve the dynamic performance as well as the robustness of the system. Finally, relevant simulations are carried out to illustrate the effectiveness and rationality of the proposed control strategy in comparison with two other fractional-order control strategies.

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How to turn your camera into a perfect pinhole model

arXiv

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arXiv 2023年

作者： De Boi, Ivan Pathak, Stuti Oliveira, Marina Penne, Rudi InViLab University of Antwerp Groenenborgerlaan 171 Antwerp2020 Belgium Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Coimbra3004-531 Portugal

Camera calibration is a first and fundamental step in various computer vision applications. Despite being an active field of research, Zhang's method remains widely used for camera calibration due to its implementation in popular toolboxes like MATLAB and OpenCV. However, this method initially assumes a pinhole model with oversimplified distortion models. In this work, we propose a novel approach that involves a pre-processing step to remove distortions from images by means of Gaussian processes. Our method does not need to assume any distortion model and can be applied to severely warped images, even in the case of multiple distortion sources, e.g., a fisheye image of a curved mirror reflection. The Gaussian processes capture all distortions and camera imperfections, resulting in virtual images as though taken by an ideal pinhole camera with square pixels. Furthermore, this ideal GP-camera only needs one image of a square grid calibration pattern. This model allows for a serious upgrade of many algorithms and applications that are designed in a pure projective geometry setting but with a performance that is very sensitive to nonlinear lens distortions. We demonstrate the effectiveness of our method by simplifying Zhang's calibration method, reducing the number of parameters and getting rid of the distortion parameters and iterative optimization. We validate by means of synthetic data and real world images. The contributions of this work include the construction of a virtual ideal pinhole camera using Gaussian processes, a simplified calibration method and lens distortion removal. Copyright © 2023, The Authors. All rights reserved.

关键词： Pinhole cameras

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Whole-Body MPC for Highly Redundant Legged Manipulators: Experimental Evaluation with a 37 DoF Dual-Arm Quadruped

Whole-Body MPC for Highly Redundant Legged Manipulators: Exp...

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IEEE-RAS International Conference on Humanoid Robots

作者： Ioannis Dadiotis Arturo Laurenzi Nikos Tsagarakis Humanoid and Human-Centered Mechatronics Research Line Italian Institute of Technology Genoa Italy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa Italy

Recent progress in legged locomotion has rendered quadruped manipulators a promising solution for performing tasks that require both mobility and manipulation (loco-manipulation). In the real world, task specifications and/or environment constraints may require the quadruped manipulator to be equipped with high redundancy as well as whole-body motion coordination capabilities. This work presents an experimental evaluation of a whole-body Model Predictive Control (MPC) framework achieving real-time performance on a dual-arm quadruped platform consisting of 37 actuated joints. To the best of our knowledge this is the legged manipulator with the highest number of joints to be controlled with real-time whole-body MPC so far. The computational efficiency of the MPC while considering the full robot kinematics and the centroidal dynamics model builds upon an open-source DDP-variant solver and a state-of-the-art optimal control problem formulation. Differently from previous works on quadruped manipulators, the MPC is directly interfaced with the low-level joint impedance controllers without the need of designing an instantaneous whole-body controller. The feasibility on the real hardware is showcased using the CENTAURO platform for the challenging task of picking a heavy object from the ground. Dynamic stepping (trotting) is also showcased for first time with this robot. The results highlight the potential of replanning with whole-body information in a predictive control loop.

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Evolutionary Morphology Towards Overconstrained Locomotion via Large-Scale, Multi-Terrain Deep Reinforcement Learning

Evolutionary Morphology Towards Overconstrained Locomotion v...

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ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots, ReMAR

作者： Yenan Chen Chuye Zhang Pengxi Gu Jianuo Qiu Jiayi Yin Nuofan Qiu Guojing Huang Bangchao Huang Zishang Zhang Hui Deng Wei Zhang Fang Wan Chaoyang Song Department of Mechanical and Energy Engineering Southern University of Science and Technology (SUSTech) Shenzhen China SUSTech School of Design Department of System Design and Intelligent Manufacturing SUSTech. Shenzhen Key Lab of Intelligent Robotics & Flexible Manufacturing Systems SUSTech. SUSTech. SUSTech Institute of Robotics

ISBN: (数字)9798350395969

ISBN: (纸本)9798350395976

While the animals' Fin-to-Limb evolution has been well-researched in biology, such morphological transformation remains under-adopted in the modern design of advanced robotic limbs. This paper investigates a novel class of overconstrained locomotion from a design and learning perspective inspired by evolutionary morphology, aiming to integrate the concept of ‘intelligent design under constraints’–hereafter referred to as constraint-driven design intelligence–in developing modern robotic limbs with superior energy efficiency. We propose a 3D-printable design of robotic limbs parametrically reconfigurable as a classical planar 4-bar linkage, an overconstrained Bennett linkage, and a spherical 4- bar linkage. These limbs adopt a co-axial actuation, identical to the modern legged robot platforms, with the added capability of upgrading into a wheel-legged system. Then, we implemented a large-scale, multi-terrain deep reinforcement learning framework to train these reconfigurable limbs for a comparative analysis of overconstrained locomotion in energy efficiency. Results show that the overconstrained limbs exhibit more efficient locomotion than planar limbs during forward and sideways walking over different terrains, including floors, slopes, and stairs, with or without random noises, by saving at least 22% mechanical energy in completing the traverse task, with the spherical limbs being the least efficient. It also achieves the highest average speed of 0.85m/s on flat terrain, which is 20% faster than the planar limbs. This study paves the path for an exciting direction for future research in overconstrained robotics leveraging evolutionary morphology and reconfigurable mechanism intelligence when combined with state-of-the-art methods in deep reinforcement learning.

关键词： Couplings Legged locomotion Technological innovation Education Noise Morphology Stairs

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Impact of multi-dimensional cognitive demands on takeover performance, physiological and eye-tracking measures in conditionally automated vehicles

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Transportation Research Part F: Traffic Psychology and Behaviour 2025年 114卷 461-475页

作者： Ange Wang Wenxin Shi Dengbo He Hai Yang Thrust of Intelligent Transportation Systems Hub The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology Hong Kong SAR China Thrust of Robotics and Autonomous Systems Systems Hub The Hong Kong University of Science and Technology (Guangzhou) China HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute Futian Shenzhen China

Before fully autonomous vehicles come true, drivers are still required to be responsible for driving safety and take over control of the vehicle when prompted by takeover requests in conditionally automated vehicles. Thus, drivers’ takeover performance can affect the safety of conditionally automated driving. However, though cognitive distraction can impair takeover performance in general, the influence of multi-dimensionality in the cognitive resources was under-investigated. At the same time, it is unknown how physiological and eye-tracking metrics are associated with different modalities of cognitive tasks in conditionally automated vehicles. Thus, through a driving simulation study with 42 participants, we investigated the effects of multidimensional cognitive demands, as imposed by multiple types of non-driving-related tasks, on drivers’ takeover performance, physiological responses, and eye-tracking metrics in conditionally automated vehicles. Results showed that certain takeover performance (i.e., vehicle speed and lateral acceleration), and physiological and eye-tracking metrics (i.e., differences between consecutive R-peaks, skin conductance level, variation in respiratory intervals, number of fixations, number of saccades and saccade angle) are still responsive to cognitive load in the context of driving automation. Further, the modality of the cognitive tasks can moderate the takeover performance (i.e., takeover time) and certain physiological (i.e., ratio of spectral power in the low- and high-frequency range and respiration depth) metrics. These findings suggest that, in future conditionally automated vehicles, in-vehicle task designs should consider the modality of the cognitive demands for driving safety and for the performance of the driver monitoring systems.

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Adaptive observer for a nonlinear system with partially unknown state matrix and delayed measurements

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IFAC-PapersOnLine 2023年第2期56卷 8702-8707页

作者： Olga Kozachek Alexey Bobtsov Nikolay Nikolaev Department of Control Systems and Robotics ITMO University Kronverkskiy av. 49 Saint-Petersburg 197101 Russia Laboratory “Control of Complex Systems” Institute of Problems of Mechanical Engineering V.O. Bolshoj pr. 61 St. Petersburg 199178 Russia

Problem of an adaptive state observer design for nonlinear system with unknown time-varying parameters and under condition of delayed measurements is considered. State observation problem was raised by many researchers (see for example Sanx et al. (2019)). In this paper the results proposed in Bobtsov et al. (2021b), Bobtsov et al. (2021a), Bobtsov et al. (2022a), Bobtsov et al. (2022b) are developed. The problem is solved under assumption that the state matrix can be represented as sum of known and unknown parts. The output vector is measured with a known constant delay. An adaptive observer which reconstructs unmeasured state and unknown time-varying parameter is proposed.

关键词： nonlinear system delay adaptive observer parameter identification

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Reliability Design of Manipulator Joint for China Space Station 2

Reliability Design of Manipulator Joint for China Space Stat...

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2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2022

作者： Li, Delun Zhu, Chao Zhang, Yun Bai, Mei Huang, Zhipeng Xie, Zongwu Liu, Teng Fu, Hao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering CAST Beijing100094 China Beijing Satellite Manufacturing Co. Ltd. Beijing100094 China Beijing Institute of Space Environment Engineering Beijing100094 China

ISBN: (纸本)9781510657717

The TianHe manipulator is responsible for major tasks such as China Space Station construction, operation, and supporting astronaut's extravehicular operations. The joint is the direct execution part of the manipulator to realize flexible movement, and it is the key component to ensure the core functions and performance of the China Space Station manipulator, The composition of the joint is complex, and the experience of its reliability design is very poor. So the research of reliability design method for the joint is of great significance. Starting from the joint reliability design method, this paper uses various methods such as redundant design, margin design, and environmental adaptability design to complete the joint reliability design comprehensively. The ideas and methods for reliability design for the joint of the China Space Station manipulator introduced in this paper have important reference value for the reliability design for the space complicated electromechanical products. © 2022 SPIE. All rights reserved.

关键词： Space stations

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LoRa technology application within the Internet of Flying Things concept for data collection from IoT devices

LoRa technology application within the Internet of Flying Th...

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Information, Control, and Communication Technologies (ICCT), International Conference on

作者： Alexander Dubelschikov Timur Gamberov Tatyana Tsoy Kuo-Hsien Hsia Evgeni Magid Tikhonov Moscow Institute of Electronics and Mathematics HSE University Moscow Russia Laboratory of Intelligent Robotics Systems (LIRS) Institute of Information Technology and Intelligent Systems Kazan Federal University Kazan Russia Graduate School Engineering Science and Technology National Yunlin University of Science & Technology Taiwan The Republic of China

ISBN: (数字)9798331517564

ISBN: (纸本)9798331517571

The Internet of Flying Things is one of the priority areas for robotics and automation research and applications. A promising case is an application of UAVs in a search and rescue scenario for data collection from pre-positioned IoT devices, which allows assessing and monitoring a current situation in an operation area. This paper presents a concept of using a low-power LoRa protocol to transmit data from smart sensors to UAVs that deliver the data to a dedicated cloud for further processing and analysis. A mock-up of a structure, which is described in the paper, is to be realized using microcontrollers, LoRa modules and smart temperature sensors.

关键词： Temperature sensors Protocols Microcontrollers LoRa Data collection Communications technology Internet of Things robotics and automation Monitoring Intelligent sensors

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