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Dynamic modeling and control simulation of a modified delta manipulator

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Dynamic modeling and control simulation of a modified delta ...

International Conference on Information and Automation (ICIA)

作者： Jianlong Hao Xiaoliang Xie Guibin Bian Zhenqiu Feng Zhanjie Gao Zengguang Hou Hongnian Yu Luige Vladareanu State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Faculty of Science and Technology Bournemouth University Poole Dorset UK Robotics and Mechatronics Department Romanian Academy Romian

ISBN: (纸本)9781467391054

The delta parallel mechanism has proven to be a very successful parallel robot design and a number of variants have been proposed in the literature. Taking advantage of its simple construction and the intrinsic features such as high stiffness and accuracy, delta robots play an important role both in the fields of industrial robots and academical fields. In this paper, dynamic modeling and control simulation of a cable-driven modified delta manipulator for haptic interface are discussed. For the parallel mechanism is highly coupled and nonlinear, the dynamic model is of great importance for model-based controller to achieve a satisfactory performance. Based on the principle of virtual work, the dynamic equations of this manipulator are established. The proportional-derivative (PD) computed torque control scheme is proposed for trajectory tracking. With the help of the virtual prototype builded in ADAMS software and used in MATLAB software, the co-simulation is accomplished and the results validate the performance of the controller proposed in this paper.

关键词： Manipulator dynamics Joints Mathematical model Computational modeling Prototypes Trajectory

Mitigating Motion Sickness with Optimization-based Motion Planning

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arXiv 2023年

作者： Zheng, Yanggu Shyrokau, Barys Keviczky, Tamas The Department of Cognitive Robotics Faculty of Mechanical Maritime and Materials Engineering Delft University of Technology 2628CD Netherlands Delft Center for Systems and Control Faculty of Mechanical Maritime and Materials Engineering Delft University of Technology 2628CD Netherlands

The acceptance of automated driving is under the potential threat of motion sickness. It hinders the passengers’ willingness to perform secondary activities. In order to mitigate motion sickness in automated vehicles, we propose an optimization-based motion planning algorithm that minimizes the distribution of acceleration energy within the frequency range that is found to be the most nauseogenic. The algorithm is formulated into integral and receding-horizon variants and compared with a commonly used alternative approach aiming to minimize accelerations in general. The proposed approach can reduce frequency-weighted acceleration by up to 11.3% compared with not considering the frequency sensitivity for the price of reduced overall acceleration comfort. Our simulation studies also reveal a loss of performance by the receding-horizon approach over the integral approach when varying the preview time and nominal sampling time. The computation time of the receding-horizon planner is around or below the real-time threshold when using a longer sampling time but without causing significant performance loss. We also present the results of experiments conducted to measure the performance of human drivers on a public road section that the simulated scenario is actually based on. The proposed method can achieve a 19% improvement in general acceleration comfort or a 32% reduction in squared motion sickness dose value over the best-performing participant. The results demonstrate considerable potential for improving motion comfort and mitigating motion sickness using our approach in automated vehicles. © 2023, CC BY-NC-ND.

关键词： Motion planning

A novel approach to the Model Reference Adaptive control of MIMO systems

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A novel approach to the Model Reference Adaptive Control of ...

IEEE International Workshop on robotics in Alpe-Adria-Danube Region (RAAD)

作者： J.K. Tar I.J. Rudas J.F. Bitó K.R. Kozłowski C. Pozna John von Neumann Faculty of Informatics buda University Budapest Hungary Chair of Control and Systems Engineering Poznan University of Technology Poznan Poland Design and Robotics Department University Transilvania of Brasov Brasov Romania

The “Model Reference Adaptive control (MRAC)” is a popular approach from the early nineties to our days. Its basic idea is the application of proper feedback that makes the behavior of the controlled system identical to that of the “reference model” that normally is simple enough to control. The idea has many particular variants with the common feature that they are designed by the use of Lyapunov's 2 nd (“direct”) method that normally applies a quadratic Lyapunov function constructed of the tracking error and further additional terms. Though this approach normally guarantees global asymptotic stability, its use can entail complicated tuning that may have disadvantages whenever very fast applications are needed. In this paper an alternative problem tackling, the application of “Robust Fixed Point Transformations (RFPT)” in the MRAC technique is recommended. This approach applies strongly saturated, multiplicative nonlinear terms causing a kind of “deformation” of the input of the available imprecise system model. Instead parameter tuning that is typical in the traditional MRAC it operates with a simple convergence guaranteed only within a local basin of attraction. This technique can well compensate the simultaneous consequences of modeling errors and external disturbances that normally can “fob” the more traditional, tuning based approaches. As a potential application paradigm the novel MRAC control of a “cart - beam - hamper” system is considered. The conclusions of the paper are illustrated by simulation results.

关键词： Adaptive control MIMO Lyapunov method Motion control Programmable control Intelligent robots systems engineering and theory control systems control system synthesis Asymptotic stability

A Robotic Framework for the Robot@Factory 4.0 Competition

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A Robotic Framework for the Robot@Factory 4.0 Competition

IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Ricardo B. Sousa Cláudia D. Rocha João G. Martins João Pedro Costa João Tomás Padrão José Maria Sarmento José Pedro Carvalho Maria S. Lopes Paulo G. Costa António Paulo Moreira Faculty of Engineering University of Porto (FEUP) Porto Portugal CRIIS - Centre for Robotics in Industry and Intelligent Systems INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal University of Trás-os-Montes and Alto Douro (UTAD) Vila Real Portugal C2SR - Cyber-Physical Control Systems and Robotics SYSTEC - Research Center for Systems and Technologies Porto Portugal

ISBN: (数字)9798350352344

ISBN: (纸本)9798350352351

Robotic competitions stand as platforms to propel the forefront of robotics research while nurturing STEM education, serving as hubs of both applied research and scientific innovation. In Portugal, the Portuguese robotics Open (FNR) is an event with several robotic competitions, including the Robot@Factory 4.0 competition. This competition presents an example of deploying autonomous robots on a factory shop floor. Although the literature has works proposing frameworks for the original version of the Robot@Factory competition, none of them proposes a system framework for the Robot@Factory 4.0 version that presents the hardware, firmware, and software to complete the competition and achieve autonomous navigation. This paper proposes a complete robotic framework for the Robot@Factory 4.0 competition that is modular and open-access, enabling future participants to use and improve it in future editions. This work is the culmination of all the knowledge acquired by winning the 2022 and 2023 editions of the competition.

关键词： Technological innovation Education Propulsion Production facilities Software Hardware Autonomous robots

Comfort-oriented driving: performance comparison between human drivers and motion planners

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arXiv 2023年

Motion planning is a fundamental component in automated vehicles. It influences the comfort and time efficiency of the ride. Despite a vast collection of studies working towards improving motion comfort in self-driving cars, little attention has been paid to the performance of human drivers as a baseline. In this paper, we present an experimental study conducted on a public road using an instrumented vehicle to investigate how human drivers balance comfort and time efficiency. The human driving data is compared with two optimization-based motion planners that we developed in the past. In situations when there is no difference in travel times, human drivers incurred an average of 23.5% more energy in the longitudinal and lateral acceleration signals than the motion planner that minimizes accelerations. In terms of frequency-weighted acceleration energy, an indicator correlated with the incidence of motion sickness, the average performance deficiency rises to 70.2%. Frequency-domain analysis reveals that human drivers exhibit more longitudinal oscillations in the frequency range of 0.2-1 Hz and more lateral oscillations in the frequency range of up to 0.2 Hz. This is reflected in time-domain data features such as less smooth speed profiles and higher velocities for long turns. The performance difference also partly results from several practical matters and additional factors considered by human drivers when planning and controlling vehicle motion. The driving data collected in this study provides a performance baseline for motion planning algorithms to compare with and can be further exploited to deepen the understanding of human drivers. © 2023, CC BY-NC-ND.

关键词： Frequency domain analysis

Robust control of Interleaved Boost Converter for Open-Cathode PEM Fuel Cell systems

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Robust Control of Interleaved Boost Converter for Open-Catho...

IEEE International Conference on Automatic control and Intelligent systems (I2CACIS)

作者： Jie Ying Tan R.M.T Raja Ismail Institute of Postgraduate Studies Universiti Malaysia Pahang Pekan Pahang Malaysia Robotics Intelligent Systems & Control Engineering (RISC) Research Group Faculty of Electrical & Electronics Universiti Malaysia Pahang Pekan Pahang Malaysia

This paper implements a thermal control and a super-twisting sliding mode (STSM) incorporated with an interleaved boost converter (IBC) for an open-cathode proton exchange membrane fuel cell (OC-PEMFC). The implementation of the thermal control is to regulate the stack temperature and adjust the air stoichiometric during the fuel cell current variation. The STSM controller is designed to ensure the fuel cell system’s robustness by achieving the reference values set. Therefore, simulation results discussed that the thermal control provides the suitable stack temperature to the system and maintains the fan voltage during temperature variations. A PI controller is designed and used as a comparison to the proposed STSM controller. Hence, the proposed STSM demonstrates its effectiveness in tracking down the reference current values for the fuel cell system.

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Skill Assessment Using Kinematic Signatures: Geomagic Touch Haptic Device

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Skill Assessment Using Kinematic Signatures: Geomagic Touch ...

RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： N. S. Hojati M. Motaharifar H. D. Taghirad A. Malekzadeh Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence (ICCE) Faculty of Electrical Engineering K.N. Toosi University of Technology Tehran Iran Faculty of Mathematics K.N. Toosi University of Technology Tehran Iran

ISBN: (数字)9781728166049

ISBN: (纸本)9781728166056

The aim of this paper is to develop a practical skill assessment for some designed experimental tasks, retrieved from Minimally Invasive Surgery. The skill evaluation is very important in surgery training, especially in MIS. Most of the previous studies for skill assessment methods are limited in the Hidden Markov Model and some frequency transforms, such as Discrete Fourier transform, Discrete Cosine Transform and etc. In this paper, some features have been extracted from time-frequency analysis with the Discrete Wavelet Transform and temporal signal analysis of some kinematic metrics which were computed from Geomagic Touch kinematic data. In addition, the k-nearest neighbors classifier are employed to detect skill level based on extracted features. Through cross-validation results, it is demonstrated that the proposed methodology has annrouriate accuracy in skill level detection.

关键词： Feature extraction Measurement Discrete wavelet transforms Haptic interfaces Surgery Microsoft Windows

Adaptive finite-time and fixed-time control design using output stability conditions

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arXiv 2021年

作者： Zimenko, Konstantin Efimov, Denis Polyakov, Andrey Faculty of Control Systems and Robotics ITMO University 49 Kronverkskiy av. Saint Petersburg197101 Russia Inria Univ. Lille CNRS UMR 9189 - CRIStAL LilleF-59000 France

The present paper provides a sufficient condition to ensure output finite-time and fixed-time stability. Comparing with analogous researches the proposed result is less restrictive and obtained for a wider class of systems. The presented output stability condition is used for adaptive control design, where the state vector of a plant is extended by adjustable control parameters. © 2021, CC BY.

关键词： Stability

Human intention recognition for human aware planning in integrated warehouse systems

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arXiv 2020年

作者： Petković, Tomislav Hvězda, Jakub Rybecký, Tomáš Marković, Ivan Kulich, Miroslav Přeučil, Libor Petrović, Ivan University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Laboratory for Autonomous Systems and Mobile Robotics Unska 3 ZagrebHR-10000 Croatia Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague160 00 Czech Republic

With the substantial growth of logistics businesses the need for larger and more automated warehouses increases, thus giving rise to fully robotized shop-floors with mobile robots in charge of transporting and distributing goods. However, even in fully automatized warehouse systems the need for human intervention frequently arises, whether because of maintenance or because of fulfilling specific orders, thus bringing mobile robots and humans ever closer in an integrated warehouse environment. In order to ensure smooth and efficient operation of such a warehouse, paths of both robots and humans need to be carefully planned;however, due to the possibility of humans deviating from the assigned path, this becomes an even more challenging task. Given that, the supervising system should be able to recognize human intentions and its alternative paths in real-time. In this paper, we propose a framework for human deviation detection and intention recognition which outputs the most probable paths of the humans workers and the planner that acts accordingly by replanning for robots to move out of the human's path. Experimental results demonstrate that the proposed framework increases total number of deliveries, especially human deliveries, and reduces human-robot encounters. Copyright © 2020, The Authors. All rights reserved.

关键词： Mobile robots