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arXiv 2023年

作者： Su, Yao Li, Jiarui Jiao, Ziyuan Wang, Meng Chu, Chi Li, Hang Zhu, Yixin Liu, Hangxin China Department of Advanced Manufacturing and Robotics College of Engineering Peking University China Department of Automation Tsinghua University China Institute for Artificial Intelligence Peking University China

We investigate the sequential manipulation planning problem for unmanned aerial manipulators (UAMs). Unlike prior UAM work that primarily focuses on one-step manipulation tasks, sequential manipulations require coordinated motions of the floating base, the manipulator, and the object being manipulated, entailing a unified kinematics and dynamics model for motion planning under designated constraints. By leveraging a VKC-based motion planning framework that consolidates components’ kinematics into one chain, the sequential manipulation task of a UAM can be planned as a whole with more coordinated motions. Integrating the kinematics and dynamics models with a hierarchical control framework, we demonstrate, for the first time, an over-actuated UAM achieves a series of new sequential manipulation capabilities in both simulation and experiment. © 2023, CC BY.

关键词： Manipulators

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A New Agile Actuation System of a Cable-Driven Parallel Robot

A New Agile Actuation System of a Cable-Driven Parallel Robo...

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

作者： S. Ali A. Moosavian MohammadJavad Shabani SeyedSina Seyedi HasanAbadi Mohammadreza Dahaaghin Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotic and Automated Systems (ARAS) K. N. Toosi University of Technology Tehran Iran

Cable-driven Parallel Robots (CDPRs) offer a wider range of workspace compared to rigid-link parallel robots. These robots are equipped with an actuation system that satisfies some requirements, such as having low inertia and a negligible amount of friction. These two criteria lead to the agility definition of a system. On the other hand, winch-drum actuation systems should be able to wind the cable properly, in a way it does not be wound on itself. In this paper, an innovative winch-drum actuation system with a universal joint module is designed and fabricated for a CDPR. The winch-drum module is equipped with a power screw module which allows the cable to be wound properly around the drum and the universal joint module allows the cable to accordingly orient within the workspace. To validate the proposed designated system, it is experimentally evaluated in two control scenarios; i.e. reaching a set point and path tracking task The results show that the proposed actuation system fulfills the desired criteria and has the potential to be implemented in any other CDPR.

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Bayesian Inverse Problems with Conditional Sinkhorn Generative Adversarial Networks in Least Volume Latent Spaces

SSRN

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SSRN 2024年

作者： Chen, Qiuyi Tsilifis, Panagiotis Fuge, Mark Department of Mechanical Engineering University of Maryland College ParkMD20742 United States Robotics AI & Computer Vision Group General Electric Vernova Advanced Research NiskayunaNY12309 United States

Solving inverse problems in scientific and engineering fields has long been intriguing and holds great potential for many applications, yet most techniques still struggle to address issues such as high dimensionality, nonlinearity and model uncertainty inherent in these problems. Recently, generative models such as Generative Adversarial Networks (GANs) have shown great potential in approximating complex high dimensional conditional distributions and have paved the way for characterizing posterior densities in Bayesian inverse problems, yet the problems’ high dimensionality and high nonlinearity often impedes the model’s training. In this paper we show how to tackle these issues with Least Volume—a novel unsupervised nonlinear dimension reduction method—that can learn to represent the given datasets with the minimum number of latent variables while estimating their intrinsic dimensions. Once the low dimensional latent spaces are identified, efficient and accurate training of conditional generative models becomes feasible, resulting in a latent conditional GAN framework for posterior inference. We demonstrate the power of the proposed methodology on a variety of applications including inversion of parameters in systems of ODEs and high dimensional hydraulic conductivities in subsurface flow problems, and reveal the impact of the observables’ and unobservables’ intrinsic dimensions on inverse problems. © 2024, The Authors. All rights reserved.

关键词： Inverse problems

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Preliminary study of online real-time control system for lower extremity exoskeletons based on EEG and sEMG fusion

Preliminary study of online real-time control system for low...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Li, Wenju Shao, Keyong Zhu, Chi Ma, Yue Cao, Wujing Yin, Meng Yang, Lijun Luo, Mingxiang Wu, Xinyu Northeast Petroleum University School of Electrical Engineering Information Daqing China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Guangdong Shenzhen518055 China Maebashi Institute of Technology Department of Systems Life Engineering Maebashi3710132 Japan

ISBN: (纸本)9781665481090

Motion imaging (MI) is widely used in exoskele-ton robot control direction. However, online real-time con-trol of exoskeletons based on biological signals is difficult to achieve. Because the anti-interference of biological signals in real life is poor and affected by individual differences, the control of auxiliary equipment by the realization of human-machine interface is still facing great challenges. In this paper, a human-machine interface (HMI) based on hybrid biological signals is designed and online real-time control of lower extremity exoskeletons is realized. Based on a comprehensive analysis of human walking, the HMI uses the electromyography signals (upper extremities) and EEG signals generated during real exercise as input signals. Different analysis methods are designed for different modal signals. We extracted four features of sEMG signals to distinguish between different movement processes in the human body. For EEG signals, the use of Independent Component Analysis (ICA) increases the robustness of the system. Event-related desynchronization/synchronization (ERS/ERD) and power spectral densities are reused for analysis from the perspective of the interaction of multiple information in the channel, time and frequency domains. The human-machine interface integrates EEG and EMG multimodal biological signals, and the average recognition accuracy of different subjects has reached 93.7%. In order to increase the recognition accuracy of practical applications and reduce the differences between different individuals, a window voting mechanism is designed. Healthy subjects were tested, and the recognition accuracy of the lower limb exoskeleton online real-time assistance system reached 99%, with high accuracy and reliability. © 2022 IEEE.

关键词： Real time control

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Live Demonstration: Soft Flexible Capacitive Sensing Arrays for Pressure, Shear, and Proximity

Live Demonstration: Soft Flexible Capacitive Sensing Arrays ...

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IEEE SENSORS

作者： Jian Gao Kieran Morton Ryusuke Ishizaki Fumiya Hamatsu Takeshi Ohsato John DW Madden Advanced Material Processing Engineering Laboratory University of British Columbia Vancouver Canada Frontier Robotics Honda R&D Co. Ltd Saitama Japan

Soft flexible capacitive sensors are demonstrated that can capture a combination of pressure, shear, and proximity information intended for medical, sports and robotics applications. They consist of three major components—silicone elastomer, conductive fabric, and flexible printed circuit boards (FPCB). Empowered by a custom readout circuit utilizing the Cypress PSoC 6 MCU, the systems consume 20 mW while scanning and transmitting measurement data via Bluetooth Low-Energy (BLE) 5.0. Pressure, shear, and proximity are visualized in a custom mobile application. Operation of our wearable and industrial sensors is shown.

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Design and Analysis of Knee Joint for Transfemoral Amputees

Design and Analysis of Knee Joint for Transfemoral Amputees

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2021 International Conference on Artificial Intelligence and Mechatronics Systems, AIMS 2021

作者： Qadir, Muhammad Usman Khan, Muhammad Awais Hussain, Muzammal Ul Haq, Izhar Akhtar, Nizar Shah, Kmaran Advanced Robotics Automation Lab University of Engineering Technology Dept. of Mechatronics Engineering Peshawar Pakistan University of Engineering Technology Dept. of Mechatronics Engineering Peshawar Pakistan International Committee of Red Cross Sanaa Yemen

ISBN: (纸本)9781665424820

Lower limb amputation not only reduces mobility but also results in significant impairment in quality of life. Microprocessor based transfemoral knee joints have gained significant importance in the last decade to not only restore cosmetics but also provide functionality comparable to real limb. One of the key issues in such devices is selection of the suitable material for manufacturing of knee joint to minimize chances of failure under various loading conditions, while at the same time ensuring the weight of the knee is within acceptable limits. The purpose of this research is to design a microprocessor-based knee joint and perform various static structural analysis for different materials to optimize strength to weight ratio of the proposed design. Initially, a model for the proposed microprocessor-based knee was developed in SolidWorks followed by displacement study and computation of von-mises stresses in Ansys Workbench. Different materials used in the analysis include Plain Carbon Steel, Stainless Steel 304, Aluminum 6061. Based on the results Aluminum 6061 was identified as a suitable material for manufacturing knee joint as it not only reduces weight of the knee joint but also the deformation and stress values are within acceptable limits. The minimum and maximum Von Mises stress of Aluminum 6061 was 559.9 Pa and 71.37 MPa respectively with tensile strength of 313 MPa. © 2021 IEEE.

关键词： Manufacture

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Intelligent Model-Free Control for Tendon-Driven Continuum Robotic Arms

Intelligent Model-Free Control for Tendon-Driven Continuum R...

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

作者： Nima Maghooli Omid Mahdizadeh S. Ali A. Moosavian Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotic and Automated Systems (ARAS) K. N. Toosi University of Technology Tehran Iran

Continuum manipulator modeling is always associated with structured and unstructured uncertainties. Therefore, model-based control system design for this class of robotic systems will be very challenging. On the other hand, the performance quality of model-free controllers is completely dependent on their hyperparameters; they are also very sensitive to the considered trajectory for the system. As a result, using model-free controllers will require setting parameters for different scenarios. In this research, the design of a model-free controller with comparable performance to model-based control strategies is presented. To this end, various parameters are determined online by the gain adjustment system. The research innovation is to use a supervised machine learning method, fuzzy inference system (FIS), to implement the intelligent gain adaptation system to achieve this goal. The Modified Transpose Jacobian (MTJ) performs well in trajectory tracking due to its approximated feedback linearization tool. In addition, the PID controller structure makes it a locally robust control strategy. An adaptive gain adjustment system can greatly increase algorithm potential and establish the capability to follow trajectories in different work points in the system work space. This research aims to improve the performance of the MTJ model-free control strategy in tracking trajectories starting from arbitrary initial conditions in the system work space. This is achieved by the gain adjustment system design using a fuzzy inference system. Both simulation and experimental results reveal the merits of the proposed controller.

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Design and Control of an Omnidirectional Aerial Robot with a Miniaturized Haptic Joystick for Physical Interaction

arXiv

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arXiv 2024年

作者： Mellet, Julien Berra, Andrea Marcellini, Salvatore Soto, Miguel Ángel Trujillo Heredia, Guillermo Ruggiero, Fabio Lippiello, Vincenzo PRISMA Lab Department of Electrical Engineering and Information Technology University of Naples Federico II Naples Italy CATEC Advanced Center for Aerospace Technologies Seville Spain GRVC Robotics Vision and Control Group School of Engineering University of Seville Seville Spain

Fully actuated aerial robot proved their superiority for Aerial Physical Interaction (APhI) over the past years. This work proposes a minimal setup for aerial telemanipulation, enhancing accessibility of these technologies. The design and the control of a 6-Degrees of Freedom (DoF) joystick with 4-DoF haptic feedback is detailed. It is the first haptic device with standard Remote Controller (RC) form factor for APhI. By miniaturizing haptic device, it enhances RC with the sense of touch, increasing physical awareness. The goal is to give operators an extra sense, other than vision and sound, to help to perform safe APhI. To the best of the authors knowledge, this is the first teleoperation system able to decouple each single axis input command. On the omnidirectional quadrotor, by reducing the number of components with a new design, we aim a simplified maintenance, and improved force and thrust to weight ratio. Open-sourced physic based simulation and successful preliminary flight tests highlighted the tool as promising for future APhI applications. © 2024, CC BY-NC-ND.

关键词： Omnidirectional antennas

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Assisted Physical Interaction: Autonomous Aerial Robots with Neural Network Detection, Navigation, and Safety Layers

Assisted Physical Interaction: Autonomous Aerial Robots with...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Andrea Berra Viswa Narayanan Sankaranarayanan Achilleas Santi Seisa Julien Mellet Udayanga G.W.K.N. Gamage Sumeet Gajanan Satpute Fabio Ruggiero Vincenzo Lippiello Silvia Tolu Matteo Fumagalli George Nikolakopoulos Miguel Ángel Trujillo Soto Guillermo Heredia CATEC Advanced Center for Aerospace Technologies Seville Spain Department of Computer Electrical and Space Engineering Robotics and AI Team Luleå University of Technology Luleå Sweden Department of Electrical Engineering and Information Technology PRISMA Lab University of Naples Federico II Naples Italy Department of Electrical Engineering and Photonics Automation and Control Group Technical University of Denmark Denmark Robotics Vision and Control Group School of Engineering University of Seville Seville Spain

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

The paper introduces a novel framework for safe and autonomous aerial physical interaction in industrial settings. It comprises two main components: a neural network-based target detection system enhanced with edge computing for reduced onboard computational load, and a control barrier function (CBF)-based controller for safe and precise maneuvering. The target detection system is trained on a dataset under challenging visual conditions and evaluated for accuracy across various unseen data with changing lighting conditions. Depth features are utilized for target pose estimation, with the entire detection framework offloaded into low-latency edge computing. The CBF-based controller enables the UAV to converge safely to the target for precise contact. Simulated evaluations of both the controller and target detection are presented, alongside an analysis of real-world detection performance.

关键词： Visualization Pose estimation Neural networks Lighting Object detection Autonomous aerial vehicles Aircraft navigation

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Flow Sensing-Based Underwater Target Detection Using Distributed Mobile Sensors

Flow Sensing-Based Underwater Target Detection Using Distrib...

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IEEE Conference on Decision and Control

作者： Jun Wang Tongsheng Shen Dexin Zhao Feitian Zhang Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing China National Innovation Institute of Defense Technology Beijing China Department of Advanced Manufacturing and Robotics and the State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University Beijing China

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper presents a novel bioinspired underwater target detection method with distributed mobile sensors. Inspired by the fish's lateral line system, distributed mobile sensors are proposed to measure their respective local flow pressure and collectively estimate the parameters (e.g., position and dimension) of underwater targets with dynamic sensor trajectory planning. This paper formulates an optimal trajectory planning problem for a group of mobile sensors using information entropy as the cost function, with an aim to maximize the confidence level in the estimated target parameters. This paper in particular investigates the detection of a circular target in a uniform flow. A Bayesian filter is adopted to assimilate the distributed pressure measurements dynamically to estimate the position and radius of given circular targets. To verify the effectiveness of the proposed method, simulation is conducted with both fixed and moving circular targets in uniform flow. Simulation results are presented and analyzed.

关键词： Trajectory planning Simulation Object detection Robot sensing systems Sensor systems Entropy Sensors

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