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International Conference on control, Automation, robotics and Vision (ICARCV)

作者： Francesco D'Orazio Tommaso Belvedere Spyridon G. Tarantos Giuseppe Oriolo Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy CNRS Université de Rennes Inria IRISA Rennes France Center of AI & Robotics (CAIR) and Engineering Division New York University Abu Dhabi Abu Dhabi United Arab Emirates

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

This paper presents a novel method to maintain the dynamic balance of a Mobile Manipulator (MM) during the pick-up of heavy objects. The approach entails the generation of a preliminary reach-to-grasp trajectory, which is subsequently refined by an Optimization-Based controller (OBC) formulated as a Quadratic Program (QP). The trajectory is modified in a minimal fashion to ensure that the robot maintains balance during the reaching phase and remains balanced when the payload is grasped. This is accomplished by incorporating a balance constraint into the OBC that predicts the Zero Moment Point (ZMP) position of the robot at the beginning of the pick-up phase. This accounts for the gravitational and inertial effects that the object has on the robot. The method is validated through simulations conducted with the TIAGo robot in Gazebo. The results demonstrate that the proposed approach effectively prevents the robot from tipping over when the payload is considered.

关键词： Simulation Wheels Stability analysis Robustness Trajectory Safety Mobile robots Robots Manipulator dynamics Payloads

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control Contraction Metrics on Lie Groups

arXiv

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arXiv 2024年

作者： Wu, Dongjun Yi, Bowen Manchester, Ian R. Department of Automatic Control Lund University Box 118 LundSE-221 00 Sweden Department of Electrical Engineering Polytechnique MontrealQCH3T 1J4 Canada Australian Centre for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Australia

In this paper, we extend the control contraction metrics (CCM) approach, which was originally proposed for the universal tracking control of nonlinear systems, to those that evolves on Lie groups. Our idea is to view the manifold as a constrained set that is embedded in Euclidean space, and then propose the sufficient conditions for the existence of a CCM and the associated controller design. Notably, we demonstrate that the search for CCM on Lie groups can be reformulated as convex conditions. The results extend the applicability of the CCM approach and provide a framework for analyzing the behavior of control systems with Lie group structures. © 2024, CC BY.

关键词： Nonlinear systems

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Riding the Rollercoaster: Improving UAV Piloting Skills with Augmented Visualization and Collaborative Planning

Riding the Rollercoaster: Improving UAV Piloting Skills with...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Riccardo Franceschini Javier Rodriguez Marquez Matteo Fumagalli Julian Cayero Becerra Eurecat Centre Tecnològic de Catalunya Robotics and Automation Unit Cerdanyola del Vallès Barcelona Spain Department of Electrical Engineering Automation and Control group Danish Technical University Elektrovej Kgs. Lyngby Denmark

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

Operating unmanned aerial vehicles (UAVs) in complex environments can be challenging, particularly for inexperienced operators. This paper introduces a method aimed at enhancing the piloting experience by incorporating an intermediary processing layer between the remote controller and the drone. The presented approach empowers operators to control both the speed and direction of the UAV along a secure path, which is continuously computed and overlaid onto the operator's camera stream. The UAV autonomously plans and executes this path, adapting to the operator's commands and en-vironmental changes. The primary aim of this proposed solution is to enhance the operator's situational awareness, perception, as well as the safety and efficiency of UAV navigation. The paper outlines the system and methodology employed, showing its ability to operate at a high enough frequency to enable seamless user interactions. Furthermore, to validate the effectiveness of this approach, a real-world test and a user-based experimental study conducted in a simulation environment with an audience comprising varying levels of pilot expertise have been carried out.

关键词： Human-robot interaction Process control Collaboration Autonomous aerial vehicles Safety Planning Haptic interfaces

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DeepBHMR: Learning Bidirectional Hybrid Mixture Models for Generalized Rigid Point Set Registration

DeepBHMR: Learning Bidirectional Hybrid Mixture Models for G...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Zhe Min Zhengyan Zhang Ang Zhang Rui Song Yibin Li Max Q.-H. Meng School of Control Science and Engineering Shandong University China Wellcome/EPSRC Centre for Surgical and Interventional Sciences University College London UK Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Yuanhua Robotics Perception and AI Technologies Ltd Shenzhen China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, we introduce a novel normal-assisted learning-based rigid registration approach, i.e., Deep Bi-directional Hybrid Mixture Registration (DeepBHMR). Our approach utilises helpful normal vectors explicitly in both correspondence and transformation stages and formulates the optimization objective of registration in a bi-directional way that considers noise in both point sets. DeepBHMR consists of three modules: (1) the correspondence network that estimates the correspondence probability relating points within one generalized point set (i.e., positional and normal vectors) with components of Hybrid Mixture Models (HMMs) representing the other generalized point set; (2) the posterior module that computes HMMs parameters; (3) the transformation module that computes the rotation matrix and the translation vector given the estimated generalized-point to hybrid-distribution correspondences and HMMs parameters. DeepBHMR has been validated on 291 human femur and 260 hip models, and extensive experimental results demonstrate that DeepBHMR outperforms the state-of-the-art registration methods (p-value < 0.01). In the circumstance of femur bones, the mean rotation and translation error values are around 1° (i.e., 1.01°) and less than 1 mm (i.e., 0.36mm), respectively. Furthermore, even under the large transformation (i.e., in the range of [0,180]° and [0, 100] mm), the mean RMSE values being 3.05 mm is still satisfactory. Additionally, the results demonstrate the DeepBHMR’s favorable generalizability from femur shapes to hip shapes. We have carefully validated the significant benefits of incorporating normal vectors and the bidirectional mechanism. DeepBHMR can successfully handle the challenging scenario of large transformation and partial registration. The codes are available at https://***/zzyrobot/***.

关键词： Translation Accuracy Shape Hidden Markov models Mixture models Bidirectional control Bones Vectors Optimization Hip

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MATERobot: Material Recognition in Wearable robotics for People with Visual Impairments

arXiv

引用

arXiv 2023年

作者： Zheng, Junwei Zhang, Jiaming Yang, Kailun Peng, Kunyu Stiefelhagen, Rainer The Institute for Robotics and Anthropomatics Karlsruhe Institute of Technology Karlsruhe76131 Germany The Department of Engineering Science University of Oxford OxfordOX1 3PJ United Kingdom The School of Robotics The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China

People with Visual Impairments (PVI) typically recognize objects through haptic perception. Knowing objects and materials before touching is desired by the target users but under-explored in the field of human-centered robotics. To fill this gap, in this work, a wearable vision-based robotic system, MATERobot, is established for PVI to recognize materials and object categories beforehand. To address the computational constraints of mobile platforms, we propose a lightweight yet accurate model MATEViT to perform pixel-wise semantic segmentation, simultaneously recognizing both objects and materials. Our methods achieve respective 40.2% and 51.1% of mIoU on COCOStuff-10K and DMS datasets, surpassing the previous method with +5.7% and +7.0% gains. Moreover, on the field test with participants, our wearable system reaches a score of 28 in the NASA-Task Load Index, indicating low cognitive demands and ease of use. Our MATERobot demonstrates the feasibility of recognizing material property through visual cues and offers a promising step towards improving the functionality of wearable robots for PVI. The source code has been made publicly available at MATERobot. Copyright © 2023, The Authors. All rights reserved.

关键词： NASA

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The impact of optical turbulence created by Rayleigh Benard convection on vortex structure in beams carrying orbital angular momentum

The impact of optical turbulence created by Rayleigh Benard ...

引用

Propagation Through and Characterization of Atmospheric and Oceanic Phenomena, pcAOP 2022

作者： Avramov-Zamurovic, Svetlana Judd, K.P. Matt, S. Handler, R.A. Watnik, A.T. Weapons Robotics and Control Engineering Department United States Naval Academy MD United States Naval Research Laboratory WashingtonDC United States Naval Research Laboratory Stennis Space Center MS United States George Mason University FairfaxVA United States

We simulate Rayleigh Benard natural convection in air and propagate Gaussian Laguerre beams with varying topological charge through it. We present the impact of the optical turbulence on the phase and intensity of the... 详细信息

ISBN: (纸本)9781557528209

关键词： Natural convection

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Effect of Electromagnetic Microwaves on Migration of Undesirable Compounds into Food

SSRN

引用

SSRN 2025年

作者： Bronczyk, Karolina Dąbrowska, Agata Dąbrowski, Adam Konieczka, Adam Department of Trace Analysis Faculty of Chemistry Adam Mickiewicz University Uniwersytetu Poznanskiego 8 Poznan61-614 Poland Faculty of Automatic Control Robotics and Electrical Engineering Poznan University of Technology Piotrowo 3A Poznan60-965 Poland

Food contact materials (FCMs) may be responsible for migration of contaminants into food, especially during heating. This article describes the effect of electromagnetic microwaves used to heat food on the migration of organic contaminants into neutral, and acidic food. An untargeted analysis (GC-MS) was performed to determine groups of organic compounds, which can be released most quickly from FCMs into heated food. Low-molecular-weight carbonyl compounds are particularly important migrants, as they can affect the quality and sensory properties of foods. It makes them suitable for use as markers in migration studies. A targeted analysis was performed to determine the factors determining the intensity of migration processes. The derivatization method using the reagent 2,3,4,5,6-pentafluorobenzylhydroxylamine (PFBOA) was used, which allows the use of gas chromatography coupled with an electron capture detector (GC-ECD). The study showed that plant-based FCMs lead to greater contamination of food with undesirable carbonyls than glass and plastics. Short-term storage of food in a refrigerator promotes the migration of carbonyls to food. Longer storage reduces the total concentration of carbonyls in neutral food. However, aldehydes and ketones are more biologically stable in acidic food. Additionally, plant-based FCMs can affect the sensory profile of food heated briefly with the microwave radiation. © 2025, The Authors. All rights reserved.

关键词： Acetone

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A Miniaturised Camera-based Multi-Modal Tactile Sensor

A Miniaturised Camera-based Multi-Modal Tactile Sensor

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Kaspar Althoefer Yonggen Ling Wanlin Li Xinyuan Qian Wang Wei Lee Peng Qi The Centre for Advanced Robotics @ Queen Mary (ARQ) Queen Mary University of London London United Kingdom Tencent Robotics X Lab Shenzhen China Beijing Institute for General Artificial Intelligence (BIGAI) Beijing China The Department of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai China

In conjunction with huge recent progress in cam-era and computer vision technology, camera-based sensors have increasingly shown considerable promise in relation to tactile sensing. In comparison to competing technologies (be they resistive, capacitive or magnetic based), they offer super-high-resolution, while suffering from fewer wiring problems. The human tactile system is composed of various types of mechanoreceptors, each able to perceive and process distinct information such as force, pressure, texture, etc. Camera-based tactile sensors such as GelSight mainly focus on high-resolution geometric sensing on a flat surface, and their force measurement capabilities are limited by the hysteresis and non-linearity of the silicone material. In this paper, we present a miniaturised dome-shaped camera-based tactile sensor that allows accurate force and tactile sensing in a single coherent system. The key novelty of the sensor design is as follows. First, we demonstrate how to build a smooth silicone hemispheric sensing medium with uniform markers on its curved surface. Second, we enhance the illumination of the rounded silicone with diffused LEDs. Third, we construct a force-sensitive mechanical structure in a compact form factor with usage of springs to accurately perceive forces. Our multi-modal sensor is able to acquire tactile information from multi-axis forces, local force distribution, and contact geometry, all in real-time. We apply an end-to-end deep learning method to process all the information.

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Nonlinear MPC for Full-Pose Manipulation of a Cable-Suspended Load using Multiple UAVs

Nonlinear MPC for Full-Pose Manipulation of a Cable-Suspende...

引用

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Sihao Sun Antonio Franchi Robotics and Mechatronics Department Electrical Engineering Mathematics and Computer Science (EEMCS) Faculty University of Twente AE Enschede The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy LAAS-CNRS Université de Toulouse Toulouse France

In this work, we propose a centralized control method based on nonlinear model predictive control to let multiple UAVs manipulate the full pose of an object via cables. At the best of the authors knowledge this is the first method that takes into account the full nonlinear model of the load-UAV system, and ensures all the feasibility constraints concerning the UAV maximumum and minimum thrusts, the collision avoidance between the UAVs, cables and load, and the tautness and maximum tension of the cables. By taking into account the above factors, the proposed control algorithm can fully exploit the performance of UAVs and facilitate the speed of operation. Simulations are conducted to validate the algorithm to achieve fast and safe manipulation of the pose of a rigid-body payload using multiple UAVs. We demonstrate that the computational time of the proposed method is sufficiently small (<100 ms) for UAV teams composed by up to 10 units, which makes it suitable for a huge variety of future industrial applications, such as autonomous building construction and heavy-load transportation.

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controllable Mechanical-domain Energy Accumulators

arXiv

引用

arXiv 2022年

作者： Kim, Sung Y. Braun, David J. The Advanced Robotics and Control Laboratory within the Center for Rehabilitation Engineering and Assistive Technology Department of Mechanical Engineering Vanderbilt University NashvilleTN37235 United States

Springs are efficient in storing and returning elastic potential energy but are unable to hold the energy they store in the absence of an external load. Lockable springs use clutches to hold elastic potential energy in the absence of an external load, but have not yet been widely adopted in applications, partly because clutches introduce design complexity, reduce energy efficiency, and typically do not afford high fidelity control over the energy stored by the spring. Here, we present the design of a novel lockable compression spring that uses a small capstan clutch to passively lock a mechanical spring. The capstan clutch can lock over 1000 N force at any arbitrary deflection, unlock the spring in less than 10 ms with a control force less than 1% of the maximal spring force, and provide an 80% energy storage and return efficiency (comparable to a highly efficient electric motor operated at constant nominal speed). By retaining the form factor of a regular spring while providing high-fidelity locking capability even under large spring forces, the proposed design could facilitate the development of energy-efficient spring-based actuators and robots. © 2022, CC BY-NC-ND.

关键词： Potential energy

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