检索结果-内蒙古大学图书馆

Preferenced Oracle Guided Multi-mode Policies for dynamic Bipedal Loco-Manipulation

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Ravichandar, Prashanth Krishna, Lokesh Sobanbabu, Nikhil Nguyen, Quan Dynamic Robotics and Control Laboratory University of Southern California Los AngelesCA90089 United States

dynamic loco-manipulation calls for effective whole-body control and contact-rich interactions with the object and the environment. Existing learning-based control synthesis relies on training low-level skill policies and explicitly switching with a high-level policy or a hand-designed finite state machine, leading to quasi-static behaviors. In contrast, dynamic tasks such as soccer require the robot to run towards the ball, decelerate to an optimal approach to dribble, and eventually kick a goal—a continuum of smooth motion. To this end, we propose Preferenced Oracle Guided Multi-mode Policies (OGMP) to learn a single policy mastering all the required modes and preferred sequence of transitions to solve uni-object loco-manipulation tasks. We design hybrid automatons as oracles to generate references with continuous dynamics and discrete mode jumps to perform a guided policy optimization through bounded exploration. To enforce learning a desired sequence of mode transitions, we present a task-agnostic preference reward that enhances performance. The proposed approach demonstrates successful loco-manipulation for tasks like soccer and moving boxes omnidirectionally through whole-body control. In soccer, a single policy learns to optimally reach the ball, transition to contact-rich dribbling, and execute successful goal kicks and ball stops. Leveraging the oracle’s abstraction, we solve each loco-manipulation task on robots with varying morphologies, including HECTOR V1, Berkeley Humanoid, Unitree G1, and H1, using the same reward definition and weights. © 2024, CC BY.

关键词：

Feedback-feedforward Signal control with Exogenous Demand Estimation in Congested Urban Road Networks

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Pedroso, Leonardo Batista, Pedro Papageorgiou, Markos Control Systems Technology section Eindhoven University of Technology Netherlands Institute for Systems and Robotics Instituto Superior Técnico Universidade de Lisboa Portugal Dynamic Systems and Simulation Laboratory Technical University of Crete Chania Greece Faculty of Maritime and Transportation Ningbo University Ningbo China

To cope with uncertain traffic patterns and traffic models, traffic-responsive signal control strategies in the literature are designed to be robust to these uncertainties. These robust strategies still require sensing infrastructure to implement traffic-responsiveness. In this paper, we take a novel perspective and show that it is possible to use the already necessary sensing infrastructure to estimate the uncertain quantities in real time. Specifically, resorting to the store-and-forward model, we design a novel network-wide traffic-responsive strategy that estimates the occupancy and exogenous demand in each link, i.e., entering (exiting) vehicle flows at the origins (destinations) of the network or within links, in real time. Borrowing from optimal control theory, we design an optimal linear quadratic control scheme, consisting of a linear feedback term, of the occupancy of the road links, and a feedforward component, which accounts for the varying exogenous vehicle load on the network. Thereby, the resulting control scheme is a simple feedback-feedforward controller, which is fed with occupancy and exogenous demand estimates, and is suitable for real-time implementation. Numerical simulations for the urban traffic network of Chania, Greece, show that, for realistic surges in the exogenous demand, the proposed solution significantly outperforms tried-and-tested solutions that ignore the exogenous demand. © 2023, CC BY-NC-ND.

关键词： Traffic signals

Optical Tactile Sensing for Aerial Multi-Contact Interaction: Design, Integration, and Evaluation

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Aucone, Emanuele Sferrazza, Carmelo Gregor, Manuel D'Andrea, Raffaello Mintchev, Stefano The Environmental Robotics Laboratory Dept. of Environmental Systems Science ETH Zürich Zürich8092 Switzerland Birmensdorf8903 Switzerland The Robot Learning Lab UC Berkeley BerkeleyCA94704 United States The Institute for Dynamic Systems and Control Dept. of Mechanical and Process Engineering ETH Zürich Zürich8092 Switzerland

Distributed tactile sensing for multi-force detection is crucial for various aerial robot interaction tasks. However, current contact sensing solutions on drones only exploit single end-effector sensors and cannot provide distributed multi-contact sensing. Designed to be easily mounted at the bottom of a drone, we propose an optical tactile sensor that features a large and curved soft sensing surface, a hollow structure and a new illumination system. Even when spaced only 2 cm apart, multiple contacts can be detected simultaneously using our software pipeline, which provides real-world quantities of 3D contact locations (mm) and 3D force vectors (N), with an accuracy of 1.5 mm and 0.17 N respectively. We demonstrate the sensor’s applicability and reliability onboard and in real-time with two demos related to i) the estimation of the compliance of different perches and subsequent re-alignment and landing on the stiffer one, and ii) the mapping of sparse obstacles. The implementation of our distributed tactile sensor represents a significant step towards attaining the full potential of drones as versatile robots capable of interacting with and navigating within complex environments. Copyright © 2024, The Authors. All rights reserved.

关键词： Drones

A Structured Prediction Approach for Robot Imitation Learning

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Duan, Anqing Batzianoulis, Iason Camoriano, Raffaello Rosasco, Lorenzo Pucci, Daniele Billard, Aude Robotics and Machine Intelligence Laboratory The Hong Kong Polytechnic University Hong Kong Learning Algorithms and Systems Laboratory École Polytechnique Fédérale de Lausanne Lausanne Switzerland Visual And Multimodal Applied Learning Laboratory Politecnico di Torino Turin Italy DIBRIS Università degli Studi di Genova Genoa Italy Laboratory for Computational and Statistical Learning IIT@MIT Istituto Italiano di Tecnologia Massachusetts Institute of Technology CambridgeMA United States Center Università di Genova Genoa Italy Dynamic Interaction Control research line Italian Institute of Technology Genoa Italy

We propose a structured prediction approach for robot imitation learning from demonstrations. Among various tools for robot imitation learning, supervised learning has been observed to have a prominent role. Structured prediction is a form of supervised learning that enables learning models to operate on output spaces with complex structures. Through the lens of structured prediction, we show how robots can learn to imitate trajectories belonging to not only Euclidean spaces but also Riemannian manifolds. Exploiting ideas from information theory, we propose a class of loss functions based on the f-divergence to measure the information loss between the demonstrated and reproduced probabilistic trajectories. Different types of f-divergence will result in different policies, which we call imitation modes. Furthermore, our approach enables the incorporation of spatial and temporal trajectory modulation, which is necessary for robots to be adaptive to the change in working conditions. We benchmark our algorithm against state-of-the-art methods in terms of trajectory reproduction and adaptation. The quantitative evaluation shows that our approach outperforms other algorithms regarding both accuracy and efficiency. We also report real-world experimental results on learning manifold trajectories in a polishing task with a KUKA LWR robot arm, illustrating the effectiveness of our algorithmic framework. Copyright © 2023, The Authors. All rights reserved.

关键词： Trajectories

Multibody simulation for tracking error reduction in solar tracking robots

学校读者我要写书评

暂无评论

AIP Conference Proceedings 2023年第1期2872卷

作者： Aldo Hernández-Díaz Diego A. Flores-Hernández Alberto Luviano-Juárez Sergio Isai Palomino-Resendiz Itzamá López-Yáñez National Polytechnic Institute - UPIITA Applied Dynamic Systems Laboratoy Mexico City 07340 Mexico National Polytechnic Institute - UPIITA Advanced Robotics Laboratory Mexico City 07340 Mexico National Polytechnic Institute - ESIME-ZAC Department of Control and Automation Mexico City 07738 Mexico National Polytechnic Institute - CIDETEC Mexico City 07738 Mexico

Currently, the use of renewable energy sources such as solar energy, collected by photovoltaic technology, has gained ground in the energy sector. Its use has been popularised due to the fact that it is considered a clean energy, that is a type of energy is produced without burning fossil fuels which are a cause of global warming, among other environmental damages. In order to optimize the energy harvesting through photovoltaic technology, it is necessary to maintain a perpendicular incidence of the sun rays with the photovoltaic module, leading to the use of solar tracking systems that demand the application of trajectory tracking control strategies that minimize the tracking errors while ensuring the lowest energy consumption of the robotic system. In this work, a comprehensive multibody simulation was carried out to obtain a concrete appreciation of the behavior of the tracking system prior to an experimental implementation. This type of simulations allows us to simulate complete systems formed by solid links and rigid joints that were previously designed, and with a calculated analytical model (Kinematic and dynamic). Furthermore, the obtained simulator allows us to apply a variety of control strategies that are represented by means of 3D simulations which are very similar to the actual experimental results, so that it would be possible to estimate the ªtracking error results° without the necessity of a physical implementation. From the kinematic and dynamic models of a solar tracker of two degrees of freedom, released in an azimuthal-elevation configuration, a PID controller and a passivity-based controller were implemented in Matlab-Simscape®, obtaining simulations of a solar trajectory tracking minimizing the error between the reference and the solar tracker.

关键词：

Comparative analysis of control strategies for the reduction of tracking error in CPV systems

学校读者我要写书评

暂无评论

AIP Conference Proceedings 2023年第1期2841卷

作者： Sergio I. Palomino-Resendiz Víctor Cadix-Martín Basil Mohammed Al-Hadithi Diego A. Flores-Hernández Instituto Politécnico Nacional – ESIME-ZAC Departamento de Control y Automatización Mexico City 07738 Mexico Escuela Técnica Superior de Ingeniería y Diseño Industrial Departamento de Ingeniería Eléctrica Automática y Física Aplicada Universidad Politécnica de Madrid Madrid 28012 Spain Intelligent Control Group Universidad Politécnica de Madrid Centre for Automation and Robotics UPM-CSIC Madrid 28006 Spain Instituto Politécnico Nacional – UPIITA Applied Dynamic Systems Laboratory Mexico City 07340 Mexico

In this work, an experimental methodology is shown that allows selecting the best controller alternative to govern a two-axis solar tracking system in trajectory tracking tasks. This, based on the comparison of the performance of different controllers during the tracking of a solar trajectory (obtained offline with the help of a numerical method) using a prototype solar tracking system in a simulation environment. The selection of the controllers is based on the performance reported in the literature and commercially for other alternatives based on parameters such as: tracking error and energy consumption, computational cost, ease of implementation, ease of tuning, among others. However, for the final validation and selection of the controller, a brief analysis of the numerical results obtained during the follow-up tests is provided.

关键词：

Learning to Sequence Multiple Tasks with Competing Constraints

学校读者我要写书评

暂无评论

Learning to Sequence Multiple Tasks with Competing Constrain...

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Anqing Duan Raffaello Camoriano Diego Ferigo Yanlong Huang Daniele Calandriello Lorenzo Rosasco Daniele Pucci Dynamic Interaction Control Lab Istituto Italiano di Tecnologia Via San Quirico 19D Genoa Italy Laboratory for Computational and Statistical Learning (IIT@MIT) Istituto Italiano di Tecnologia and Massachusetts Institute of Technology Cambridge MA USA Department of Advanced Robotics Istituto Italiano di Tecnologia Via Morego 30 Genova Italy DIBRIS Università degli Studi di Genova Genoa Italy

Imitation learning offers a general framework where robots can efficiently acquire novel motor skills from demonstrations of a human teacher. While many promising achievements have been shown, the majority of them are only focused on single-stroke movements, without taking into account the problem of multi-tasks sequencing. Conceivably, sequencing different atomic tasks can further augment the robot's capabilities as well as avoid repetitive demonstrations. In this paper, we propose to address the issue of multi-tasks sequencing with emphasis on handling the so-called competing constraints, which emerge due to the existence of the concurrent constraints from Cartesian and joint trajectories. Specifically, we explore the null space of the robot from an information-theoretic perspective in order to maintain imitation fidelity during transition between consecutive tasks. The effectiveness of the proposed method is validated through simulated and real experiments on the iCub humanoid robot.

关键词：

Design and modeling of a compact rotational nonlinear spring

学校读者我要写书评

暂无评论

Design and modeling of a compact rotational nonlinear spring

IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Hamed Jalaly Bidgoly Majid Nili Ahmadabadi Mohammad Reza Zakerzadeh Cognitive Robotics Laboratory The Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering College of Engineering University of Tehran Iran Dynamic and Vibration Laboratory School of Mechanical Engineering College of Engineering University of Tehran Iran

ISBN: (纸本)9781509037636

In this paper, we propose a new method for implementing a rotational nonlinear spring with user defined profile, based on the combination of a linear spring with a nonlinear transmission mechanism. The proposed structure consists of a non-circular cam, a roller which moves along outer circumference of the cam, and a stretched translational linear spring which is connected between center of the cam and center of the roller. We obtain a set of differential equations to design shape of the cam for any given torque-angle profile. Also, it will be shown that profiles with both positive and negative values can be implemented by the proposed method. At last, the cam of some popular nonlinear springs are designed, including constant, cubic, hyperbolic tangent and sinusoidal springs.

关键词： Computer aided manufacturing Camelopardalis Hookean spring springs Device Spring TRANSFER MECHANISM Modeling nonlinearity Rotational SCROLL Differential equations Spring season

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

学校读者我要写书评

暂无评论

BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ