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检索条件"机构=Robotics Engineering Program"

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Design and analysis of a new hybrid rotary steerable system for directional drilling

Design and analysis of a new hybrid rotary steerable system ...

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2013 44th IEEE International Symposium on robotics, ISR 2013

作者： Park, Jieun Kim, Jongheon Park, Byeolteo Myung, Hyun Division of Mechanical Engineering KAIST Korea Republic of Dept. Civil and Environmental Engineering KAIST Korea Republic of Dept. Civil and Environmental Engineering Robotics Program KAIST Korea Republic of

ISBN: (纸本)9781479911738

Recently, shale gas has become an important energy source. Directional drilling is an imperative technology when it comes to excavating shale gas because it exists in underground in horizontally spaced areas. A rotary steerable system (RSS) enables the effective directional drilling. In general, there are two types of RSS, the point-the-bit and the push-the-bit. In this paper, a new hybrid type RSS is proposed. The hybrid type RSS has advantages of both the point-the-bit and the push-the-bit. We expect that the proposed RSS can increase the build-rate. The effectiveness of the proposed mechanism is discussed by predicting the side force. © 2013 IEEE.

关键词： Directional drilling

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Exploring Classification, Size, and Quality of Mangifera Indica L. Through Image Processing and AI Techniques 2

Exploring Classification, Size, and Quality of Mangifera Ind...

引用

2nd International Conference on Mechanics, Electronics, Automation and Automatic Control, MEAAC 2024

作者： Wanthong, Irin Sri-On, Theeraphat Seangsri, Soontaree Khaengkarn, Sorada Srisertpol, Jiraphon Mechatronics Engineering Program School of Mechanical Engineering Suranaree University of Technology Nakhon Ratchasima Thailand Department of Mechatronics and Robotics Engineering School of Engineering and Innovation Rajamangala University of Technology Tawan-ok Chonburi Thailand

ISBN: (纸本)9781643685403

This paper introduces methods for efficiently classifying mangoes intended for export, a market valued at approximately 4,500 million baht annually. The classification process is divided into two primary components: size categorization and quality assessment. The first phase involves categorizing mango sizes into four distinct categories (M, 1L, 2L, 3L), while the second phase focuses on assessing mango quality, particularly detecting anthracnoseâ€"a prevalent disease affecting mangoes. This detection is achieved through image processing techniques, where images are converted into binary representations and analyzed using both Artificial Neural Networks (ANNs) and Convolutional Neural Networks (CNNs). Comparative analysis reveals that CNN outperforms ANN in size classification, achieving a remarkable train accuracy of 99.16% and a test accuracy of 88.0%. Furthermore, in quality classification, CNN demonstrates a train accuracy of 91.0% and a test accuracy of 88.0%. These findings underscore the effectiveness of CNN techniques in accurately classifying mangoes for export, thereby facilitating improved quality control and market competitiveness. Â© 2024 The Authors.

关键词： Convolutional neural networks

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Stability Guaranteed Actor-Critic Learning for Robots in Continuous Time 20

Stability Guaranteed Actor-Critic Learning for Robots in Con...

引用

20th International Conference on Electrical engineering, Computing Science and Automatic Control, CCE 2023

作者： Pantoja-Garcia, Luis Parra-Vega, Vicente Garcia-Rodriguez, Rodolfo Robotics and Adv. Manufacturing CINVESTAV Saltillo Mexico Universidad Politecnica Metropolitana de Hidalgo Postgraduate Program in Aerospacial Engineering Tolcayuca Mexico

ISBN: (纸本)9798350306767

Actor-Critic (AC) architecture has the salient feature, for the plethora of Reinforcement Learning schemes, that two intertwining neural networks (NN) collaborate to deploy a motor learning mechanism that oversees and evaluates the action to control a dynamical system as the robot manipulator. Since such NNs can be studied as dynamical systems to learn how to control the robot dynamics with a given performance, it has finally paved the way to deal with stability analysis, unfortunately, few works have addressed it. In this paper, we propose a Critic-NN whose approximation of the value function substantiates the decision making mechanism that collaborates to tune the Actor-NN action (approximation of inverse dynamics). The novel proposed design of the adaptation of the neural weights yields Lyapunov stability that provides explicit conditions for an attractive invariant set that render a stable regime using a quite simple NN with one hidden layer. Numerical simulations show the performance of the proposed approach. In addition, robustness is analyzed when the robot is subject to Liptchitz disturbances, interestingly showing relaunching of the learning mechanism when needed. Finally, a discussion on dealing with asymptotic stability, robustness issues, and the learning mechanism from a reward provided by the expert user is addressed. © 2023 IEEE.

关键词： Asymptotic stability

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ED-NERF: EFFICIENT TEXT-GUIDED EDITING OF 3D SCENE WITH LATENT SPACE NERF 12

ED-NERF: EFFICIENT TEXT-GUIDED EDITING OF 3D SCENE WITH LATE...

引用

12th International Conference on Learning Representations, ICLR 2024

作者： Park, Jangho Kwon, Gihyun Ye, Jong Chul Kim Jaechul Graduate School of AI Korea Republic of Robotics Program Korea Republic of Department of Bio and Brain Engineering KAIST Korea Republic of

Recently, there has been a significant advancement in text-to-image diffusion models, leading to groundbreaking performance in 2D image generation. These advancements have been extended to 3D models, enabling the generation of novel 3D objects from textual descriptions. This has evolved into NeRF editing methods, which allow the manipulation of existing 3D objects through textual conditioning. However, existing NeRF editing techniques have faced limitations in their performance due to slow training speeds and the use of loss functions that do not adequately consider editing. To address this, here we present a novel 3D NeRF editing approach dubbed ED-NeRF by successfully embedding real-world scenes into the latent space of the latent diffusion model (LDM) through a unique refinement layer. This approach enables us to obtain a NeRF backbone that is not only faster but also more amenable to editing compared to traditional image space NeRF editing. Furthermore, we propose an improved loss function tailored for editing by migrating the delta denoising score (DDS) distillation loss, originally used in 2D image editing to the three-dimensional domain. This novel loss function surpasses the well-known score distillation sampling (SDS) loss in terms of suitability for editing purposes. Our experimental results demonstrate that ED-NeRF achieves faster editing speed while producing improved output quality compared to state-of-the-art 3D editing models. Code and rendering results are available at our project page. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Distillation

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CWave: High-performance single-source any-angle path planning on a grid

CWave: High-performance single-source any-angle path plannin...

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2017 IEEE International Conference on robotics and Automation, ICRA 2017

作者： Sinyukov, Dmitry A. Padir, Taskin Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA01609 United States Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States

ISBN: (纸本)9781509046331

Path planning on a 2D-grid is a well-studied problem in robotics. It usually involves searching for a shortest path between two vertices on a grid. Single-source path planning is a modified problem which asks to find distances from a given point to all other points on the map. A high-performance algorithm for single-source any-angle path planning on a grid that we named CWave is proposed in this work. 'Any-angle' attribute of a path planning algorithm implies that such algorithm can find paths which may include any angle segments, as opposed to standard A © 2017 IEEE.

关键词： Motion planning

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Damping Injection Learning for Robots with Actor-Critic Driven by Integral Sliding Manifolds 20

Damping Injection Learning for Robots with Actor-Critic Driv...

引用

20th International Conference on Electrical engineering, Computing Science and Automatic Control, CCE 2023

作者： Tevera-Ruiz, Alejandro Garcia-Rodriguez, Rodolfo Parra-Vega, Vicente Robotics and Advanced Manufacture-CINVESTAV Saltillo Mexico Univ. Politécnica Metropolitana de Hidalgo Postgraduate Program in Aerospace Engineering Mexico

ISBN: (纸本)9798350306767

Reinforcement Learning (RL) is characterized by enforcing a reward collection mechanism that qualifies task performance aimed at optimizing a value function that tunes the action (control). In contrast to control theory, RL satisfies two metrics simultaneously: the task metric commonly, defined as the task error, and the temporal difference (TD) error. Thus, the RL has been empowered to learn how to fulfill control tasks based on a learning stage that collects rewards that evaluate a second metric of the robot's performance. In this way, including RL in control systems is an advantageous scheme for some critical tasks nowadays. Consequently, the stability can be guaranteed, largely missing in the RL's literature, to safe system operation.. In this paper, we propose an Actor-Critic (AC) scheme using the Critic Neural Network (C-NN) to approximate a value function using the TD error reduction, whereas the adaptive tuning of damping injection gain is provided by the Actor NN (A-NN) to enforce stability in closed-loop finally;achieving asymptotic stability with an underlying integral sliding mode loop. In this way, our proposal contributes to a novel model-free RL scheme that yields local exponential convergence with a smooth control action. Numeric simulations for a 2-DoF robot manipulator are presented and discussed under different conditions.. © 2023 IEEE.

关键词： Asymptotic stability

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Hierarchical Navigation Architecture and Robotic Arm Controller for a Sample Return Rover

Hierarchical Navigation Architecture and Robotic Arm Control...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Velin Dimitrov Mathew DeDonato Adam Panzica Samir Zutshi Mitchell Wills Taskin Padir Robotics Engineering Program Worcester Polytechnic Institute

This work presents a hierarchical navigation architecture and cascade classifier for sample search and identification on a space exploration rover. A three tier navigation architecture and inverse Jacobian based robot arm controller are presented. The algorithms are implemented on AERO, the Autonomous Exploration Rover, participating in the NASA Sample Return Robot Centennial Challenge in 2013 and initial results are demonstrated.

关键词： Navigation Manipulators Robot sensing systems Planning Robot kinematics

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Modular Robot Arm Design for Physical Human-Robot Interaction

Modular Robot Arm Design for Physical Human-Robot Interactio...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ty Tremblay Taskin Padir Robotics Engineering Program Worcester Polytechnic Institute

This paper describes the design and implementation of the controls and power plant for a robotic arm for physical human-robot interaction on a cyber-physical wheelchair system. There are almost 50 million people in the US who have some degree of disability, and more than 6.5 million of them experience problems with self-care. The aim of this research is to develop a system to control a modular cable-driven arm which will allow locked-in individuals, who are unable to interact with the physical world through movement and speech, to perform activities of daily living (ADL). We present the design of a compact power plant for the 5DOF arm. The robot control is implemented using the Robot Operating System (ROS) framework.

关键词： Joints Wheelchairs Mobile robots Manipulators Robot sensing systems

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DeepCat: A Deep Learning Approach to Understand Your Cat's Body Language 11

DeepCat: A Deep Learning Approach to Understand Your Cat's B...

引用

11th International Japan-Africa Conference on Electronics, Communications, and Computations, JAC-ECC 2023

作者： Fawzy, Arwa Hassan, Ahmed Gad, Ahmed Zaky, Ahmed B. El-Hussieny, Haitham Alexandria Egypt program Alexandria Egypt Benha University Faculty of Engineering at Shoubra Electrical Engineering Department Egypt Egypt-Japan University of Science and Technology Department of Mechatronics and Robotics Engineering Alexandria Egypt

ISBN: (纸本)9798350369328

Pet owners experience difficulty in understanding their pets' body language and its implications for animal welfare, given that animals cannot utilize human speech to communicate their emotions and health conditions. However, previous experiments for analyzing cat behavior have demonstrated that cats are precisely expressive. DeepCat, a deep-learning approach developed in this study, translates cats' body language signals, enabling owners to discern their feline companions' intended messages and emotional states. Our DeepCat model was trained on a dataset comprising 10,000 cat images, implementing automatic labeling to track key features, including the tail, eyes, and mouth. Presented as a Flutter application, DeepCat can function everywhere, allowing owners to easily monitor their cats and make informed decisions in situations that require caution. This paper discusses the potential benefits and limitations of DeepCat and provides suggestions for future research in this domain. © 2023 IEEE.

关键词： Emotion Recognition

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Design and Experimental Validation of a Mobile Robot Platform for Analog Planetary Exploration

Design and Experimental Validation of a Mobile Robot Platfor...

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Annual Conference on IEEE Industrial Electronics Society

作者： Joseph L. Amato Jon J. Anderson Thomas J. Carlone Michael E. Fagan Kenneth A. Stafford Taskin Padir Robotics Engineering Program Worcester Polytechnic Institute

ISBN: (纸本)9781467324199

This paper presents the design and experimental validation of a modular robotic platform for planetary exploration. A rover, ORYX 2.0, is designed and developed to serve as a research platform that can transport payloads over rough terrain. Field testing is conducted to evaluate the mobility potential of ORYX 2.0's passive kinematic suspension. Data from field testing is analyzed to identify the wheel velocities over rough terrain when straight line trajectories are desired. A simulation tool is used to estimate the terrain profile, using the 3-axis orientation data and angle of the rocking suspension. The approach used in estimating terrain profiles can effectively be used to improve the rover performance for trajectory tracking control.

关键词： topographical profiles Space Exploration Rough terrain simulation tool field experimentation tracking control Payload Platform Mobile robots

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