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检索条件"机构=Center for Robotics and Control"

共 1201 条记录，以下是251-260 订阅

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Two Stage Technical Vision Algorithm for Automatic Fruit Picking Based on Neural Networks and Hough Transform

Two Stage Technical Vision Algorithm for Automatic Fruit Pic...

引用

International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： L. A. Rybak V. V. Cherkasov A. A. Voloshkin Scientific Research Institute of Robotics and Control Systems Belgorod State Technological University n.a. V.G. Shukhov Belgorod Russia Federal Research Center “Informatics and Management” of the Russian Academy of Sciences Moscow Russia

ISBN: (数字)9798331512194

ISBN: (纸本)9798331512200

The article presents the development of a technical vision algorithm for automatic fruit harvesting based on the use of the YOLOv8 neural network and data obtained from binocular cameras. The algorithm uses a two-stage approach: at the first stage, the front-facing RGB-D camera installed on the mobile platform determines the position of trees and fruits, and at the second stage, the camera on the capture device specifies the coordinates of fruits using segmentation and Hough transform methods. To improve speech recognition accuracy, we use HSVspace filtering and combine data from multiple cameras using the Kalman filter. The results of modeling and experimental studies confirming the resistance to environmental influences, such as partial overlap of objects, changing lighting and the presence of foreign elements, are presented.

关键词： Resistance Training Accuracy Filtering Neural networks Lighting Transforms Speech recognition Cameras Manufacturing

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Spatial-Temporal Hypergraph Neural Network based on Attention Mechanism for Multi-view Data Action Recognition 10

Spatial-Temporal Hypergraph Neural Network based on Attentio...

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10th International Conference on Dependable Systems and Their Applications, DSA 2023

作者： Wu, Zhixuan Ma, Nan Zhi, Tao Xu, Genbao Beijing Union University Beijing Key Laboratory of Information Service Engineering College of Robotics Beijing100101 China Beijing University of Technology Faculty of Information Technology Beijing100124 China Beijing University of Technology Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Beijing100124 China Yunji Technology Beijing100081 China

ISBN: (纸本)9798350304770

To address the issue of large network computing parameters for spatial-temporal features of actions in multi-view video sequences, this paper proposes a Spatial-Temporal Hypergraph Neural Network based on Attention Mechanism (STHGNN-AM). This method consists of a Temporal Attention Mechanism based on Trainable Threshold (TAM-TT) and a Multi-scale Spatial-Temporal Residual Module (MS-STRM), achieving multi-view data action recognition. Specifically, TAM-TT is constructed by using a learnable threshold to extract key frames of actions from different view video frames input to the module. MS-STRM is employed to further improve the model performance, and high-order semantic features of actions are learned in a hypergraph neural network. The MS-STRM extracts features using a multi-scale approach, modeling long-term and short-term semantic information to capture the temporal information changes between different frames. Comparative experiments on the NTU RGB+D and imitating traffic police gestures datasets evince the superior performance and heightened recognition accuracy exhibited by the proposed methodology, effectively enhancing the cognitive ability of machine-human body language interaction. © 2023 IEEE.

关键词： Semantics

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Step and Timing Adaptation during Online DCM Trajectory Generation for Robust Humanoid Walking with Double Support Phases

Step and Timing Adaptation during Online DCM Trajectory Gene...

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IEEE-RAS International Conference on Humanoid Robots

作者： Tobias Egle Johannes Englsberger Christian Ott Faculty of Electrical Engineering and Information Technology Automation and Control Institute TU Wien Vienna Austria Institute of Robotics and Mecha-tronics German Aerospace Center (DLR) Wessling Germany

In this paper, we present a robust DCM-based online trajectory generator with step timing adaptation using MPC in addition to manipulating the ground reaction forces by the DCM tracking controller. The proposed control framework utilizes three strategies to react to disturbances: timing adaptation, footstep position adjustment, and CoP modulation. Most state-of-the-art walking controllers only address some of these aspects, and especially the timing adaptation is often neglected in the presence of double support phases as the resulting optimization problem generally becomes nonlinear. We show that we can keep the fast disturbance rejection from the DCM tracking controller while adjusting the timing and location of the footsteps via MPC if the CoP-based ankle strategy is insufficient to maintain balance. This framework is particularly relevant for robots with active control of the CoP inside the support polygon by utilizing a combination of ankle and step strategy to take full advantage of the robot's capabilities in response to external disturbances. The method is validated in simulation on the robot kangaroo. It has lightweight, fully actuated legs and a sufficiently large contact area, making it highly suitable for a combined step time adaptation and contact force modulation approach.

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Self-Tuning Robust Tracking control for Autonomous Underwater Vehicles

Self-Tuning Robust Tracking Control for Autonomous Underwate...

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

作者： Nima Maghooli Fahimeh S. Tabatabaee-Nasab S. Ali A. Moosavian Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotics … Automated Systems (ARAS) Laboratory K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781665454537

This paper addresses the control design problem for a nonlinear and nonholonomic dynamics model of an autonomous underwater vehicle. The kinematics control algorithm is a PID controller while a self-tuning control method is used for trajectory tracking. The kinetics control algorithm is based on an integral sliding mode technique that is robust against time-varying disturbances. The obtained results presented here use the Remote Environmental Monitoring UnitS (REMUS) underwater vehicle model and show the high performance of the controller. Based on the results demonstrated for the two designated trajectories, the tracking quality of self-tuning robust control, despite the significant similarity of the control input of both algorithms for x, y, and z, is much better than the sliding mode control. As a result, AUV was able to follow the desired trajectory, and tracking errors converged to zero. It is worth noting that at non-derivative points of the path (1 st trajectory), tracking errors were entirely within response quality limits (y = ±0.05[m]). The order of control efforts of the proposed control is suitable and can be implemented in the physical system.

关键词： Robust control Autonomous underwater vehicles Mechatronics Trajectory tracking Heuristic algorithms Robot kinematics Trajectory

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Experimental Validation of Functional Iterative Learning control on a One-Link Flexible Arm

Experimental Validation of Functional Iterative Learning Con...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Sjoerd Drost Pietro Pustina Franco Angelini Alessandro De Luca Gerwin Smit Cosimo Della Santina Department of Cognitive Robotics Delft University of Technology Delft Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Department of Information Engineering Research Center “Enrico Piaggio” University of Pisa Pisa Italy Institute of Robotics and Mechatronics German Aerospace Center (DLR) Oberpfaffenhofen Germany

Performing precise, repetitive motions is essential in many robotic and automation systems. Iterative learning control (ILC) allows determining the necessary control command by using a very rough system model to speed up the process. Functional iterative learning control is a novel technique that promises to solve several limitations of classic ILC. It operates by merging the input space into a large functional space, resulting in an over-determined control task in the iteration domain. In this way, it can deal with systems having more outputs than inputs and accelerate the learning process without resorting to model discretizations. However, the framework lacks so far a validation in experiments. This paper aims to provide such experimental validation in the context of robotics. To this end, we designed and built a one-link flexible arm that is actuated by a stepper motor, which makes the development of an accurate model more challenging and the validation closer to the industrial practice. We provide multiple experimental results across several conditions, proving the feasibility of the method in practice.

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Relevance of the Rayleigh-Bénard model in studying optical turbulence

Relevance of the Rayleigh-Bénard model in studying optical ...

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2024 Applications of Lasers for Sensing and Free Space Communications, LS and C 2024

作者： Avramov-Zamurovic, Svetlana Ferlic, Nathaniel A. Judd, K. Peter Weapons Robotics and Control Engineering Department United States Naval Academy 597 McNair Rd. Hopper Hall AnnapolisMD21402 United States Naval Air Warfare Center Aircraft Division 22347 Cedar Point Road Patuxent RiverMD20670 United States United States Naval Research Laboratory 4555 Overlook Ave. SW WashingtonDC20375 United States

The Rayleigh-Bénard physical model generates well-defined optical turbulence. We demonstrate its characterization and use in various experimental studies, including phase retrieval, structured light, and optical ...

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Study of the Applicability of the Method of Optical Triangulation for Evaluation of the Geometric Parameters and Cleanliness of the Surface of Products of Complex Shapes

Study of the Applicability of the Method of Optical Triangul...

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Information, control, and Communication Technologies (ICCT), International Conference on

作者： Vyacheslav V. Konyashov Alexey S. Sergeev Oleg A. Kolganov Alexey V. Fedorov Kseniya A. Konyashova Vladimir V. Bychenok Faculty of Control Systems and Robotics ITMO University ST Petersburg Russia Scientific and technical center “Etalon” ST Petersburg Russia Institution of Science “IKCSEKT” ST Petersburg Russia

The results of experimental studies of the applicability of the method of optical laser triangulation for constructing the profile of conical and cylindrical products with a ribbed surface, made by milling, are reflected. An algorithm for constructing a geometric profile of products of complex shape based on a system of triangulation sensors is proposed. The results of experimental approbation of the proposed algorithm on the stand for automated control of the geometry of complex-profile parts using a laser triangulation 2-D scanner are presented. The sensitivity of a laser triangulation 2-D scanner to the roughness parameters during milling the surface of products is evaluated. The accuracy characteristics of the triangulation method for determining the surface roughness parameters for different orientations of laser radiation with respect to the test object are estimated.

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Performance Evaluation of Beams Carrying Orbital Angular Momentum in Optical Turbulence in Rayleigh-Bénard Underwater Convection

Performance Evaluation of Beams Carrying Orbital Angular Mom...

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2024 Applications of Lasers for Sensing and Free Space Communications, LS and C 2024

作者： Avramov-Zamurovic, Svetlana Ferlic, Nathaniel A. O’Malley, Owen Judd, K. Peter Weapons Robotics and Control Engineering Department United States Naval Academy 597 McNair Rd. Hopper Hall AnnapolisMD21402 United States Naval Air Warfare Center Aircraft Division 22347 Cedar Point Road Patuxent RiverMD20670 United States United States Naval Research Laboratory 4555 Overlook Ave. SW WashingtonDC20375 United States

We compare the propagation of a Gaussian beam to the beams that carry OAM in moderate and strong underwater optical turbulence created by Rayleigh Bénard convection. Analysis focuses on scintillation index and fr... 详细信息

关键词： Gaussian beams

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HCRI: A ROS2 Human Collision Object Interface for Robotic Manipulation Planning

HCRI: A ROS2 Human Collision Object Interface for Robotic Ma...

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Changcong Wang Chongyi Wei Shaoping Bai Yibin Li Xincheng Tian Lelai Zhou the Center for Robotics School of Control Science and Engineering Shandong University Jinan China the Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan China Department of Materials and Production Aalborg University Aalborg Denmark

Human-Robot Collaboration (HRC) is people and robots work together in the same workspace to achieve shared goals. To ensure safety, robots need to perceive the position of the human body for planning purposes. However, there is no universal method for converting the human body into collision objects. To solve this problem, we propose an interface to convert the human body segments into collision objects in the robot planning scene. The interface estimates the human body Skinned Multi-Person Linear model (SMPL) by RGB image and measures the collision object size of the corresponding body segment. The corresponding size of collision objects are added to the corresponding positions of the human pose estimated by different types of sensors. The accuracy of human size estimation is verified on TotalMocap of AMASS. The interface with OctoMap is compared to evaluate the efficiency and the validity on interface is verified on the robot UR5e.

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Within-Hand Manipulation with an Underactuated Dexterous Hand Based on Pre-Trained Reinforcement Learning

Within-Hand Manipulation with an Underactuated Dexterous Han...

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Chinese Automation Congress (CAC)

作者： Xin Li Wenrui Chen Yaonan Wang Qiang Diao Sijie Wu Fan Yang National Engineering Research Center for Robot Visual Perception and Control College of Electrical and Information Engineering Hunan University Changsha China National Engineering Research Center for Robot Visual Perception and Control School of Robotics Hunan University Changsha China National Engineering Research Center for Robot Visual Perception and Control College of Mechanical and Vehicle Engineering Hunan University Changsha China

This paper investigates a dexterous manipulation method for multi-fingered hands based on the approximate policy optimization (PPO) algorithm. First, a prior knowledge base of dexterous manipulation demonstration data is provided for the PPO algorithm, and the original model is pre-trained to guide fast network training. Second, a new reward function is proposed to optimize rotational manipulation action decisions based on hand joints, fingertip tactile, and object pose infor mation. Finally, a three-fingered hand is used as an example for rotational manipulation experiments, and the comparative simulation results show that the method is more efficient than the traditional PPO algorithm and provides ideas for dexterous manipulation of multi-fingered hands.

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