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检索条件"任意字段=International Conference on Robot Vision and Signal Processing"

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Intelligent tapping robot system for surface machining of hatch body

Intelligent tapping robot system for surface machining of ha...

引用

2023 IEEE international conference on Sensors, Electronics and Computer Engineering, ICSECE 2023

作者： Zhang, Jieru Li, Guanhua Liang, Yuanzhi Xue, Shanshan Lu, Peng Chang, Xiaofei Beijing Xinfeng Aerospace Equipment Co. Ltd. Beijing China

ISBN: (纸本)9798350313734

In the space field, there are many types of cabin parts table and uneven distribution. Manual tapping is usually used. The processing process is complicated, and it needs to be constantly turned to find the right, with high labor cost and low processing efficiency. In the space field, there are many types of cabin parts table and uneven distribution. Manual tapping is usually used. The processing process is complicated, and it needs to be constantly turned to find the right, with high labor cost and low processing efficiency. To solve the above problems, industrial robots equipped with tapping modules, visual modules and laser pose modulators are proposed to realize intelligent tapping operations on the surface of the cabin body. Firstly, the machine vision algorithm is used to identify the characteristics of the reference hole and locate the hole center with high precision, and the rotary table is guided to realize the cabin body Angle alignment. Then, the laser attitude adjustment algorithm is used to realize the automatic measurement of the normal direction of the cabin surface, and the algorithm is used to realize the automatic adjustment of the robot's end attitude, so as to ensure that the machining tool taps along the axis direction of the hole to be processed. Then, the robot automatically taps each row of holes according to the off-line programming trajectory until the tapping of all holes is completed. The test results show that both the aperture and perpendicularity meet the technological requirements. Therefore, the system studied in this paper can meet the actual production requirements. To solve the above problems, industrial robots equipped with tapping modules, visual modules and laser pose modulators are proposed to realize intelligent tapping operations on the surface of the cabin body. Firstly, the machine vision algorithm is used to identify the characteristics of the reference hole and locate the hole center with high precision, and the rotary t

关键词： Efficiency

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A Study on the Effects of Increasing Obstacles on Path Generation Time, Energy and Steps Count using Rapidly Exploring Random Tree∗ (Asterisk) Algorithm

A Study on the Effects of Increasing Obstacles on Path Gener...

引用

2023 international conference on Artificial Intelligence robotics, signal and Image processing, AIRoSIP 2023

作者： Ul Husnain, Anees Shah, Noraisyah Mohamed Mokhtar, Norrima Bin Abdul Halim, Syahmi Adli Takao, Give Universiti Malaya Department of Electrical Engineering Kuala Lumpur Malaysia Hiroshima University Graduate School of Advanced Science and Engineering Higashi Hiroshima Japan

ISBN: (纸本)9798350327472

Collision avoidance in complex or dynamic environments has been under the light for quite some time in robotic research. This article presents the study of Rapidly Exploring Random Tree (RRT) and its variation in an environment containing dynamic obstacles to avoid collision and reach a target location. A simulation was established consisting of a multi-obstacle environment resembling real-world complexities of an indoor environment. The objective of the study was the feasibility of the path generated for the robot, considering the limitations like maximum turning angle, acceleration or deceleration, number of maneuvers. The smoothness of the generated path plays critical role for the robots, therefore, this case study of RRT highlights this issue and eventually recommends the consideration of hardware limitations in robots or a threshold of smoothness for autonomous collision avoidance path planning algorithms. © 2023 IEEE.

关键词： robot programming

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Design and Implementation of Pipeline Detection robot with Three-Dimensional Scanning Capability

Design and Implementation of Pipeline Detection Robot with T...

引用

2023 IEEE international conference on signal processing, Communications and Computing, ICSPCC 2023

作者： Chen, Dansheng Zhao, Min Ding, Ning Yuan, Xiaoqiang Li, Nan Fang, Zehao Shenzhen Institute of Artificial Intelligence and Robotics for Society Center for Special Robots Shenzhen China Institute of Robotics and the Intelligent Manufacturing the Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9798350316728

To adapt to different application scenarios, the structure and execution components of pipeline robots need to be customized according to specific projects. Custom design requires a lot of time and manpower. Therefore, this paper proposes a pipeline robot based on network communication, which can achieve three-dimensional inspection inside pipelines with good expandability, reducing the development work for new projects and allowing for quick product updates. The hardware of the robot is designed around an ethernet switch controller, which connects communication modules and sensors, the expansion interface is reserved for further use. The software is based on the special workflow of pipeline detection robots and is designed around robot control - data acquisition - pipeline defect analysis. Testing in various scenarios showed that the design of the robot meets the functional requirements of pipeline detection as well as having good expandability. © 2023 IEEE.

关键词： robots

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vision- and map-based non-line-of-sight satellites hybridized processing 26

Vision- and map-based non-line-of-sight satellites hybridize...

引用

IEEE 26th international conference on Intelligent Transportation Systems (ITSC)

作者： Betaille, David Meurie, Cyril Cocheril, Yann Univ Gustave Eiffel Struct & Instrumentat Integree COSYS SII F-44344 Bouguenais France Univ Gustave Eiffel COSYS LEOST Lab Elect Ondes & Signaux Transports F-59650 Villeneuve Dascq France

ISBN: (纸本)9798350399462

Intelligent transportation systems use GNSS receivers as basic technological components. In urban applications one faces the problem of GNSS multipath and particularly of non-line-of-sight (NLOS) satellites. The development of GNSS receiver technologies for mass market encompasses the capability NLOS satellites processing by innovative techniques, not only based on the signal to Noise Ratio, but also on vision or city model. This is particularly needed for urban positioning of cars for applications which require high accuracy and integrity, typically driving automation. This article deals with the detection of NLOS satellites among those tracked by an automotive-range receiver. We aim at developing a method jointly based on the analysis of video stream and a 3D map model of the environment. The article provides a literature review, an evaluation of some existing techniques and a preliminary analysis of the implementation of the retained algorithm on a prototype developed in the frame of a European H2020 "Fundamental Elements call" project.

关键词： Satellites

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Research on Binocular Stereo vision Ranging Based on Improved YOLOv5s 5

Research on Binocular Stereo Vision Ranging Based on Improve...

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5th international conference on Intelligent Control, Measurement and signal processing, ICMSP 2023

作者： Zhang, Pengwei Liu, Zhenyu School of Electronic and Information Engineering Beijing Jiaotong University Beijing China

ISBN: (纸本)9798350336030

In order to accurately obtain the distance information of the target, a target detection and distance measurement method based on an improved YOLOv5s model and binocular stereo vision fusion is proposed. First, the attention mechanism is introduced into the YOLOv5s model, and the comparison experiments show that the introduction of the ECA module improves the accuracy rate by 2.1%. Furthermore, by adding the SGBM-based binocular distance measurement algorithm to the YOLOv5s model, the distance of the target is calculated and given using the binocular parallax information during target detection. The experimental results show that the method measures the distance with less error, which provides technical support for many low-cost, non-contact ranging scenarios. © 2023 IEEE.

关键词： Stereo image processing

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Rethink Long-Tailed Recognition with vision Transforms 48

Rethink Long-Tailed Recognition with Vision Transforms

引用

48th IEEE international conference on Acoustics, Speech and signal processing, ICASSP 2023

作者： Xu, Zhengzhuo Yang, Shuo Wang, Xingjun Yuan, Chun Tsinghua University Tsinghua Shenzhen International Graduate School China Shenzhen Peng Cheng Lab China

ISBN: (纸本)9781728163277

In the real world, data tends to follow long-Tailed distributions w.r.t. class or attribution, motivating the challenging Long-Tailed Recognition (LTR) problem. In this paper, we revisit recent LTR methods with promising vision Transformers (ViT). We figure out that 1) ViT is hard to train with longtailed data. 2) ViT learns generalized features in an unsupervised manner, like mask generative training, either on longtailed or balanced datasets. Hence, we propose to adopt unsupervised learning to utilize long-Tailed data. Furthermore, we propose the Predictive Distribution Calibration (PDC) as a novel metric for LTR, where the model tends to simply classify inputs into common classes. Our PDC can measure the model calibration of predictive preferences quantitatively. On this basis, we find many LTR approaches alleviate it slightly, despite the accuracy improvement. Extensive experiments on benchmark datasets validate that PDC reflects the model's predictive preference precisely, which is consistent with the visualization. © 2023 IEEE.

关键词： Computer vision

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SPADE: Self-Supervised Pretraining for Acoustic Disentanglement 48

SPADE: Self-Supervised Pretraining for Acoustic Disentanglem...

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48th IEEE international conference on Acoustics, Speech and signal processing, ICASSP 2023

作者： Harvill, John Barber, Jarred Nair, Arun Pishehvar, Ramin University of Illinois Urbana-Champaign United States Amazon Alexa Ai United States

ISBN: (纸本)9781728163277

Self-supervised representation learning approaches have grown in popularity due to the ability to train models on large amounts of unlabeled data and have demonstrated success in diverse fields such as natural language processing, computer vision, and speech. Previous self-supervised work in the speech domain has disentangled multiple attributes of speech such as linguistic content, speaker identity, and rhythm. In this work, we introduce a self-supervised approach to disentangle room acoustics from speech and use the acoustic representation on the downstream task of device arbitration. Our results demonstrate that our proposed approach significantly improves performance over a baseline when labeled training data is scarce, indicating that our pretraining scheme learns to encode room acoustic information while remaining invariant to other attributes of the speech signal. © 2023 IEEE.

关键词： Natural language processing systems

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Lightmyography Based Decoding of Human Intention Using Temporal Multi-Channel Transformers

Lightmyography Based Decoding of Human Intention Using Tempo...

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IEEE/RSJ international conference on Intelligent robots and Systems (IROS)

作者： Godoy, Ricardo V. Dwivedi, Anany Shahmohammadi, Mojtaba Liarokapis, Minas Univ Auckland Dept Mech & Mechatron Engn New Dexter Res Grp Auckland New Zealand Friedrich Alexander Univ Erlangen Nurnberg Inst Autonomous Syst & Mechatron Erlangen Germany

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

For the development of muscle-machine interfaces (MuMIs), researchers have relied mainly on Electromyography (EMG) signals. However, these signals require complex hardware systems, as well as specialized signal processing and feature extraction methods. To overcome these issues, in our previous work, we proposed a novel MuMI for decoding human intention and motion, called Lightmyography (LMG). To improve the performance of this interface even further, in this work, we employ two novel deep learning techniques called Temporal Multi-Channel Transformer (TMC-T) and Temporal Multi-Channel vision Transformer (TMC-ViT) for the classification of hand gestures based on the LMG data. The performance of these two Transformer-based methods is evaluated and compared with other well-known deep learning and classical machine learning methods. This work also addresses the influence of varying parameters defined during the training phase of decoding models, such as the size and shape of the input data packet. A series of data augmentation techniques were also employed to generate synthetic data and increase the dataset size so as to train deep learning models more efficiently.

关键词： Deep learning Training Adaptation models signal processing algorithms signal processing Transformers Data models

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EXPLORING EFFECTIVE STIMULUS ENCODING VIA vision SYSTEM MODELING FOR VISUAL PROSTHESES 12

EXPLORING EFFECTIVE STIMULUS ENCODING VIA VISION SYSTEM MODE...

引用

12th international conference on Learning Representations, ICLR 2024

作者： Wang, Chuanqing Wu, Di Fang, Chaoming Yang, Jie Sawan, Mohamad CenBRAIN Neurotech School of Engineering Westlake University Hangzhou China Westlake Institute for Optoelectronics Hangzho Fuyang311421 China

Visual prostheses are potential devices to restore vision for blind people, which highly depends on the quality of stimulation patterns of the implanted electrode array. However, existing processing frameworks prioritize the generation of stimulation while disregarding the potential impact of restoration effects and fail to assess the quality of the generated stimulation properly. In this paper, we propose for the first time an end-to-end visual prosthesis framework (StimuSEE) that generates stimulation patterns with proper quality verification using V1 neuron spike patterns as supervision. StimuSEE consists of a retinal network to predict the stimulation pattern, a phosphene model, and a primary vision system network (PVS-net) to simulate the signal processing from the retina to the visual cortex and predict the firing rate of V1 neurons. Experimental results show that the predicted stimulation shares similar patterns to the original scenes, whose different stimulus amplitudes contribute to a similar firing rate with normal cells. Numerically, the predicted firing rate and the recorded response of normal neurons achieve a Pearson correlation coefficient of 0.78. © 2024 12th international conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Restoration

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Depalletisation humanoid torso: Real-time cardboard package detection based on deep learning and pose estimation algorithm 27

Depalletisation humanoid torso: Real-time cardboard package ...

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27th international conference on Methods and Models in Automation and robotics (MMAR)

作者： Yesudasu, Santheep Sebbata, Wafae Brethe, Jean-Francois Bonnin, Patrick Normandy Univ GREAH Le Havre France Sch Engn ECE Robot Paris France Normandy Univ ISEL Le Havre France Univ Versailles ISTY Mantes La Ville France

ISBN: (纸本)9798350311075

This paper presents a system for efficiently depalletising textureless and versatile cardboard boxes, even when they are tightly packed together, by utilizing deep learning and point clouds. The system uses an industrial humanoid torso equipped with a 6 DoF dual-arm and an RGB-D camera allowing for fast, accurate, and adaptable object handling without the need for additional sensors or setup. Operating in a warehouse environment, the robot is responsible for loading/unloading pallets of cardboard packages and placing them onto conveyor belts for further processing. The system uses ROS interface for communication, control, and MoveIt for dual-arm path planning and achieves impressive F1 scores of 0.81 and 0.90 for single-face and multi-face boxes, respectively, as demonstrated through real-time testing. These results provide valuable insights into the system's capabilities and potential future improvements.

关键词： deep learning computer vision object detection point cloud pose estimation dual-arm humanoid torso depalletisation

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