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Kinematic Analysis and Programming Implementation of Patrol robots Based on Ackermann’s Principle 1

引用

international conference on Communications, signal processing, and Systems, CSPS 2023

作者： Wang, Renjun Li, Lu Li, Xiaojiang Zhao, Qunfeng Zhonghuan Information College Tianjin University of Technology Tianjin China

ISBN: (数字)9789819975051

ISBN: (纸本)9789819975396

The kinematic analysis of the patrol robot is based on Ackermann theory to derive the relationship between front wheel deflection angle, rear wheel speed and robot target speed. The fitted curve is obtained by plotting a scatter plot of the relationship between the deflection angle of the robot's rudder and the deflection angle of the front wheel and fitting the curve. Ultimately the whole robot is programmed for motion control. This paper provides a basis for theoretical analysis for further research on the Ackermann principle patrol robot. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： robot programming

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MixSense: Mixture of vision Sense

MixSense: Mixture of Vision Sense

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2025 IEEE international conference on Acoustics, Speech, and signal processing, ICASSP 2025

作者： Lin, Jian Wang, Zhuoran Qiu, Qibo Chen, Jianzhong Ge, Zixian Jin, Weizhong Yan, Yuchao Yu, Li Hangzhou China School of Computing and Information University of Pittsburgh Pittsburgh United States

ISBN: (纸本)9798350368741

It is a new trend to fine-tune Large Multimodal Models (LMMs) to adapt to specific visual tasks through task-related conversation data. This approach provides a new paradigm for solving various vision-language tasks, however, it still faces two problems: (1) the global visual features input to the backbone Large Language Model (LLM) lack the focus on task-specific information, which may lead a sub-optimal performance on specific visual tasks;(2) The hallucinations on specific tasks are underestimated, which makes the model prone to factual errors during inference. In order to solve these two problems, we propose MixSense, a new LMM paradigm that aligns the visual features of specilized models and general models to the backbone LLM together, increasing the focus on specific task information while maintaining the vanilla capabilities of the model;evaluated and fine-tuned with the constructed task-specific negative samples, we can further assess the degree of hallucinations of the model on specific visual tasks and reduce it. We validate our method on a popular Object Detection (OD) task, Referring Expression Comprehension (REC), and extensive experiments demonstrate the effectiveness of our proposal. © 2025 IEEE.

关键词： Large Multimodal Model Negative Samples Specific Tasks

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Application and research of trajectory prediction of table tennis robot based on LSTM

Application and research of trajectory prediction of table t...

引用

2024 international conference on Image processing and Artificial Intelligence, ICIPAl 2024

作者： Song, Quanyu Lu, Rong College of General Education Guangdong University of Science and Technology Dongguan523013 China College of Artificial Intelligence Dongguan Polytechnic Dongguan523083 China

ISBN: (纸本)9781510681514

With the development of science and technology, table tennis robots are becoming more and more common in the daily competition and training of athletes. This study is mainly for the research and development of the vision of table tennis robots. This study uses long and short time memory network (LSTM) to predict table tennis trajectory. We collected a large amount of table tennis sport data and used it to train and test our LSTM model. By analyzing the motion trajectory of the ball, we designed an effective LSTM architecture that can capture the complex dynamic properties of table tennis movements. Experimental results show that our model achieves remarkable success in table tennis trajectory prediction, with higher accuracy and robustness compared to traditional methods. © 2024 SPIE.

关键词： Computer vision

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Research on Surface Reconstruction Method of Transparent Object Based on robot in-position Measurement 5

Research on Surface Reconstruction Method of Transparent Obj...

引用

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

作者： Piao, Tiange Du, Jing Wei, Wei Sun, Yuwen Dalian University of Technology State Key Laboratory of High-Performance Precision Manufacturing Dalian116024 China

ISBN: (纸本)9798350336030

Transparent parts are widely used in instrumentation, national defense, aerospace and other fields. These parts have strict operating environment and high optical performance requirements, and in-place measurement is the key to ensure their manufacturing requirements. However, transparent parts often have complex surface shapes and light transmission properties, which makes it difficult to meet the requirements of high-precision measurement. To solve this problem, this paper takes the aeronautical transparent parts as the object, and constructs a robot position measurement system based on spectral confocal sensor. Through the synchronous acquisition of sensor data and robot pose, the coordinate information of both sides of the transparent material is extracted in real time. On this basis, the NURBS algorithm is used to reconstruct the measured surface data, and the second-order geometric iterative algorithm is used to complete the optimal surface registration under unconstrained conditions. Finally, the evaluation of the measurement accuracy of surface parts is realized. © 2023 IEEE.

关键词： Light transmission

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Digital Shadow Enabled Integrated Multi-platform Automation System for Industrial Assembly 10

Digital Shadow Enabled Integrated Multi-platform Automation ...

引用

10th IEEE international conference on Electronics, Computing and Communication Technologies (IEEE CONECCT)

作者： Revankar, Ashutosh Halapeti, Deepa Vengurlekar, Samarth Giriyapur, Arunkumar C. KLE Technol Univ Dept Automat & Robot Hubballi India

ISBN: (纸本)9798350385939;9798350385922

This paper presents a fully autonomous assembly line for custom cubes with two sub-block options (plastic and aluminium). Users can design their cubes through an Android app or website interface. The system retrieves orders, processes them based on deadlines, and dispenses the required sub-blocks. A quality inspection station with computer vision and machine learning ensures that defect-free parts are used. Cobots handle sub-block transportation and manipulation throughout the assembly process, with a dedicated station for inserting pins when necessary. A digital Shadow model facilitates performance analysis and optimization. Cloud-based platforms manage data, order processing, and remote access. Finally, an Automated Storage and Retrieval System (ASRS) manages cube storage and delivery. This research demonstrates the potential of combining automation, machine learning, and real-time monitoring for efficient custom product assembly. The approach offers applications in various industries and lays the groundwork for future research on expanding customization options and production flow optimization.

关键词： Digital-shadow robotic assembly line Pneumatic systems Industry 4.0 IoT Control strategy optimization MATLAB Simulink OPC UA server PLCs

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Design and Validation of A Passively Actuated Food Repositioning Mechanism Applied to the Chewing robot 29

Design and Validation of A Passively Actuated Food Repositio...

引用

29th international conference on Mechatronics and Machine vision in Practice (M2VIP)

作者： Wang, Xudong Xu, Weiliang Dhupia, Jaspreet Bronlund, John Univ Auckland Dept Mech & Mechatron Engn Auckland New Zealand Massey Univ Sch Food & Adv Technol Palmerston North New Zealand Reddit Inst Palmerston North New Zealand

ISBN: (纸本)9798350325621

Research hotspots in food science and dental studies currently focus on analyzing food texture, preparing food boluses, and studying the interaction between food and the chewing system during the mastication process using in vitro experiments. Several food repositioning mechanisms have been developed and applied to the chewing robots for different applications, but they are normally actively actuated by motors or pneumatic/hydraulic valves, which increase the complexity of the system. This study aims to develop a food repositioning mechanism to mimic the function of tongue and cheek muscles during food masticatory process with no actuation. The technical requirements of the new food repositioning mechanism are summarized by analyzing the pros and cons of the existing mechanisms. A new food repositioning mechanism based on spring and V-shaped inclined plates are developed, hinge structure is applied to support the inclined plates, and its performance is validated by using simulations.

关键词： food repositioning mechanism passive actuation in vitro experiments oral processing

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ViPFormer: Efficient vision-and-Pointcloud Transformer for Unsupervised Pointcloud Understanding

ViPFormer: Efficient Vision-and-Pointcloud Transformer for U...

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IEEE international conference on robotics and Automation (ICRA)

作者： Sun, Hongyu Wang, Yongcai Cai, Xudong Bai, Xuewei Li, Deying Renmin Univ China Sch Informat Dept Comp Sci Beijing 100872 Peoples R China

ISBN: (纸本)9798350323658

Recently, a growing number of work design unsupervised paradigms for point cloud processing to alleviate the limitation of expensive manual annotation and poor transferability of supervised methods. Among them, CrossPoint follows the contrastive learning framework and exploits image and point cloud data for unsupervised point cloud understanding. Although the promising performance is presented, the unbalanced architecture makes it unnecessarily complex and inefficient. For example, the image branch in CrossPoint is similar to 8.3x heavier than the point cloud branch leading to higher complexity and latency. To address this problem, in this paper, we propose a lightweight vision-and-Pointcloud Transformer (ViPFormer) to unify image and point cloud processing in a single architecture. ViPFormer learns in an unsupervised manner by optimizing intra-modal and cross-modal contrastive objectives. Then the pretrained model is transferred to various downstream tasks, including 3D shape classification and semantic segmentation. Experiments on different datasets show ViPFormer surpasses previous state-of-the-art unsupervised methods with higher accuracy, lower model complexity and runtime latency. Finally, the effectiveness of each component in ViPFormer is validated by extensive ablation studies. The implementation of the proposed method is available at https: //***/auniquesun/ViPFormer.

关键词： Semantic Segmentation

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Medicine Authentication Based on Image processing Using Convolutional Neural Networks 16

Medicine Authentication Based on Image Processing Using Conv...

引用

16th international conference on Computer and Automation Engineering (ICCAE)

作者： Ramos, Rodolfo Ruperto T., III Samonte, Kevin Rayne B. Manlises, Cyrel O. Mapua Univ Sch Elect Elect & Comp Engn Manila 1002 Philippines

ISBN: (纸本)9798350370058;9798350370164

The proliferation of counterfeit pharmaceuticals presents a critical challenge to public health and safety worldwide. A common method to differentiate authentic from counterfeit medicine is visually inspect the medicine's packaging. However, medicine packaging is susceptible and easy to replication. This research investigates an image-based classification method using machine learning and computer vision to differentiate between counterfeit and authentic medicine packaging. This research aims to develop a system that can authenticate local paracetamol and Biogesic based on support vector machines and convolutional neural networks. This can be done through these specific objectives: (1) To be able to capture PNG images of the packaging of the paracetamol using a Raspberry Pi camera;(2) To be able to use Support Vector Machines for feature extraction and Convolutional Neural Network models for the classification;(3) To be able to verify the reliability of the system using a confusion matrix. The classification of this study was evaluated using a confusion matrix. The resulting accuracy of the system is 88.75 %. Despite the promising results yielded by the developed system, the researchers recommend considering a wider database of medicines as well as features to consider.

关键词： convolutional neural networks support vector machines feature extraction image classification counterfeit medicine classification

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KNOWLEDGE-INFUSED LEARNING FOR FINE-GRAINED PLANT DISEASE RECOGNITION 31

KNOWLEDGE-INFUSED LEARNING FOR FINE-GRAINED PLANT DISEASE RE...

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2024 international conference on Image processing

作者： Ahmad, Jamil Gueaieb, Wail El Saddik, Abdulmotaleb De Masi, Giulia Karray, Fakhri Mohamed Bin Zayed Univ Artificial Intelligence Abu Dhabi U Arab Emirates Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada Technol Innovat Inst Autonomous Robot Res Ctr Abu Dhabi U Arab Emirates Univ Waterloo Sch Elect & Comp Engn Waterloo ON Canada

ISBN: (纸本)9798350349405;9798350349399

Domain knowledge exists in various forms, including text, ontologies, graphs, images, audio, and videos. In plant disease detection, most works solely utilize images with disease labels, neglecting textual descriptions of visual disease symptoms used by human experts for diagnosis. These text descriptions and sample images aid expert identification of visual symptoms. We propose a novel method that leverages text descriptions and image data by modeling domain-specific knowledge about visual symptoms in leaf images as separate feature channels. Each channel corresponds to specific features whose absence or presence in the image influences model predictions. We introduce a channel attention-guided fusion module for weighting each channel based on the input and corresponding output. The combined feature channels are transformed into a standardized 3-channel input format, which can then be processed by any pre-trained convolutional neural network (CNN) as input for feature extraction and subsequent classification. Furthermore, intermediate activations of the channel attention layer combined with the weights from the fusion layer make model predictions explainable. Experimental results on three publicly available datasets of apple and cucumber leaf diseases demonstrate improvements of up to 5% utilizing various state-of-the-art CNN architectures, indicating the efficacy of incorporating textual disease descriptions using the proposed approach.

关键词： knowledge-infusion feature extraction channel attention disease detection explainability

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Hand Orientation Detection Based on Disparity Maps from Stereo Imagery

Hand Orientation Detection Based on Disparity Maps from Ster...

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IEEE international conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)

作者： Setiawan, Dion Yuniarno, Eko Mulyanto Purnomo, Mauridhy Hery Inst Teknol Sepuluh Nopember Dept Elect Engn Surabaya Indonesia Inst Teknol Sepuluh Nopember Dept Elect Engn Dept Comp Engn Surabaya Indonesia

ISBN: (纸本)9798350322996;9798350323009

Manipulating objects is one of the most basic human interactions. This involves holding, shifting, lifting, and passing objects to other people. These interactions can be replicated for human assistive robot systems in robotics, which can help the elderly with their daily tasks. Many researchers have developed 2D image-based approaches to produce hand landmark detection to recognize hand shapes and gestures. However, there are shortcomings in the resulting data output, namely that it does not provide the characteristics of the distance and orientation of the hand being detected. As a result, it cannot be utilized as input to control the robot manipulator's movements to get closer to the region of the human hand. We have designed a hand position and orientation recognition system with a stereo camera to anticipate its disparity map, which includes distance prediction data for every map pixel, to overcome this challenge. The disparity map is projected onto a point cloud using a hand landmark detection technique, and the points that match the hand landmarks are chosen. We employ the Singular Value Decomposition (SVD) mathematical technique to ascertain the hand position and orientation. We verified the sequence of tasks completed to determine the position and orientation of the stereo camera. Furthermore, our approach is user-friendly and can be easily applied across a range of simpler systems, achieving a processing speed of approximately 10.03 FPS.

关键词： Elderly Assistive robots Interaction Stereo-vision 3D Hand Tracking

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