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7th Conference on Robot Learning, CoRL 2023

作者： Zhang, Harry Eisner, Ben Held, David Robotics Institute School of Computer Science Carnegie Mellon University United States

Understanding and manipulating articulated objects, such as doors and drawers, is crucial for robots operating in human environments. We wish to develop a system that can learn to articulate novel objects with no prior interaction, after training on other articulated objects. Previous approaches for articulated object manipulation rely on either modular methods which are brittle or end-to-end methods, which lack generalizability. This paper presents FlowBot++, a deep 3D vision-based robotic system that predicts dense per-point motion and dense articulation parameters of articulated objects to assist in downstream manipulation tasks. FlowBot++ introduces a novel per-point representation of the articulated motion and articulation parameters that are combined to produce a more accurate estimate than either method on their own. Simulated experiments on the PartNet-Mobility dataset validate the performance of our system in articulating a wide range of objects, while real-world experiments on real objects' point clouds and a Sawyer robot demonstrate the generalizability and feasibility of our system in real-world scenarios. Videos are available on our anonymized website here. © 2023 Proceedings of Machine Learning Research. All Rights Reserved.

关键词： 3D Learning Articulated Objects Manipulation

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Person Segmentation and Action Classification for Multi-Channel Hemisphere Field of View LiDAR Sensors

Person Segmentation and Action Classification for Multi-Chan...

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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Seliunina, Svetlana Otelepko, Artem Memmesheimer, Raphael Behnke, Sven University of Bonn Autonomous Intelligent Systems Group Computer Science Institute VI - Intelligent Systems and Robotics Lamarr Institute for Machine Learning and Artificial Intelligence Center for Robotics Germany

ISBN: (纸本)9798331531614

Robots need to perceive persons in their surroundings for safety and to interact with them. In this paper, we present a person segmentation and action classification approach that operates on 3D scans of hemisphere field of view LiDAR sensors. We recorded a data set with an Ouster OSDome-64 sensor consisting of scenes where persons perform three different actions and annotated it. We propose a method based on a MaskDINO model to detect and segment persons and to recognize their actions from combined spherical projected multi-channel representations of the LiDAR data with an additional positional encoding. Our approach demonstrates good performance for the person segmentation task and further performs well for the estimation of the person action states walking, waving, and sitting. An ablation study provides insights about the individual channel contributions for the person segmentation task. The trained models, code and dataset are made publicly available. © 2025 IEEE.

关键词： Signal encoding

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Fusion of Feature Ranking Methods for an Effective Intrusion Detection System

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computers, Materials & Continua 2023年第8期76卷 1721-1744页

作者： Seshu Bhavani Mallampati Seetha Hari School of Computer Science and Engineering VIT-AP UniversityAndhra PradeshIndia Center of Excellence AIand RoboticsVIT-AP UniversityAndhra PradeshIndia

Expanding internet-connected services has increased cyberattacks,many of which have grave and disastrous *** Intrusion Detection System(IDS)plays an essential role in network security since it helps to protect the network from vulnerabilities and *** extensive research was reported in IDS,detecting novel intrusions with optimal features and reducing false alarm rates are still ***,we developed a novel fusion-based feature importance method to reduce the high dimensional feature space,which helps to identify attacks accurately with less false alarm ***,to improve training data quality,various preprocessing techniques are *** Adaptive Synthetic oversampling technique generates synthetic samples for minority *** the proposed fusion-based feature importance,we use different approaches from the filter,wrapper,and embedded methods like mutual information,random forest importance,permutation importance,Shapley Additive exPlanations(SHAP)-based feature importance,and statistical feature importance methods like the difference of mean and median and standard deviation to rank each feature according to its *** by simple plurality voting,the most optimal features are *** the optimal features are fed to various models like Extra Tree(ET),Logistic Regression(LR),Support vector Machine(SVM),Decision Tree(DT),and Extreme Gradient Boosting Machine(XGBM).Then the hyperparameters of classification models are tuned with Halving Random Search cross-validation to enhance the *** experiments were carried out on the original imbalanced data and balanced *** outcomes demonstrate that the balanced data scenario knocked out the imbalanced ***,the experimental analysis proved that our proposed fusionbased feature importance performed well with XGBM giving an accuracy of 99.86%,99.68%,and 92.4%,with 9,7 and 8 features by training time of 1.5,4.5 and 5.5 s on Network Security Laborat

关键词： Cyber security feature ranking imbalance preprocessing IDS SHAP

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Collaborate and Explain on the Fly: Nonmonotonic Logical Reasoning and Incremental Learning for Ad Hoc Teamwork 21

Collaborate and Explain on the Fly: Nonmonotonic Logical Rea...

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21st International Workshop on Non-Monotonic Reasoning, NMR 2023

作者： Dodampegama, Hasra Sridharan, Mohan Intelligent Robotics Lab School of Computer Science University of Birmingham United Kingdom

This paper describes an architecture for ad hoc teamwork, i.e., to enable an agent to collaborate with other agents "on the fly". State of the art frameworks for ad hoc teamwork often pursue a data-driven approach, using a large labeled dataset of prior observations to model the behavior of other agents and to determine the ad hoc agent’s behavior. These models are computationally expensive to learn, lack transparency, and make it difficult to recognize and adapt to previously unseen changes. In a departure from existing work, we introduce an architecture for ad hoc teamwork that performs non-monotonic logical reasoning with prior commonsense domain knowledge and models that are learned and revised rapidly from limited examples to predict the behavior of other agents. In addition, the architecture enables the agent to provide relational descriptions as on-demand explanations of its decisions and beliefs in response to different types of questions. We evaluate the architecture’s capabilities in two benchmark multiagent collaboration domains: Fort Attack and Half field Offense, in comparison with data-driven and knowledge-driven baselines. © 2023 Copyright for this paper by its authors.

关键词： Multi agent systems

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A Cognitive Architecture for Integrated Robot Systems

A Cognitive Architecture for Integrated Robot Systems

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2023 International Workshop on Cognitive AI, CogAI 2023

作者： Sridharan, Mohan Intelligent Robotics Lab School of Computer Science University of Birmingham United Kingdom

This paper describes an integrated architecture for robots that combines knowledge-based and data-driven methods for transparent reasoning, control, and learning. Specifically, the architecture builds on the principle of step-wise iterative refinement to support non-monotonic logical reasoning and probabilistic reasoning with tightly-coupled transition diagrams of the domain at different resolutions. Reasoning with prior domain knowledge and heuristic methods guide the interactive learning and revision of knowledge in the form of axioms governing change, predictive models controlling the robot's movement, and predictive models of the behavior of other agents. Furthermore, the interplay between these components is used to embed the principles of explainable agency, enabling a robot to provide on-demand relational descriptions of its decisions and beliefs in response to different types of questions. © 2023 Copyright for this paper by its authors.

关键词： Heuristic methods

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A study on Automated railway level crossing control system using FMCW radar for accident prevention 28

A study on Automated railway level crossing control system u...

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28th International Conference on Applied Electronics, AE 2023

作者： Greitans, Kristaps Maris Institute of Electronics and Computer Science Robotics and Machine Perceptions Laboratory Riga Latvia

ISBN: (纸本)9798350335538

This study paper explores the implementation of Intelligent Transportation Systems (ITS) in railway transportation, with a focus on level crossings, which have been a significant issue in railway safety. The paper discusses the limitations of current technologies such as laser technology and video surveillance and presents a novel solution utilizing a 79GHz Frequency Modulated Continuous Wave (FMCW) radar in combination with a CCTV camera for a dual sensor module. The FMCW radar is shown to be more accurate and cost-effective than previous technologies and can detect both large and small objects in the defined area at level crossings and difficult weather situations. The paper also presents a system architecture that takes into account vehicle detection time, which is crucial in reducing the risk of accidents and improving the safety of level crossings. This study aimed to compare the performance of different object detection modules under varying weather conditions. Three object detection methods were tested: a camera with the object detection algorithm Yolov5, FMCW radar with a built-in tracker, and manual observation. Four measurement sessions were conducted, each with a different combination of weather and time of day. The results showed that all modules performed similarly well under clear weather conditions, with the camera and radar modules detecting all vehicles approaching. However, under rainy and dark conditions, the radar module outperformed the camera, detecting 5 more objects. © 2023 IEEE.

关键词： Cameras

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MESSI: Task Mapping and Scheduling Strategy for FPGA-based Heterogeneous Real-Time Systems

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ACM Transactions on Design Automation of Electronic Systems 2025年第3期30卷 1-29页

作者： Ahmadi-Pour, Sallar Saha, Sangeet Mcdonald-Maier, Klaus Drechsler, Rolf Institute of Computer Science University of Bremen Faculty 3 Mathematics and Computer Science Bremen Bremen Germany Robotics and Embedded Systems Research Group University of Essex School of Computer Science and Electronic Engineering Colchester United Kingdom Cyber-Physical Systems DFKI Rheinland-Pfalz Kaiserslautern Germany

Continuous demands for improved performance within constrained resource budgets are driving a move from homogeneous to heterogeneous processing platforms for the implementation of today's Real-Time (RT) embedded systems. The applications executing on such systems are typically represented as a Precedence Task Graph (PTG), where a node represents a task or algorithm for one functionality and edges represent the complex interactions between multiple functionalities. Due to RT constraints, the task graph needs to be executed within a specified deadline. Although some existing studies have looked into solving this challenge, comprehensive studies that combine the theoretical features of RT task-graph mapping and scheduling with practical runtime architectural characteristics have mostly been ignored to date. Hence, in this article, we consider the challenge of scheduling an RT application modeled as a single PTG, with the objective of minimizing the overall execution time under Hardware (HW) resource and deadline constraints for heterogeneous Central Processing Unit (CPU) + Field Programmable Gate Array (FPGA) architectures. First, we introduce an optimal solution using Integer Linear Programming (ILP). However, this ILP-based optimal solution suffers from computational complexity and does not scale well even for moderately large problem sizes. Hence, we additionally propose heuristic algorithms for task mapping and scheduling. The efficiency of the proposed scheme, named MESSI, has been evaluated through experiments using PTG on a practical CPU+FPGA system regarding current technology restrictions. Our experiments demonstrate that performance gains of 55.6% and area usage reductions of 46.3% are possible compared to full Software (SW) and HW execution, respectively. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Integer programming

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Nonlinear Dynamic Inversion-based Motion Planning of a Floating Satellite Platform

Nonlinear Dynamic Inversion-based Motion Planning of a Float...

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AIAA science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Banerjee, Avijit Tevetzidis, Ilias Satpute, Sumeet Gajanan Nikolakopoulos, George Robotics and AI research group Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This article presents a nonlinear dynamic inversion-based motion plan for a levitating robotic satellite emulation platform. The frictionless motion of such a levitating platform has dynamic equivalency with a satellite’s realistic movement in space, thus evolving as an efficient demonstration tool as a hardware-in-loop satellite motion simulator. A brief design description of the emulation platform unified with various sensor and actuator units is presented, and an associated nonlinear mathematical model representing its coupled dynamic motion is described. The proposed control design architecture manipulates the associated nonlinear dynamics, which appear due to the coupling of translational and rotational movement of the robotic platform, thereby establishing an efficient trajectory tracking capability for various operating regions without the additional requirement of gain scheduling. In order to realize the control requirement through a set of ON-OFF thruster-based actuation units, which closely resembles the reaction control system of realistic satellite design, an optimal thrust allocation logic is proposed that accounts for various physical limitations of thrusters such as thrusters as its magnitude constraint and minimum on time. The efficacy of the proposed modelling and control scheme is experimentally validated in different realistic motion planning scenarios, such as point-to-point manoeuvres with terminal objectives and a superior path-following capability. The experimental studies are supported with related results. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Motion planning

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sEMG-based Sarcopenia risk classification using empirical mode decomposition and machine learning algorithms

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Mathematical Biosciences and Engineering 2024年第2期21卷 2901-2921页

作者： Kumar, Konki Sravan Lee, Daehyun Jamsrandoj, Ankhzaya Soylu, Necla Nisa Jung, Dawoon Kim, Jinwook Mun, Kyung Ryoul Center for Artificial Intelligence Korea Institute of Science and Technology Seoul Korea Republic of KHU-KIST Department of Converging Science and Technology Graduate School Kyung Hee University Seoul Korea Republic of Department of Human Computer Interface and Robotics Engineering University of Science and Technology Daejeon Korea Republic of Department of Computer Science Ozyegin University Istanbul Turkey

Early detection of the risk of sarcopenia at younger ages is crucial for implementing preventive strategies, fostering healthy muscle development, and minimizing the negative impact of sarcopenia on health and aging. In this study, we propose a novel sarcopenia risk detection technique that combines surface electromyography (sEMG) signals and empirical mode decomposition (EMD) with machine learning algorithms. First, we recorded and preprocessed sEMG data from both healthy and at-risk individuals during various physical activities, including normal walking, fast walking, performing a standard squat, and performing a wide squat. Next, electromyography (EMG) features were extracted from a normalized EMG and its intrinsic mode functions (IMFs) were obtained through EMD. Subsequently, a minimum redundancy maximum relevance (mRMR) feature selection method was employed to identify the most influential subset of features. Finally, the performances of state-of-the-art machine learning (ML) classifiers were evaluated using a leave-one-subject-out cross-validation technique, and the effectiveness of the classifiers for sarcopenia risk classification was assessed through various performance metrics. The proposed method shows a high accuracy, with accuracy rates of 0.88 for normal walking, 0.89 for fast walking, 0.81 for a standard squat, and 0.80 for a wide squat, providing reliable identification of sarcopenia risk during physical activities. Beyond early sarcopenia risk detection, this sEMG-EMD-ML system offers practical values for assessing muscle function, muscle health monitoring, and managing muscle quality for an improved daily life and well-being. © 2024 American Institute of Mathematical sciences. All rights reserved.

关键词： Empirical mode decomposition

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Design of an Automatic Price Tag System for Web-Based Retail Business 9

Design of an Automatic Price Tag System for Web-Based Retail...

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9th International Conference on Information Management and Technology, ICIMTech 2024

作者： Liawatimena, Suryadiputra Gunawan, Devina Bina Nusantara University Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Computer Science Deparment BINUS Graduate Program Master of Computer Science Jakarta11480 Indonesia Bina Nusantara University Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

Modern retail businesses face a significant challenge with the inefficiency of manually changing price labels on shelves. This manual process not only consumes valuable time and resources but also increases the likelihood of errors, leading to potential inaccuracies in pricing and a less streamlined shopping experience for customers. The proposed solution is the implementation of an Electronic Shelf Label (ESL) system that automatically displays the prices of goods on retail business shelves. This system connects a website (front end and back end) to e-paper via a Wi-Fi network and microcontroller, allowing retail business owners to update prices more easily. Additionally, buyers can search for desired items through the website. The results are the time to send data from the website to the e-paper, namely, to know the performance of the e-paper used. The average time required from 10 attempts to send data from the website to the e-paper is 20.935 seconds. Since the data is connected to the server and will be updated automatically, using this system will be more efficient than manually changing the price label, although it takes time to transfer data from the website to the e-paper. © 2024 IEEE.

关键词： Sales

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