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LPL-VIO: monocular visual-inertial odometry with deep learning-based point and line features

Neural Computing and Applications 2024年第36期36卷 23061-23075页

作者： Liu, Changxiang Yang, Qinhan Yu, Hongshan Fu, Qiang Akhtar, Naveed College of Electrical and Information Engineering School of Robotics Quanzhou Institute of Industrial Design and Machine Intelligence Innovation Hunan University Changsha China School of Computing and Information Systems The University of Melbourne VIC Australia

Visual-inertial SLAM (VINS) has garnered substantial interest in the field of mobile robotics due to its robustness and cost-effectiveness. The incorporation of both point and line features in visual SLAM has shown significant performance improvements compared to relying solely on point features. Furthermore, learning-based features consistently outperform traditional hand-crafted features across a diverse range of tasks. Leveraging all these observations, we propose a novel deep learning technique, termed learning-based point and line visual-inertial odometry (LPL-VIO), which is aimed to enhance robustness and performance of traditional systems. LPL-VIO takes a 2-stage approach, including a deep learning front-end and a traditional nonlinear optimization back-end. In the first stage (front-end), we employ proposed networks for points and lines to extract and track deep learning-based point and line features in visual images, while implementing IMU preintegration. In the second stage (back-end), we adopt a sliding window strategy to tightly couple point and line re-projection errors with IMU preintegration residuals. These residuals are optimized using bundle adjustment for precise global pose estimation. Extensive experiments are conducted on both public EuRoC datasets and our own real-world dataset collected in challenging outdoor environments. Qualitative and quantitative results show that our method exhibits strong competitiveness compared with the existing point–line techniques, and outperforms the popular VINS-Mono. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： SLAM robotics

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designing Humanoids: How Robot Posture Influences Users' Perceived Safety in HRI 23

Designing Humanoids: How Robot Posture Influences Users' Per...

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23rd IEEE-RAS International Conference on Humanoid Robots, Humanoids 2024

作者： Nertinger, Simone Herzog, Olivia Mühlbauer, Anna Naceri, Abdeldjallil Haddadin, Sami Technical University of Munich Munich Institute of Robotics and Machine Intelligence Germany Technical University of Munich School of Engineering and Design Germany

ISBN: (纸本)9798350373578

In human-human interaction, posture serves as a critical non-verbal cue that subconsciously shapes first impressions and perceptions. Given the preference for anthropomorphism of robots acting in socially intensive situations such as caregiving, the influence of posture is expected to increase in interactions with humanoid robots. This study aims to identify the most preferred default position for the assistive humanoid robot GARMI, ensuring users' perceived safety in human-robot interaction (HRI). In a preliminary study, 30 participants evaluated ten different arm postures of the robot GARMI regarding their perceived discomfort. From these evaluations and direct rankings, three arm positions were selected for further analysis alongside the current default position in the virtual reality (VR) study. In this subsequent study, 50 participants assessed their perception of safety using both objective measures of comfort distance, grounded in proxemic theory, and two subjective measures, i.e., Godspeed questionnaire and Robotic Social Attribute Scale (RoSaS). The results indicate a significant impact of the robot's arm postures on users' perceived safety. A polite, butler-like posture is recommended as the default position, aligning with the role users typically attribute to the robot GARMI. © 2024 IEEE.

关键词： Anthropomorphic robots

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Mobile Preassembly Systems with Cooperative Dual-Arm Manipulation - A Concept for Industrial Applications in the Near Future 56

Mobile Preassembly Systems with Cooperative Dual-Arm Manipul...

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56th International Symposium on robotics, ISR Europe 2023

作者： Wittmann, Jonas Laile, Mathias Rainer, Johannes Fottner, Johannes Rixen, Daniel TUM School of Engineering and Design Munich Institute of Robotics and Machine Intelligence Technical University of Munich Germany TUM School of Engineering and Design Technical University of Munich Germany

ISBN: (纸本)9783800761418

In current manufacturing plants, autonomous guided vehicles (AGVs) are used for the transport of material. Our goal is to expand the use of AGVs, enabling them to perform complex handling and preassembly tasks. For a more efficient production, these tasks should be performed during transport. We propose a concept for a mobile dual-arm robot that we develop in a two-year project. Four modules are at the core of our solution: the Task Planner controls the high-level process, the Dual-Arm Planner enables coordinated and cooperative dual-arm manipulation, the Vision module detects objects and the Navigator controls the mobile base. Preliminary experiments demonstrate the navigation and manipulation capabilities of our robot. © VDE VERLAG GMBH Berlin Offenbach.

关键词： cooperating robots dual arm manipulation mobile manipulation

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The influence of an interactive user training on perceived safety in HRI 56

The influence of an interactive user training on perceived s...

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56th International Symposium on robotics, ISR Europe 2023

作者： Exeler, Sharon Nertinger, Simone Herzog, Olivia Naceri, Abdeldjallil Haddadin, Sami Munich Institute of Robotics and Machine Intelligence Technical University of Munich Germany School of Engineering and Design Technical University of Munich Germany

ISBN: (纸本)9783800761418

As robots become more prevalent in personal use, human-robot interaction (HRI) must also take lay users into account. To ensure acceptance by new user groups, HRI must be perceived as safe. Since experience is a crucial factor in the perception of safety, we suggest an interactive user training to be a promising method to facilitate HRI for laypersons. In this paper, we analyze the level of perceived safety of 16 participants before and after a 30-minute user training compared to 14 participants of a control group without getting any robot-specific training. Further, the applicability of eye gaze parameters, i.e., fixation count and fixation duration, is evaluated as an objective metric to measure perceived safety. Whereas no significant effect of training can be found, habituation shows to have an impact on perceived safety in HRI. Even though the variables fixation count and fixation duration cannot be used to measure one’s perceived safety, the results lead to a better understanding of the shortcomings of using gaze parameters in the analysis of perceived safety. © VDE VERLAG GMBH Berlin Offenbach.

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Event-enhanced synthetic aperture imaging

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Science China(Information Sciences) 2025年第3期68卷 388-390页

作者： Siqi LI Shaoyi DU Jun-Hai YONG Yue GAO Beijing National Research Center for Information Science and Technology School of SoftwareTsinghua University Institute for Brain and Cognitive Sciences Beijing Laboratory of Brain and Cognitive IntelligenceTsinghua University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and ApplicationsInstitute of Artificial Intelligence and Robotics Xi'an Jiaotong University

Synthetic aperture imaging(SAI) methods aim to see through dense occlusions and reconstruct the target scene behind occlusions. Traditional frame-based SAI methods,e.g., DeOccNet [1], take the occluded light field ima...

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A Multi-party Asymmetric Self-play Algorithm and Its Application in Multi-USV Adversarial Game Simulations 24

A Multi-party Asymmetric Self-play Algorithm and Its Applica...

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2024 International Conference on machine Learning, Pattern Recognition and Automation engineering, MLPRAE 2024

作者： Rao, Jinjun Wang, Cong Liu, Mei Lei, Jingtao Giernacki, Wojciech Department of Precision Mechanical Engineering School of Mechatronic Engineering and Automation Shanghai University China Institute of Robotics and Machine Intelligence Faculty of Automatic Control Robotics and Electrical Engineering Poznan University of Technology Poland

ISBN: (纸本)9798400709876

Aiming at the problem that the combination of self-play (SP) and deep reinforcement learning (DRL) only involves two-party games and the policy learning of each party is limited, a multi-party asymmetric self-play algorithm (MASP) is proposed. Firstly, by improving the ELO scoring system, the ELO scoring takes into account each party of the unmanned surface vehicle (USV) clusters, and the imbalance of the number of USV clusters, so that the frequency of exchanging strategies of all USV clusters in the confrontation process is equal. Secondly, it ensures that USV clusters have a balanced combat ability, and at the same time ensures that the combat ability of all parties is strong and weak and the gap is not too wide. In addition, the parameters are dynamically set to reduce the update frequency of the policy of the stronger party. The experimental results show that the MASP can make the USV clusters learn more effective policies, have a shorter game time, and obtain higher rewards and ELO scores in the simple 2v2 adversarial game scenario and the three-party game scenario of a warship escort mission. © 2024 ACM.

关键词： Deep reinforcement learning

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DEEPSPF: SPHERICAL SO(3)-EQUIVARIANT PATCHES FOR SCAN-TO-CAD ESTIMATION 12

DEEPSPF: SPHERICAL SO(3)-EQUIVARIANT PATCHES FOR SCAN-TO-CAD...

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12th International Conference on Learning Representations, ICLR 2024

作者： Salihu, Driton Misik, Adam Wu, Yuankai Patsch, Constantin Seguel, Fabian Steinbach, Eckehard Munich Institute of Robotics and Machine Intelligence Department of Computer Engineering Technical University of Munich School of Computation Information and Technology Germany Siemens Technology Germany

Recently, SO(3)-equivariant methods have been explored for 3D reconstruction via Scan-to-CAD. Despite significant advancements attributed to the unique characteristics of 3D data, existing SO(3)-equivariant approaches often fall short in seamlessly integrating local and global contextual information in a widely generalizable manner. Our contributions in this paper are threefold. First, we introduce Spherical Patch Fields, a representation technique designed for patch-wise, SO(3)-equivariant 3D point clouds, anchored theoretically on the principles of Spherical Gaussians. Second, we present the Patch Gaussian Layer, designed for the adaptive extraction of local and global contextual information from resizable point cloud patches. Culminating our contributions, we present Learnable Spherical Patch Fields (DeepSPF) - a versatile and easily integrable backbone suitable for instance-based point networks. Through rigorous evaluations, we demonstrate significant enhancements in Scan-to-CAD performance for point cloud registration, retrieval, and completion: a significant reduction in the rotation error of existing registration methods, an improvement of up to 17% in the Top-1 error for retrieval tasks, and a notable reduction of up to 30% in the Chamfer Distance for completion models, all attributable to the incorporation of DeepSPF. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Computer aided design

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Development and Evaluation of a Cost-effective IMU System for Gait Analysis: Comparison with Vicon and VideoPose3D Algorithms

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Current Directions in Biomedical engineering 2023年第1期9卷 254-257页

作者： Wilhelm, Nikolas Haddadin, Sami Micheler, Carina M. Lang, Jan J. Hinterwimmer, Florian Schaack, Victor Smits, Ricardo Burgkart, Rainer Department of Orthopedics and Sports Orthopedics Klinikum Rechts der Isar School of Medicine and Munich Institute of Robotics and Machine Intelligence Department of Electrical and Computer Engineering Technical University of Munich Munich Germany Munich Institute of Robotics and Machine Intelligence Department of Electrical and Computer Engineering Technical University of Munich Munich Germany Department of Orthopedics and Sports Orthopedics Klinikum Rechts der Isar School of Medicine Munich Germany

This study aimed to develop and evaluate a costeffective Inertial Measurement Unit (IMU) system for gait analysis, comparing its performance with the Vicon system and the VideoPose3D algorithm. The system comprises five calibrated sensors and a mobile app to measure lower body orientation during gait and stair climbing. Eight healthy participants were involved in the experiment, each performing ten repetitions to analyze hip and knee flexion angles. The IMU system demonstrated significantly lower mean square error than deep learning-based approaches and comparable results to the Vicon system, indicating its potential for clinical and research applications. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Gait analysis

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Intention-Oriented Fast Joint Prediction and Planning for Safe Driving 27

Intention-Oriented Fast Joint Prediction and Planning for Sa...

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27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024

作者： Zhang, Mingyi Xue, Jianru Lv, Chen Fang, Jianwu Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence China School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore

ISBN: (纸本)9798331505929

The primary challenges for Autonomous Vehicle (AV) navigation in complex scenarios are to effectively handle the interactions between the Ego-Vehicle (EV) and surrounding participants and generate safe yet non-conservative plans. Current approaches employ Planning-Informed Prediction (PIP) and Joint Prediction and Planning (JPP) to model these interactions. At the same time, information loss exists in PIP and JPP always ignores the intention interactions for a free space generation. To this end, this paper incorporates intention interactions into JPP, where a shared intention interaction module is adopted to both the planning and the prediction tasks via a cross-query mechanism, enabling the model to reduce the model size and accelerate inference speed. In contrast to previous methods that typically plan a single trajectory and result in conservative behaviors, we introduce a contingent-masked planner to balance the safety and efficiency, so as to fulfill the scene-level prediction and greatly improve computational efficiency. We evaluate our approach through closed-loop experiments on the CARLA longest6 and Town05 benchmarks, and faster inference speed and more robust performance against state-of-the-art methods. © 2024 IEEE.

关键词： Prediction models

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Real-Time UAV Fault Detection and Classification Using Measurement Data from the PADRE Database

Real-Time UAV Fault Detection and Classification Using Measu...

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2024 IEEE/SICE International Symposium on System Integration, SII 2024

作者： Puchalski, Radoslaw Giernacki, Wojciech Ha, Quang Institute of Robotics and Machine Intelligence University of Technology Faculty of Control Robotics and Electrical Engineering of Poznan Poznan Poland School of Electrical and Data Engineering University of Technology Sydney Faculty of Engineering and Information Technology UltimoNSW2007 Australia

ISBN: (纸本)9798350312072

The growing number of applications for unmanned aerial vehicles operating in close proximity to humans calls for strict safety requirements. To ensure reliability and safety, fast and effective diagnosis of possible drone faults is needed. In this paper, a study on the detection of damage to the propellers of a multirotor using inertial sensors was conducted. Measurement data from the publicly available PADRE repository were used. Frequency features and raw measurement data applicability were tested. Two different approaches to data processing during fault detection and classification were tested. The first is to analyze the signals after collecting the entire set of data needed for treatment by the neural network. The second approach processes the data after every single acquisition of sensor measurements. The performance results and processing time of each solution are recorded for analysis. By effectively selecting parameters of the proposed approaches, the processing time and accuracy of UAV fault classification can be significantly improved, as verified over different classes of propeller defects. Early fault detection is essential for safe operations of multirotor drones. © 2024 IEEE.

关键词： Drones

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