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IEEE/RSJ International Conference on intelligent Robots and Systems (IROS)

作者： M. R. Dindarloo A. S. Mirjalili S. A. Khalilpour R. Khorrambakht Stephan Weiss H. D. Taghirad Advanced Robotics and Automated Systems (ARAS) Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Tandon School of Engineering Control/Robotics Research Laboratory New York University Brooklyn NY Department of Smart Systems Technologies University of Klagenfurt Austria

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

The efficient operation of large-scale Cable-Driven Parallel Robots (CDPRs) relies on precise calibration of kinematic parameters and the simplicity of the calibration process. This paper presents a graph-based self-calibration framework that explicitly addresses cable sag effects and facilitates the calibration procedure for large-scale CDPRs by only relying on internal sensors. A unified factor graph is proposed, incorporating a catenary cable model to capture cable sagging. The factor graph iteratively refines kinematic parameters, including anchor point locations and initial cable length, by considering jointly onboard sensor data and the robot’s kineto-static model. The applicability and accuracy of the proposed technique are demonstrated through Finite Element (FE) simulations, on both large and small-scale CDPRs subjected to significant initialization perturbations.

关键词： Meters Accuracy Perturbation methods Kinematics Robot sensing systems End effectors Software Calibration Sensors Finite element analysis

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Graph-Based Collision Avoidance Algorithm Among Swarm Agents

Graph-Based Collision Avoidance Algorithm Among Swarm Agents

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International Symposium on electrical and Electronics engineering (ISEEE)

作者： Akif Durdu Mesut Tuncer Berat Yıldız Department of Electrical and Electronics Engineering Robotics Automation Control Laboratory (RAC-LAB) Konya Technical University Konya Turkiye Department of Computer Engineering Robotics Automation Control Laboratory (RAC-LAB) Konya Technical University Konya Turkiye Department of Electrical and Electronics Engineering Karamanoglu Mehmetbey University Karaman Turkiye

More than one homogenous or heterogenous type unmanned vehicle can work in a coordinated manner and perform large-scale swarm tasks (firefighting, search and rescue, mapping, and military operations, etc.) efficiently in a shorter time by sharing tasks. Collision of these vehicles is among the most significant problems encountered during their work. The crash of the vehicles causes the vehicles to be out of duty and, accordingly, to the mission’s failure. In this study, Quadrotor-type UAVs used as agents can go to any target point by receiving location, speed, and compass information with GPS and IMU sensors. In the application, the agents’ locations were kept and updated in a list in pairs, similar to the traversing process in the Optimized Bubble Sort Algorithm. The projections of the velocity vectors on the agents’ axis (local) on a single coordinate plane are taken to determine the collision situation between these two agents that are traveling instantaneously. These global velocity vectors, whose projections are taken, are re-projected to the edge formed by these two agents in the graph and then subtracted from each other. Suppose the size of the vector is greater than the distance between two agents obtained by any GPS distance algorithm (Pythagoras, Haversine, etc.). In this case, collision is detected, and the separation process is activated. Separation is the process of advancing one agent in the opposite direction of the other until a minimum safe distance is achieved, where one agent entered by the user will not affect the other. Once the separation is complete, the agent moves to the final destination point.

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FROST: Fusion and Multimodal 3D Reconstruction of Icy Surfaces for Robotic Exploration

FROST: Fusion and Multimodal 3D Reconstruction of Icy Surfac...

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Computational Intelligence on engineering/Cyber Physical Systems Companion (CIES Companion), IEEE Symposium on

作者： Huy Xuan Pham Erdal Kayacan Department of Electrical and Computer Engineering Artificial Intelligence in Robotics Laboratory (Air Lab) Aarhus University Aarhus C Denmark Automatic Control Group (RAT) Paderborn University Paderborn Germany

ISBN: (数字)9798331508494

ISBN: (纸本)9798331508500

Three-dimensional (3D) reconstruction serves as a cornerstone in various robotic applications, playing critical roles in scene understanding and navigation. Traditionally, LiDAR has been instrumental in generating precise point clouds of the environment, providing essential data for these applications. However, the efficacy of LiDAR sensors is significantly hindered in challenging conditions, such as the presence of water or icy surfaces. The complex interplay between laser beams and icy or non-ideal surfaces can result in signal degradation, distortion, or even complete signal loss, adversely affecting the accuracy and reliability of the 3D reconstruction process. The reflective and refractive properties of ice, along with its variable surface conditions, present challenges that traditional LiDAR sensors struggle to address. This paper proposes a diverse dataset to facilitate a multimodal approach for reconstructing icy surfaces using various sensors. A preliminary study based on this dataset demonstrates the feasibility of combining the geometric surface obtained from consecutive LiDAR scans with reconstructed meshes from visual cameras. The integration of distinct data sources has the potential to improve the robustness of reconstruction algorithms in diverse scenarios. The dataset can be downloaded at https://***/records/13862009.

关键词： Point cloud compression Surface reconstruction Laser radar Three-dimensional displays Navigation Ice Robustness Laser beams Image reconstruction Surface treatment

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How to Swarm: Entropy-Based Model Parameter Analysis

How to Swarm: Entropy-Based Model Parameter Analysis

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IEEE Southeastcon

作者： Nathan Rayon Stefan Wheeless Gabriel Broom Hakki Erhan Sevil Department of Computer Science University of West Florida (UWF) Pensacola FL USA Department of Electrical and Computer Engineering University of West Florida (UWF) Pensacola FL USA Department of Intelligent Systems and Robotics University of West Florida (UWF) Pensacola FL USA

In this study, we implemented our entropy-based swarm model to an autonomous waypoint navigation application for a group of multi-rotor Unmanned Aerial Vehicles (UAVs) through a set course in free space. Multi-UAVs of multiple group sizes were run with variations in parameters, and the path lengths traveled were measured to determine the most efficient configurations, and we investigated the impact of varying parameters on the swarm behavior performance. The simulation of the UAV kinematics and environment was performed in AirSim. The results show that the swarm model with different parameter setup operates successfully and the effects of the parameter selection on our multi-UAV swarm model are discussed.

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Self-Supervised Reflective Learning Through Self-Distillation and Online Clustering for Speaker Representation Learning

IEEE Transactions on Audio, Speech and Language Processing

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IEEE Transactions on Audio, Speech and Language Processing 2025年 33卷 1535-1550页

作者： Danwei Cai Zexin Cai Ze Li Ming Li Department of Electrical and Computer Engineering Duke University Durham NC USA Suzhou Municipal Key Laboratory of Multimodal Intelligent Systems Digital Innovation Research Center Duke Kunshan University Kunshan China School of Computer Science Wuhan University Wuhan China

Speaker representation learning is crucial for voice recognition systems, with recent advances in self-supervised approaches reducing dependency on labeled data. Current two-stage iterative frameworks, while effective, suffer from significant computational overhead due to repeated rounds of clustering and training. They also struggle with noisy pseudo labels that can impair model learning. This paper introduces self-supervised reflective learning (SSRL), an improved framework that addresses these limitations by enabling continuous refinement of pseudo labels during training. Through a teacher-student architecture and online clustering mechanism, SSRL eliminates the need for iterative training rounds. To handle label noise, we incorporate noisy label modeling and pseudo label queues that maintain temporal consistency. Experiments on VoxCeleb show SSRL's superiority over current two-stage iterative approaches, surpassing the performance of a 5-round method in just a single training round. Ablation studies validate the contributions of key components like noisy label modeling and pseudo label queues. Moreover, consistent improvements in pseudo labeling and the convergence of cluster counts demonstrate SSRL's effectiveness in deciphering unlabeled data. This work marks an important advancement in efficient and accurate self-supervised speaker representation learning through the novel reflective learning paradigm.

关键词： Training Representation learning Iterative methods Noise Adaptation models Noise measurement Predictive models Speech processing Robustness Convergence

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SVM-based Extended Kalman Filter State Estimation of Biped Robot

SVM-based Extended Kalman Filter State Estimation of Biped R...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Gao, Chengzhi Xie, Ye Zhu, Shiqiang Huang, Guanyu Kong, Lingyu Xie, Anhuan Gu, Jianjun Zhang, Dan Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Zhejiang University Zhejiang Hangzhou311100 China York University North YorkM3J 1P3 Canada Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

At present, more and more attention has been paid to the exploration of biped robots. As the precondition of biped stable walking, the state estimation of robot has also received the attention of many experts. Biped robot has special motion characteristics, has a hybrid dynamic system and belongs to a floating base, so it must obtain the contact information of two feet before realizing the motion state estimation of the robot. The contribution of this paper is to introduce soft support vector machine to detect contact phase. This method based on support vector machine (SVM) eliminates the need for force sensors on two feet because they are vulnerable to the impact between the foot and the contact surface. In addition, precise dynamic modeling is not required. Furthermore, this paper uses SVM to obtain the touchdown information, and proposes a state estimation method using extended Kalman filter to combine motion estimation with IMU data. Finally, the touchdown detection algorithm and the state estimation algorithm are verified through experiments, and the accuracy and feasibility of the SVM method are proved through the touchdown detection experiments. Based on this, the full state estimation of the robot is realized through the state estimation experiments. © 2022 IEEE.

关键词： State estimation

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Doppler-Based Satellite-Borne Localization of Ground Electromagnetic Interferer

Doppler-Based Satellite-Borne Localization of Ground Electro...

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IEEE Conference on Aerospace

作者： Yimin D. Zhang Yanwu Ding Khanh Pham Dan Shen Genshe Chen Department of Electrical and Computer Engineering Temple University Philadelphia PA Department of Electrical and Computer Engineering Wichita State University Wichita KS Air Force Research Laboratory Kirtland Air Force Base NM Intelligent Fusion Technology Inc. Germantown MD

Accurate localization and effective suppression of ground electromagnetic interference (EMI) signals are critical to maintaining uninterrupted satellite operations and the quality of services. For EMI sources emitting certain waveforms, such as continuous-wave or phase shift keying signals, their localization exploiting the time-varying Doppler signature due to satellite motion is an attractive approach. The high-speed motions and complicated orbits of satellites render the Doppler signatures varying with a high dynamic range and nonlinear instantaneous frequency signatures. As such, their processing requires high complexity which may not be practical for real-time processing, particularly for on-orbit satellite implementation for which the computational capability is highly limited. In this paper, we develop a low-complexity approach to iteratively estimate both the location and Doppler signatures of EMI signals. We introduce virtual ground references around the sensed scenarios and compute the Doppler difference between the measured results and the predicted ones for the virtual ground reference positions. By considering such Doppler difference in lieu of the Doppler frequencies, the Doppler dynamic range and the slope of the instantaneous frequency signatures are reduced to facilitate more effective time-frequency analysis and EMI source localization. We further consider the use of multiple virtual ground references for performance improvement, and a simple EMI localization approach is proposed through the interpolation of the Doppler difference frequencies observed at these virtual references. The effectiveness of the proposed approach is verified using simulation results.

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An Efficient Model-Based Approach on Learning Agile Motor Skills without Reinforcement

arXiv

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arXiv 2024年

作者： Shi, Haojie Li, Tingguang Zhu, Qingxu Sheng, Jiapeng Han, Lei Meng, Max Q.-H. Tencent Robotics X China The Chinese University of Hong Kong Hong Kong Shenzhen Key Laboratory of Robotics Perception and Intelligence The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China The Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong The Department of Electrical and Computer Engineering The University of Alberta Canada

Learning-based methods have improved locomotion skills of quadruped robots through deep reinforcement learning. However, the sim-to-real gap and low sample efficiency still limit the skill transfer. To address this issue, we propose an efficient model-based learning framework that combines a world model with a policy network. We train a differentiable world model to predict future states and use it to directly supervise a Variational Autoencoder (VAE)-based policy network to imitate real animal behaviors. This significantly reduces the need for real interaction data and allows for rapid policy updates. We also develop a high-level network to track diverse commands and trajectories. Our simulated results show a tenfold sample efficiency increase compared to reinforcement learning methods such as PPO. In real-world testing, our policy achieves proficient command-following performance with only a two-minute data collection period and generalizes well to new speeds and paths. Copyright © 2024, The Authors. All rights reserved.

关键词： Efficiency

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A Multi-stage Precision Landing Method for Autonomous eVTOL Based on Multi-marker Joint Localization

A Multi-stage Precision Landing Method for Autonomous eVTOL ...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Xiang, Senwei Ye, Minxiang Zhu, Shiqiang Gu, Jason Xie, Anhuan Men, Zehua Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Lab Hangzhou310000 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

Electric vertical takeoff and landing aircraft (eVTOL) has drawn more and more attention from home and abroad in recent years. It is believed autonomous eVTOL will create a new era of Urban Air Mobility (UAM) and Advanced Air Mobility (AAM). To autonomous eVTOL, precision landing is an extremely critical operation for it directly affects flight safety. In this paper, we analyze the special issues an eVTOL will encounter when it lands in the UAM applications. A multi-stage precision landing method based on multi-marker joint localization is proposed accordingly. Our method contains three key elements: a compatible vertiport with multiple visual markers;an accurate, fast detection and localization algorithm for the vertiport and a multi-stage landing strategy. We implement our method on an eVTOL prototype named ZJ-Copter developed by Zhejiang Lab. A series of real-world experiments have been conducted to validate the effectiveness and accuracy of the proposed method. Experiment results show that our method works well in real-world scenarios for autonomous eVTOL without GPS signal during landing process. The positioning accuracy is less than 0.1m (altitude © 2022 IEEE.

关键词： Aircraft landing

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An Isomerism Learning Model to Solve Time-Varying Problems Through intelligent Collaboration

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1772-1774页

作者： Zhihao Hao Guancheng Wang Bob Zhang Leyuan Fang Haisheng Li the Department of Computer and Information Science University of MacaoMacao 999078China the School of Data Science the Chinese University of Hong KongShenzhen 518172 Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen 518000 China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China IEEE the College of Electrical and Information Engineering Hunan UniversityChangsha 410082 the Peng Cheng Laboratory Shenzhen 518000China the Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business UniversityBeijing 100048 the School of Computer Science and Engineering Beijing Technology and Business UniversityBeijing 100048China

Dear Editor,This letter deals with a solution for time-varying problems using an intelligent computational(IC)algorithm driven by a novel decentralized machine learning approach called isomerism *** order to meet the challenges of the model’s privacy and security brought by traditional centralized learning models,a private permissioned blockchain is utilized to decentralize the model in order to achieve an effective coordination,thereby ensuring the credibility of the overall model without exposing the specific parameters and solution process.

关键词： ism thereby letter

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