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Autonomous Ultrasound Scanning using Bayesian Optimization and Hybrid Force Control 39

Autonomous Ultrasound Scanning using Bayesian Optimization a...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Goel, Raghavv Abhimanyu, Fnu Patel, Kirtan Galeotti, John Choset, Howie Carnegie Mellon Univ Inst Robot Sch Comp Sci 5000 Forbes Ave Pittsburgh PA 15213 USA Carnegie Mellon Univ Dept Mech Engn 5000 Forbes Ave Pittsburgh PA 15213 USA

ISBN: (纸本)9781728196817

Ultrasound scanning is an imaging technique that aids medical professionals in diagnostics and interventional procedures. However, a trained human-in-the-loop (HITL) with a radiologist is required to perform the scanning procedure. We seek to create a novel ultrasound system that can provide imaging in the absence of a trained radiologist, say for patients in the field who suffered injuries after a natural disaster. One challenge of automating ultrasound scanning involves finding the optimal area to scan and then performing the actual scan. This task requires simultaneously maintaining contact with the surface while moving along it to capture high quality images. In this work, we present an automated Robotic Ultrasound System (RUS) to tackle these challenges. Our approach introduces a Bayesian Optimization framework to guide the probe to multiple points on the unknown surface. Our proposed framework collects the ultrasound images as well as the pose information at every probed point to estimate regions with high vessel density (information map) and the surface contour. Based on the information map and the surface contour, an area of interest is selected for scanning. Furthermore, to scan the proposed region, a novel 6-axis hybrid force-position controller is presented to ensure acoustic coupling. Lastly, we provide experimental results on two different phantom models to corroborate our approach.

关键词： Ultrasonic imaging Phantoms Human in the loop Bayes methods Task analysis Probes Optimization

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A Comparative Analysis of Reactive Collision Avoidance methods on Uncrewed Surface Vehicles in Complex and Uncertain Environments

A Comparative Analysis of Reactive Collision Avoidance Metho...

引用

2023 Australasian conference on robotics and automation, ACRA 2023

作者： Gleeson, Jordan Dunbabin, Matthew Queensland University of Technology Queensland Australia

In this work, we robustly compare the performance of popular collision avoidance approaches for Uncrewed Surface Vehicles (USVs) in the context of adhering to the international Regulations for Preventing Collisions at Sea (COLREGs). USVs have many applications across maritime sectors. To successfully operate on congested waterways, a collision avoidance algorithm should safely plan around static and dynamic obstacles whilst abiding by the COLREGs. In this paper, we compare the performance of rule-based, velocity obstacle, and artificial potential field methods using a maritime-focused physics-based simulation environment. This paper presents novel extensions to the aforementioned collision avoidance methods that are tailored to the practical scenarios presented in this study. A performative evaluation of each method was conducted in the context of the COLREGs, with increasing levels of scenario complexity (number of vehicles) and sensor uncertainty (estimated positions). The results first highlight the more robust performance of the Velocity Obstacle collision avoidance method in dynamic environments. Secondly, poor performance under large uncertainty highlights the need for the inherent integration of uncertainty and risk into collision avoidance algorithms, particularly when other vessels are non-compliant or poorly observed. © 2023 Australasian robotics and automation Association. All rights reserved.

关键词： Collision avoidance

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Explore-Bench: Data Sets, Metrics and Evaluations for Frontier-based and Deep-reinforcement-learning-based Autonomous Exploration 39

Explore-Bench: Data Sets, Metrics and Evaluations for Fronti...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Xu, Yuanfan Yu, Jincheng Tang, Jiahao Qiu, Jiantao Wang, Jian Shen, Yuan Wang, Yu Yang, Huazhong Tsinghua Univ Dept Elect Engn Beijing Peoples R China

ISBN: (纸本)9781728196817

Autonomous exploration and mapping of unknown terrains employing single or multiple robots is an essential task in mobile robotics and has therefore been widely investigated. Nevertheless, given the lack of unified data sets, metrics, and platforms to evaluate the exploration approaches, we develop an autonomous robot exploration benchmark entitled Explore-Bench. The benchmark involves various exploration scenarios and presents two types of quantitative metrics to evaluate exploration efficiency and multi-robot cooperation. Explore-Bench is extremely useful as, recently, deep reinforcement learning (DRL) has been widely used for robot exploration tasks and achieved promising results. However, training DRL-based approaches requires large data sets, and additionally, current benchmarks rely on realistic simulators with a slow simulation speed, which is not appropriate for training exploration strategies. Hence, to support efficient DRL training and comprehensive evaluation, the suggested Explore-Bench designs a 3-level platform with a unified data flow and 12x speed-up that includes a grid-based simulator for fast evaluation and efficient training, a realistic Gazebo simulator, and a remotely accessible robot testbed for high-accuracy tests in physical environments. The practicality of the proposed benchmark is highlighted with the application of one DRL-based and three frontier-based exploration approaches. Furthermore, we analyze the performance differences and provide some insights about the selection and design of exploration methods. Our benchmark is available at https: //github. com/efc-robot/Explore-Bench.

关键词： Training Measurement automation Design methodology Benchmark testing Data models Task analysis

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An Evaluation of methods for Assessing Robot Kinematic Model Accuracy in the Presence of Noise 20

An Evaluation of Methods for Assessing Robot Kinematic Model...

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IEEE 20th international conference on automation Science and Engineering (CASE)

作者： Woodside, Mitchell R. Bazzoli, Patrick Olubodun, Philip A. Nisbett, J. Adam Xiao, Guixiu Bristow, Douglas A. Missouri Univ Sci & Engn Dept Mech & Aerosp Engn Rolla MO 65409 USA NIST Cognit & Collaborat Syst Grp Gaithersburg MD 20899 USA

ISBN: (纸本)9798350358513;9798350358520

While there are many works developing methods for modeling and calibrating robot kinematics, assessing the accuracy of those models has received little attention. However, accuracy assessment is critically important for applications where the robot must operate with absolute accuracy over a large region of workspace, such as in robotic machining. When the model of such a system is well calibrated, the remaining deterministic error can be quite complex, owing to complicated gearing errors, deformations, and quasi-static thermal changes. Locating the largest deterministic error requires an exploration over the workspace, but assessing the largest error is complicated by repeatability error and measurement noise. How then to assess the largest error from such a measurement set? This paper evaluates the efficacy of two conventional methods, maximum measured error and outlier rejection, and a novel method based on model invalidation that uses a hypothesis testing framework. A machining robot is used to develop a numerical study for evaluation of these methods under differing magnitude of measurement noise. A high-order kinematic model of the robot is constructed as used as the true robot kinematics, and the workspace for that system is used as the region of interest. A best-fit Denavit-Hartenberg (DH) model is used as the model whose accuracy is to be measured. The study shows that the largest deterministic error can be difficult to locate with just a few percent of points approaching the defining accuracy limit. As expected, the largest measured error provides a poor (over)estimate of the error as noise is increased, but outlier rejection can be equally as bad as rare large deterministic errors can be easily mistaken for lowprobability large random error. The novel model invalidation method, however, performs well across all noise levels.

关键词： Random errors

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Understanding Xacro Misunderstandings 39

Understanding Xacro Misunderstandings

引用

IEEE international conference on robotics and automation (ICRA)

作者： Albergo, Nicholas Rathi, Vivek Ore, John-Paul North Carolina State Univ Dept Comp Sci Raleigh NC 27695 USA North Carolina State Univ Elect & Comp Engn Dept Raleigh NC 27695 USA

ISBN: (纸本)9781728196817

The Xacro XML macro language can be used to augment the Universal Robot Description Format (URDF) and is part of a critical toolchain from geometric representations to simulation, visualization, and system execution. However, members of the robotics community, especially newcomers, struggle to troubleshoot and understand the interplay between systems and the Xacro preprocessing pipeline. To better understand how system developers struggle with Xacros, we manually examine 712 Xacro-related questions from the question and answer site *** and find Xacro misunderstandings fit into eight key categories using a systematic, qualitative approach called Open Coding. By examining the 'tags' applied to questions, we further find that Xacro problems manifest in a befuddlingly broad set of contexts. This hinders onboarding and complicates system developers' understanding of representations and tools in the Robot Operating System. We aim to provide an empirical grounding that identifies and prioritizes impediments to users of open robotics systems, so that tool designers, teachers, and robotics practitioners can devise ways of improving robot software tooling and education.

关键词： Software Tools for Robot Programming methods and Tools for Robot System Design Software-Hardware Integration for Robot Systems

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Centroidal Aerodynamic Modeling and Control of Flying Multibody Robots 39

Centroidal Aerodynamic Modeling and Control of Flying Multib...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Hui, Tong Paolino, Antonello Nava, Gabriele L'Erario, Giuseppe Di Natale, Fabio Bergonti, Fabio Braghin, Francesco Pucci, Daniele Ist Italiano Tecnol Artificial & Mech Intelligence Genoa Italy Politecn Milan Dept Mech Engn Milan Italy Univ Manchester Sch Comp Sci Manchester Lancs England Univ Napoli Federico II Dept Ind Engn Naples Italy

ISBN: (纸本)9781728196817

This paper presents a modeling and control framework for multibody flying robots subject to non-negligible aero-dynamic forces acting on the centroidal dynamics. First, aero-dynamic forces are calculated during robot flight in different operating conditions by means of Computational Fluid Dynamics (CFD) analysis. Then, analytical models of the aerodynamics coefficients are generated from the dataset collected with CFD analysis. The obtained simplified aerodynamic model is also used to improve the flying robot control design. We present two control strategies: compensating for the aerodynamic effects via feedback linearization and enforcing the controller robustness with gain-scheduling. Simulation results on the jet-powered humanoid robot iRonCub validate the proposed approach.

关键词： Analytical models Shape Computational fluid dynamics Computational modeling Simulation Aerodynamics Robustness

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An Occlusion Removal Approach for Surgical Instruments Based on the Optical Flow-Guided models 21

An Occlusion Removal Approach for Surgical Instruments Based...

引用

21st IEEE international conference on Mechatronics and automation (IEEE ICMA)

作者： Wang, Wanqing Liu, Fucheng Hao, Jianxiong Shi, Chaoyang Tianjin Univ Sch Mech Engn Tianjin 300072 Peoples R China

ISBN: (纸本)9798350388084;9798350388077

Surgical instrument removal has become increasingly necessary to provide precise information during intraoperative execution. Occlusions in the endoscopic view caused by interactions between surgical instruments and organs can impede a surgeon's ability to accurately assess internal tissue, as well as certain computer-assisted surgical algorithms that rely on endoscopic images. This work demonstrates a novel application of removing surgical instruments from endoscopic video utilizing flow-guided image inpainting methods. A comparative experiment was conducted to validate the advantages of the improved method. Additionally, two task-based experiments including target tracking and image fusion experiments were conducted to further demonstrate its potential as a preprocessing step for other visual algorithms.

关键词： Surgical instruments removal Video inpainting Flow-guided model

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UAV Wheat Rust Detection based on FasterNet-YOLOv8

UAV Wheat Rust Detection based on FasterNet-YOLOv8

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2023 IEEE international conference on robotics and Biomimetics, ROBIO 2023

作者： Liu, Huaiyu Zhang, Yueyuan Liu, Shuguang Zhao, Mengyang Sun, Lining Soochow University School of Mechanical and Electrical Engineering Department of Automation Engineering Suzhou215137 China Soochow University Robotics and Microsystems Center School of Mechanical and Electrical Engineering Suzhou215137 China

ISBN: (纸本)9798350325706

This paper introduces a UAV-based wheat rust detection system employing deep learning techniques. To address the limitations of traditional wheat rust disease detection methods, such as time and labor-intensive processes, lack of real-time monitoring, and excessive pesticide usage, In this paper, the YOLOv8 algorithm, representing the forefront of object detection methods is chosen for UAV wheat rust detection. We train the model on a prepared dataset. Subsequently, we evaluated 5 models, including YOLOv5, and YOLOv8, at two different scales (n, s) based on average precision (mAP@.5), precision, recall, and FPS. The experimental outcomes establish the superiority of the enhanced FasterNet-YOLOv8 model over YOLOv8 and YOLOv5 across all metrics, encompassing detection accuracy and processing speed. These findings affirm the viability of our suggested model within the UAV wheat rust monitoring system and underscore the efficacy of the model enhancements. © 2023 IEEE.

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A model for optimizing the identification of process variants in Robotic Process automation 10

A model for optimizing the identification of process variant...

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10th international conference on Social Networks Analysis, Management and Security, SNAMS 2023

作者： Mohammadi, Fatemeh Vanani, Iman Raeesi University of Milan Departement of Computer Science Milano Italy Allameh Tabataba'i University Departement of Management and Accounting Tehran Iran

ISBN: (纸本)9798350318906

This research focuses on enhancing the identification of process variants in robotic process automation (RPA) by using process mining techniques. It introduces a novel approach for identifying RPA automation candidates, combining diverse data and process science techniques not explored previously. The study analyzed event logs from the Figshare database, applying various process mining methods to evaluate processes and identify RPA-suitable activities. The proposed model's efficiency was measured against two baseline models, showing superior performance in multiple criteria. © 2023 IEEE.

关键词： robotics

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A FIWARE based Input-Output Supervisor Control Implementation 29

A FIWARE based Input-Output Supervisor Control Implementatio...

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29th IEEE international conference on Emerging Technologies and Factory automation, ETFA 2024

作者： Menexis, Antonios N. Fragkoulis, Dimitrios G. Koumboulis, Fotis N. Skarpetis, Michael G. School of Science National & Kapodistrian University of Athens Robotics Automatic Control and Cyber-Physical Systems Laboratory Department of Digital Industry Technologies Euripus Campus Euboea 34400 Greece

ISBN: (纸本)9798350361230

In this paper, a FIWARE based control implementation framework for supervisory control of inputoutput models, in Discrete Event System (DES) form, will be introduced, through the case study of an industrial product transfer system having a parametric number of conveyor belts. Each conveyor belt has an actuator (motor) for the belt's clockwise move and a sensor for the detection of the presence of a product. The model of each actuator and the model of each sensor of the belt are expressed in DES form. The input-output relation between consecutive conveyor belts is formally expressed. The satisfactory cooperation between consecutive conveyor belts has been guaranteed by developing a set of two types of supervisors for each cooperative pair. The actuators and the sensors of each belt have been described as smart data models. Finally, an implementation of the proposed supervisor scheme in FIWARE has been proposed. © 2024 IEEE.

关键词： Cloud Computing Smart Data models Supervisory Control

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