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IEEE International Conference on Soft robotics (RoboSoft)

作者： Adira Colton Declan Fitzgerald Sunandita Sarker Noah Barnes Dheeraj Gandhi Miroslaw Janowski Jeremy D. Brown Joshua Kanter Laura Olivieri Mark Fuge Axel Krieger Ryan D. Sochol Department of Mechanical Engineering University of Maryland College Park MD USA Department of Mechanical Engineering Johns Hopkins University Baltimore MD USA Program in Image Guided Neurointerventions Department of Diagnostic Radiology and Nuclear Medicine University of Maryland School of Medicine Baltimore MD USA Children's National Heart Institute Children's National Hospital Washington DC USA Department of Pediatrics University of Pittsburgh School of Medicine Pittsburgh PA USA Maryland Robotics Center University of Maryland College Park MD USA Robert E. Fischell Institute for Biomedical Devices University of Maryland College Park MD USA

Patent Ductus Arteriosus (PDA) is a heart condition in which the ductus arteriosus-a blood vessel connecting the pulmonary artery to the aorta in a fetus-fails to undergo closure after birth. A PDA can be an important factor in neonates born with severe congenital heart disease (CHD) or born prematurely. With the advent of new intravascular stent technologies, treatments based on ductus arteriosus stenting can now be completed in many cases; however, difficulties remain in accessing the ductus arteriosus in small babies successfully using current guidewire-catheter systems. Recent developments for soft robotic endovascular instruments that leverage control schemes hold distinctive potential for addressing these access challenges, but such technologies are not yet at the sizes required for navigating neonatal vasculature safely and efficiently. In an effort to meet this clinical need, this work presents an approach for 3D printing 1.5 French (Fr) soft robotic guidewires that transition from straight to “S”-shaped configurations under the application of fluidic (e.g., pneumatic or hydraulic) loading. Two distinct dual-opposing segmented soft actuators, including a symmetric and asymmetric system design (both with heights of 2.5 mm), were 3D printed onto 1.1 Fr capillaries in 35–60 minutes via “Two-Photon Direct Laser Writing (DLW)”. Experimental results revealed that both designs not only withstood pressures of up to 550 kPa, but also exhibited increased opposing bending deformations-corresponding to decreased radii of curvature-with increasing applied pressure. In combination, this study serves as a critical foundation for next-generation fluidically actuated soft robotic guidewire-catheter systems for PDA interventions.

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A robust feedback-linearization MPC with artificial target for UGVs

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Mechatronics 2025年 110卷

作者： Bruno S.S. Pereira Tito L.M. Santos Andre G.S. Conceicao Postgraduate Program in Electrical and Computer Engineering Department of Electrical and Computer Engineering Federal University of Bahia Rua Aristides Novis 02 Salvador 40210-630 Bahia Brazil Department of Robotics SENAI-CIMATEC Av. Orlando Gomes 1845 Salvador 41650-010 Bahia Brazil

This paper proposes a new robust feedback-linearization MPC for a class of Unmanned Ground Vehicles. A robust MPC for trajectory tracking with an artificial target is combined with a suitable constraint mapping to ensure robust constraint satisfaction and recursive feasibility despite the effect of bounded disturbances. The artificial reference provides a potentially enlarged domain of attraction, and an analytical target modification is used to achieve the convergence of the tracking error to a minimal robust positively invariant set. The feedback-linearization trade-off concerning the transformed constraints is also analyzed. A case study demonstrating the control strategy’s performance is presented using the Clearpath Husky A200 UGV and the OptiTrack motion capture system.

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PrimA6D: Rotational Primitive Reconstruction for Enhanced and Robust 6D Pose Estimation

arXiv

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arXiv 2020年

作者： Jeon, Myung-Hwan Kim, Ayoung Department of the Robotics Program KAIST Daejeon Korea Republic of Department of Civil and Environmental Engineering KAIST Daejeon Korea Republic of

— In this paper, we introduce a rotational primitive prediction based 6D object pose estimation using a single image as an input. We solve for the 6D object pose of a known object relative to the camera using a single image with occlusion. Many recent state-of-the-art (SOTA) two-step approaches have exploited image keypoints extraction followed by PnP regression for pose estimation. Instead of relying on bounding box or keypoints on the object, we propose to learn orientation-induced primitive so as to achieve the pose estimation accuracy regardless of the object size. We leverage a Variational AutoEncoder (VAE) to learn this underlying primitive and its associated keypoints. The keypoints inferred from the reconstructed primitive image are then used to regress the rotation using PnP. Lastly, we compute the translation in a separate localization module to complete the entire 6D pose estimation. When evaluated over public datasets, the proposed method yields a notable improvement over the LINEMOD, the Occlusion LINEMOD, and the YCB-Video dataset. We further provide a synthetic-only trained case presenting comparable performance to the existing methods which require real images in the training phase. Copyright © 2020, The Authors. All rights reserved.

关键词： Machine learning

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Evaluation of usability and user interface design on Vokasiku mobile application using think aloud

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AIP Conference Proceedings 2024年第1期3047卷

作者： Andhini Rahma Santoso Meida Cahyo Untoro Sri Karnila Yutika Amelia Effendi Program Studi Teknik Informatika Institut Teknologi Sumatera Lampung Indonesia Institut Informatika dan Bisnis Darmajaya Lampung Indonesia Robotics and Artificial Intelligence Engineering Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya Indonesia

The Vokasiku is a mobile application that provides certification test services, online courses, and information about scholarships and job vacancies. The Vokasiku application was released on April 27, 2020. The users are still few and still need improvement. One of the important aspects of software is usability. Usability describes the perception of user experience related to effectiveness, ease, and satisfaction in using the product. The usability evaluation of the Vokasiku application is carried out using a user approach in the test, namely the Think Aloud method. Measuring the level of user satisfaction is done by using the Questionnaire for User Interaction Satisfaction (QUIS). After testing by the user, there are several errors in the application, so it is necessary to design a user interface to solve the problems experienced by the user. The user interface made is a high-fidelity prototype and front-end application. The design results will be re-evaluated until the usability value increases and no major problems are found.

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FluxProg 2.0 - Teaching Introductory programming Using Flowcharts with Real and Simulated Robots for The Brazilian robotics Olympiad (OBR)

FluxProg 2.0 - Teaching Introductory Programming Using Flowc...

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IEEE Latin American robotics Symposium, LARS

作者： João Alberto Fabro Matheus Biscaya Gutierrez Fernando Henrique Ratusznei Caetano DAINF - Academic Department of Informatica PPGCA - Graduate Program on Applied Computing LASER-Laboratory for Advanced Robotics and Embedded Systems UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Information Systems academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Computer Engineering academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

In this paper, an approach to aid in introductory programming courses is presented, focused on students that had never had any contact with computer programming. The approach, that was introduced in a previous paper [3], presents programming concepts using icons and “flowcharts”, and a 3D robotics simulator (CoppeliaSim), that has free educational use. This time, a real version of the simulated robot, built using Arduino and cheap, easily obtainable electronic components, is also presented. The programs to control the robot are developed by graphically constructing flowcharts on the visual editor, and then following the execution of programs using the simulated (or real) robot, step by step. This graphic program editor is named “FluxProg”, and its 2nd version is now available online, with new features comprising variables, arithmetic and logic expressions, thus providing a complete programming environment.

关键词： Flowcharts Visualization Three-dimensional displays Conferences Education Electronic components Robots

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SPriorSeg: Fast Road-Object Segmentation using Deep Semantic Prior for Sparse 3D Point Clouds

SPriorSeg: Fast Road-Object Segmentation using Deep Semantic...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ki-In Na Byungjae Park Jong-Hwan Kim Intelligent Robotics Research Division ETRI Daejeon Republic of Korea Robotics Program KAIST Daejeon Republic of Korea School of Mechanical Engineering KOREATECH Cheonan Chungnam Republic of Korea School of Electrical Engineering KAIST Daejeon Republic of Korea

ISBN: (数字)9781728185262

ISBN: (纸本)9781728185279

Detection and classification of road-objects like cars, pedestrians, and cyclists is the first step in autonomous driving. In particular, point-wise object segmentation for 3D point clouds is essential to estimate the precise appearances of the road-objects. In this paper, we propose SPriorSeg, a fast and accurate point-level object segmentation for point clouds by integrating the strengths of deep convolutional auto-encoder and region growing algorithm. Semantic segmentation using the light-weighted convolutional auto-encoder generates semantic prior by labeling a spherical projection image of point clouds pixel-by-pixel with classes of road-objects. The region growing algorithm achieves pixel-wise instance segmentation by taking into account semantic prior and geometric features between neighboring pixels. We build a well-balanced, pixel-level labeled dataset for all classes using 3D bounding boxes and point clouds from the KITTI object dataset. The dataset is employed to train our light-weighted neural network for semantic segmentation and demonstrate the performance of both semantic and instance segmentation of SPriorSeg.

关键词： Image segmentation Three-dimensional displays Laser radar Semantics Object segmentation Labeling Autonomous vehicles

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Non-invasive oscillatory neuromodulation of cortical vestibular functions: method and future implications

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Brain Stimulation 2023年第1期16卷 266-267页

作者： Giannotta, Alessandro Rossi, Simone Cinti, Alessandra Viberti, Francesca Benelli, Alberto Neri, Francesco De Monte, David Romanella, Sara Smeralda, Carmelo Donniacuo, Aniello Prattichizzo, Domenico Santarnecchi, Emiliano Mandalà, Marco Siena Brain Investigation & Neuromodulation Lab (Si-BIN Lab) Unit of Neurology and Clinical Neurophysiology Department of Medicine Surgery and Neuroscience University of Siena Italy Oto-Neuro-Tech Conjoined Lab Policlinico Le Scotte University of Siena Italy Otolaryngology Department of Medicine Surgery and Neuroscience Neurology and Clinical Neurophysiology Section University of Siena Italy Siena Robotics and Systems (SiRS) Lab Department of Information Engineering and Mathematics University of Siena Siena Italy Precision Neuroscience & Neuromodulation Program Massachusetts General Hospital Harvard Medical School Boston MA USA

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An Approach for 3D Microprinting Soft Robotic Surgical Tools at 1.5 French Length Scales for Endovascular Interventions

An Approach for 3D Microprinting Soft Robotic Surgical Tools...

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IEEE International Conference on Soft robotics (RoboSoft)

作者： Bailey M. Felix Olivia M. Young Jordi T. Andreou Nicholas Portwood Kieran J. Barvenik Noah Barnes Clifford R. Weiss Christopher R. Bailey Dheeraj Gandhi Miroslaw Janowski Jeremy D. Brown Eleonora Tubaldi Mark Fuge Axel Krieger Ryan D. Sochol Department of Bioengineering University of Maryland College Park MD USA Department of Mechanical Engineering University of Maryland College Park MD USA Department of Mechanical Engineering Johns Hopkins University Baltimore MD USA The Russell H. Morgan Department of Radiology and Radiological Science Division of Vascular and Interventional Radiology Johns Hopkins University School of Medicine Baltimore MD USA Department of Diagnostic Radiology and Nuclear Medicine Program in Image Guided Neurointerventions University of Maryland School of Medicine Baltimore MD USA Maryland Robotics Center University of Maryland College Park MD USA Robert E. Fischell Institute for Biomedical Devices University of Maryland College Park MD USA

A wide range of endovascular interventions rely on surgical tools such as guidewire-catheter systems for navigating through blood vessels to, for example, deliver embolic materials, stents, and/or therapeutic agents to target sites as well as biopsy tools (e.g., forceps and punch needles) for medical diagnostics. In response to the difficulties in maneuvering such endovascular instruments safely and effectively to access intended sites in the body, researchers have developed an array of soft robotic surgical tools that harness fluidic (e.g., pneumatic or hydraulic) actuation schemes to support on-demand steering and control. Despite considerable progress, scaling these tools down to the sizes required for medical procedures such as cerebral aneurysm treatment and liver chemoembolization have been hindered by manufacturing-induced constraints. To provide a pathway to overcome these miniaturization challenges, this work presents a novel additive manufacturing strategy for 3D microprinting integrated soft actuators directly atop multilumen microfluidic tubing via “Two-Photon Direct Laser Writing (DLW)”. As an exemplar, a two-actuator tip was 3D printed onto custom dual-lumen tubing-resulting in a system akin to a 1.5 French (Fr) guidewire with a steerable tip. Experimental results revealed independent actuator control via the discretized lumens, with tip bending of approximately 60° under input pressures of 130 kPa via hydraulic actuation. These results suggest that the presented strategy could be extended to achieve new classes of fluidically actuated soft robotic surgical tools at unprecedented length scales for emerging applications in minimally invasive surgery.

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Deceptive labeling: Hypergames on graphs for stealthy deception

arXiv

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arXiv 2020年

作者： Kulkarni, Abhishek N. Fu, Jie Leslie, Nandi O. Kamhoua, Charles A. Robotics Engineering Program Dept. of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States U.S. Army Research Laboratory

With the increasing sophistication of attacks on cyber-physical systems, deception has emerged as an effective tool to improve system security and safety by obfuscating information or providing misleading information. In this paper, we present a solution to the deceptive game in which a control agent is to satisfy a Boolean objective specified by a co-safe temporal logic formula in the presence of an adversary. The agent intentionally introduces asymmetric information to create payoff misperception. This is done by masking information about the logical formula satisfied given the outcome of the game. We introduce hypergames on graphs as a model to capture the asymmetrical information with one-sided payoff misperception. We present the solution of such a hypergame for synthesizing stealthy deceptive strategies that exploit adversary’s misperception. Specifically, deceptive sure winning and deceptive almost-sure winning strategies are developed by reducing the hypergame to a two-player game and one-player stochastic game with reachability objectives. Finally, an illustrative example is introduced to demonstrate the correctness of theory and proposed algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Game theory

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Reward engineering for Object Pick and Place Training

arXiv

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arXiv 2020年

作者： Nagpal, Raghav Krishnan, Achyuthan Unni Yu, Hanshen Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA01609 United States Mechanical Engineering Department Worcester Polytechnic Institute WorcesterMA01609 United States

—Robotic grasping is a crucial area of research as it can result in the acceleration of the automation of several Industries utilizing robots ranging from manufacturing to healthcare. Reinforcement learning is the field of study where an agent learns a policy to execute an action by exploring and exploiting rewards from an environment. Reinforcement learning can thus be used by the agent to learn how to execute a certain task, in our case grasping an object. We have used the Pick and Place environment provided by OpenAI’s Gym to engineer rewards. Hindsight Experience Replay (HER) has shown promising results with problems having a sparse reward. In the default configuration of the OpenAI baseline and environment the reward function is calculated using the distance between the target location and the robot end-effector. By weighting the cost based on the distance of the end-effector from the goal in the x,y and z-axes we were able to almost halve the learning time compared to the baselines provided by OpenAI, an intuitive strategy that further reduced learning time. In this project, we were also able to introduce certain user desired trajectories in the learnt policies (city-block / Manhattan trajectories). This helps us understand that by engineering the rewards we can tune the agent to learn policies in a certain way even if it might not be the most optimal but is the desired manner. Copyright © 2020, The Authors. All rights reserved.

关键词： End effectors

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