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

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FluxProg 2.0 - Teaching Introductory Programming Using Flowc...

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

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

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

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

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

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

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

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

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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

Reward engineering for Object Pick and Place Training

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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

Socially acceptable route planning and trajectory behavior analysis of personal mobility device for mobility management with improved sensing

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arXiv 2021年

作者： Mishra, Sumit Rajendran, Praveen Kumar Har, Dongsoo The Robotics Program Department of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Division of Future Vehicle Department of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of The CCS Graduate School of Green Transportation Korea Advanced Institute of Science and Technology Daejeon Korea Republic of

In urban cities, with increasing acceptability of shared spaces used by pedestrians and personal mobility devices (PMDs), there is need for pragmatic socially acceptable path planning and navigation management policies. Hence, we propose a socially acceptable global route planner and assess the legibility of the resulting global route. Our approach proposed for choosing global route avoids streets penetrating shared spaces and main routes with high probability of dense usage. The experimental study shows that socially acceptable routes can be effectively found with an average of 10 % increment of route length with optimal hyperparameters. This helps PMDs to reach the goal while taking a socially acceptable and safe route with minimal interaction of different PMDs and pedestrians. When PMDs interact with pedestrians and other types of PMDs in shared spaces, micro-mobility simulations are of prime usage for acceptable and safe navigation policy. Social force models being state of the art for pedestrian simulation are calibrated for capturing random movements of pedestrian behavior. Social force model with calibration can imitate the required behavior of PMDs in a pedestrian mix navigation scheme. Based on calibrated models, simulations on shared space links and gate structures are performed to assist policies related to deciding waiting and stopping time. Also, based on simulated PMDs interaction with pedestrians, location data with finer resolution can be obtained if the resolution of GPS sensor is 0.2 m or less. This will help in formalizing better modelling and hence better micro-mobility policies. Copyright © 2021, The Authors. All rights reserved.

关键词： Navigation

M2FN: Multi-step modality fusion for advertisement image assessment

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arXiv 2021年

作者： Park, Kyung-Wha Ha, Jung-Woo Lee, JungHoon Kwon, Sunyoung Kim, Kyung-Min Zhang, Byoung-Tak Interdisciplinary Program in Neuroscience Seoul National University Korea Republic of NAVER AI LAB NAVER CLOVA Statistics and Actuarial Science Soongsil University Korea Republic of School of Biomedical Convergence Engineering Pusan National University Korea Republic of Department of Computer Science and Engineering Seoul National University Korea Republic of Surromind Robotics

Assessing advertisements, specifically on the basis of user preferences and ad quality, is crucial to the marketing industry. Although recent studies have attempted to use deep neural networks for this purpose, these studies have not utilized image-related auxiliary attributes, which include embedded text frequently found in ad images. We, therefore, investigated the influence of these attributes on ad image preferences. First, we analyzed large-scale real-world ad log data and, based on our findings, proposed a novel multi-step modality fusion network (M2FN) that determines advertising images likely to appeal to user preferences. Our method utilizes auxiliary attributes through multiple steps in the network, which include conditional batch normalization-based low-level fusion and attention-based high-level fusion. We verified M2FN on the AVA dataset, which is widely used for aesthetic image assessment, and then demonstrated that M2FN can achieve state-of-the-art performance in preference prediction using a real-world ad dataset with rich auxiliary attributes. © 2021, CC BY-NC-SA.

关键词： Marketing

Secure-by-synthesis network with active deception and temporal logic specifications

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arXiv 2020年

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

This paper is concerned with the synthesis of strategies in network systems with active cyber deception. Active deception in a network employs decoy systems and other defenses to conduct defensive planning against the intrusion of malicious attackers who have been confirmed by sensing systems. In this setting, the defender's objective is to ensure the satisfaction of security properties specified in temporal logic formulas. We formulate the problem of deceptive planning with decoy systems and other defenses as a two-player games with asymmetrical information and Boolean payoffs in temporal logic. We use level-2 hypergame with temporal logic objectives to capture the incomplete/incorrect knowledge of the attacker about the network system as a payoff misperception. The true payoff function is private information of the defender. Then, we extend the solution concepts of ω-regular games to analyze the attacker's rational strategy given her incomplete information. By generalizing the solution of level-2 hypergame in the normal form to extensive form, we extend the solutions of games with safe temporal logic objectives to decide whether the defender can ensure security properties to be satisfied with probability one, given any possible strategy that is perceived to be rational by the attacker. Further, we use the solution of games with co-safe (reachability) temporal logic objectives to determine whether the defender can engage the attacker, by directing the attacker to a high-fidelity honeypot. The effectiveness of the proposed synthesis methods is illustrated with synthetic network systems with honeypots. Copyright © 2020, The Authors. All rights reserved.

关键词： Temporal logic