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IEEE International Conference on robotics and Automation (ICRA)

作者： Lening Li Jie Fu Robotics Engineering Program Worcester Polytechnic Institute Worcester MA US

In this paper, we propose a sampling-based policy iteration for optimal planning under temporal logic constraints. The method integrates approximate optimal control, importance sampling, and formal methods. For a subclass of linear temporal logic, the planning problem is transformed to an optimal control problem for a hybrid system where discrete transitions are triggered by linear time events in temporal logic. Instead of solving the Hamilton-Jacobi-Bellman equation, we use policy function approximation to reduce the problem into a search of an optimal weight vector that parametrizes the near-optimal policy for given bases. Then, we incorporate Model Reference Adaptive Search - an importance sampling-based optimization algorithm to perform a sample-efficient search within the parameter space of policy function approximations. Facing the discontinuity in cost function introduced by temporal logic constraints and system dynamics, we introduce (1) a rank function in formal logic specifications to enable sample-efficient search; (2) specification-guided basis selection. Under mild technical assumptions, the proposed algorithm converges, with probability one, to a global approximate optimal policy that ensures the satisfaction of temporal logic constraints. The correctness and efficiency of the method are demonstrated through numerical experiments including temporal logic planning for a linear system and a nonlinear mobile robot.

关键词： Planning Approximation algorithms Trajectory Function approximation Nonlinear systems Optimal control Automata

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Automatic color correction for 3D reconstruction of underwater scenes

Automatic color correction for 3D reconstruction of underwat...

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2017 IEEE International Conference on robotics and Automation, ICRA 2017

作者： Skinner, Katherine A. Iscar, Eduardo Johnson-Roberson, Matthew Robotics Program University of Michigan Ann ArborMI48109 United States Department of Naval Architecture and Marine Engineering University of Michigan Ann ArborMI48109 United States

ISBN: (纸本)9781509046331

Mapping of underwater environments is a critical task for a range of activities from monitoring coral reef habitats to surveying submerged archaeological sites. While recent advances in methods for terrestrial mapping can achieve dense 3D reconstructions of scenes in real-time, there remains the challenge of transferring these methods to the underwater domain due to characteristic effects on propagation of light through the water column that violate the brightness constancy constraint used in terrestrial techniques. Current state-of-the-art methods for underwater 3D reconstruction exploit a physical model of light propagation underwater to account for such range-dependent effects as scattering and attenuation;however, these methods necessitate careful calibration of attenuation coefficients required by the physical model, or rely on rough estimates of these coefficients from prior lab experiments. The main contribution of this paper is to develop a novel method to achieve simultaneous estimation of attenuation coefficients for color correction during structure recovery of an underwater scene by integrating this estimation directly into the bundle adjustment step, which performs non-linear optimization. To validate the proposed method, an artificial scene is submerged in a pure water tank and surveyed with a stereo camera platform to simulate an underwater robotic survey in a controlled environment. The target structure is imaged in air with an RGB-D sensor to provide ground truth structure and color, and a color calibration board is place in the scene for further reference. Results show that the proposed method can automatically estimate a water-column aware model for color correction of underwater images simultaneously to 3D reconstruction of the submerged scene. © 2017 IEEE.

关键词： Mapping

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Inverse reinforce learning with nonparametric behavior clustering

arXiv

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arXiv 2017年

作者： Rajasekaran, Siddharthan Zhang, Jinwei Fu, Jie Department of Electrical and Computer Engineering Robotics Engineering Program Worcester Polytechnic Institute

Inverse Reinforcement Learning (IRL) is the task of learning a single reward function given a Markov Decision Process (MDP) without defining the reward function, and a set of demonstrations generated by humans/experts. However, in practice, it may be unreasonable to assume that human behaviors can be explained by one reward function since they may be inherently inconsistent. Also, demonstrations may be collected from various users and aggregated to infer and predict users behaviors. In this paper, we introduce the Non-parametric Behavior Clustering IRL algorithm to simultaneously cluster demonstrations and learn multiple reward functions from demonstrations that may be generated from more than one behaviors. Our method is iterative: It alternates between clustering demonstrations into different behavior clusters and inverse learning the reward functions until convergence. It is built upon the Expectation-Maximization formulation and non-parametric clustering in the IRL setting. Further, to improve the computation efficiency, we remove the need of completely solving multiple IRL problems for multiple clusters during the iteration steps and introduce a resampling technique to avoid generating too many unlikely clusters. We demonstrate the convergence and efficiency of the proposed method through learning multiple driver behaviors from demonstrations generated from a grid-world environment and continuous trajectories collected from autonomous robot cars using the Gazebo robot simulator. Copyright © 2017, The Authors. All rights reserved.

关键词： Demonstrations

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Framing Effects on Privacy Concerns About a Home Telepresence Robot

Framing Effects on Privacy Concerns About a Home Telepresenc...

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ACM/IEEE International Conference on Human-Robot Interaction (HRI)

作者： Matthew Hueben Frank J. Bernieri Cindy M. Grimm William D. Smart Robotics Program School of Psychological Science Oregon State University Corvallis OR United States

ISBN: (纸本)9781450343367

Privacy-sensitive robotics is an emerging area of HRI research. Judgments about privacy would seem to be context-dependent, but none of the promising work on contextual “frames” has focused on privacy concerns. This work studies the impact of contextual “frames” on local users' privacy judgments in a home telepresence setting. Our methodology consists of using an online questionnaire to collect responses to animated videos of a telepresence robot after framing people with an introductory paragraph. The results of four studies indicate a large effect of manipulating the robot operator's identity between a stranger and a close confidante. It also appears that this framing effect persists throughout several videos. These findings serve to caution HRI researchers that a change in frame could cause their results to fail to replicate or generalize. We also recommend that robots be designed to encourage or discourage certain frames.

关键词： Privacy Videos Telepresence Robot sensing systems Psychology Animation

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Development of a Hover-Capable AUV System for Automated Visual Ship-Hull Inspection and Mapping

Development of a Hover-Capable AUV System for Automated Visu...

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Oceans (Conference)

作者： Seonghun Hong Dongha Chung Jinwhan Kim Robotics Program KAIST Daejeon Korea Department of Mechanical Engineering KAIST Daejeon Korea

ISBN: (纸本)9781509064298;9780692946909

Generally, underwater hull inspection have been conducted by human divers. It is an extremely dangerous task, and hence, can be a potential application for unmanned underwater vehicles. The operational safety and performance of in-water inspection can be significantly improved by introducing unmanned vehicle systems. This study addresses the development of an hover-capable autonomous underwater vehicle system and its operational algorithms for automated visual ship hull inspection with no (or minimum) human intervention. The feasibility and practical performance of the developed system and algorithms are demonstrated by conducting field experiments with a full-scale ship in a real sea environment.

关键词： Autonomous underwater vehicles Visual inspection Underwater navigation Image mosaicking

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Planning and executing optimal non-entangling paths for tethered underwater vehicles

Planning and executing optimal non-entangling paths for teth...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Seth McCammon Geoffrey A. Hollinger Robotics Program of the School of Mechanical Industrial and Manufacturing Engineering Oregon State University Corvallis OR

In this paper, we present a method to improve the navigation of tethered underwater vehicles by computing optimal paths that prevent their tethers from becoming entangled in obstacles. To accomplish this, we define the Non-Entangling Travelling Salesperson Problem (NE-TSP) as an extension of the Travelling Salesperson Problem with a non-entangling constraint. We compute the optimal solution to the NE-TSP by constructing a Mixed Integer programming model, leveraging homotopy augmented graphs to plan an optimal trajectory through a set of inspection points, while maintaining a non-entangling guarantee. To avoid the computational expense of computing an optimal solution to the NE-TSP, we also introduce several methods to compute near-optimal solutions. In a set of simulated trials, our method was able to plan optimal non-entangling paths through a variety of environments. These results were then validated in a set of pool and field trials using a Seabotix vLBV300 underwater vehicle. The paths generated by our method were then compared to human-generated paths.

关键词： Trajectory Planning Inspection Computational modeling Service robots Underwater vehicles

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Lidar-guided autonomous landing of an aerial vehicle on a ground vehicle

Lidar-guided autonomous landing of an aerial vehicle on a gr...

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Jonghwi Kim Sangwook Woo Jinwhan Kim Department of Mechanical Engineering KAIST Daejeon Korea Robotics Program KAIST Daejeon Korea

This paper addresses the autonomous landing of an unmanned aerial vehicle (UAV) on a ground vehicle. Unlike most of the previous research on autonomous UAV landing that used onboard sensors mounted on the UAV, this study suggests using a lidar mounted on a ground vehicle for lidar-guided landing. To estimate the relative position of the UAV with respect to the landing platform, a clustering algorithm is applied. In addition, to enhance the safety of landing, a decision making procedure based on simple reachability analysis is introduced. The proposed landing method is implemented and then verified through an experiment.

关键词： Laser radar Drones Sensors Cameras Three-dimensional displays Land vehicles

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Heart on A Chip: Label-Free Isolation and Single Cell Biophysical Phenotyping Analysis of Primary Cardiomyocytes Using Inertial Microfluidics (Small 8/2021)

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Small 2021年第8期17卷

作者： Hossein Tavassoli Prunella Rorimpandey Young Chan Kang Michael Carnell Chris Brownlee John E Pimanda Peggy P.Y. Chan Vashe Chandrakanthan Department of Telecommunications Electrical Robotics and Biomedical Engineering Swinburne University of Technology Hawthorn Victoria 3122 Australia Department of Pathology School of Medical Sciences University of New South Wales Sydney NSW 2052 Australia Adult Cancer Program Lowy Cancer Research Centre University of New South Wales Sydney NSW 2052 Australia Biomedical Imaging Facility Mark Wainwright Analytical Centre University of New South Wales Sydney NSW 2052 Australia Flow Cytometry Facility Mark Wainwright Analytical Centre University of New South Wales Sydney NSW 2052 Australia Prince of Wales Clinical School University of New South Wales Sydney NSW 2052 Australia Department of Haematology Prince of Wales Hospital Sydney NSW 2052 Australia

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A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge

arXiv

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arXiv 2024年

作者： de la Rosa, Ezequiel Reyes, Mauricio Liew, Sook-Lei Hutton, Alexandre Wiest, Roland Kaesmacher, Johannes Hanning, Uta Hakim, Arsany Zubal, Richard Valenzuela, Waldo Robben, David Sima, Diana M. Anania, Vincenzo Brys, Arne Meakin, James A. Mickan, Anne Broocks, Gabriel Heitkamp, Christian Gao, Shengbo Liang, Kongming Zhang, Ziji Siddiquee, Md Mahfuzur Rahman Myronenko, Andriy Ashtari, Pooya Van Huffel, Sabine Jeong, Hyun-Su Yoon, Chi-Ho Kim, Chulhong Huo, Jiayu Ourselin, Sebastien Sparks, Rachel Clèrigues, Albert Oliver, Arnau Lladó, Xavier Chalcroft, Liam Pappas, Ioannis Bertels, Jeroen Heylen, Ewout Moreau, Juliette Hatami, Nima Frindel, Carole Qayyum, Abdul Mazher, Moona Puig, Domenec Lin, Shao-Chieh Juan, Chun-Jung Hu, Tianxi Boone, Lyndon Goubran, Maged Liu, Yi-Jui Wegener, Susanne Kofler, Florian Ezhov, Ivan Shit, Suprosanna Hernandez Petzsche, Moritz R. Menze, Bjoern Kirschke, Jan S. Wiestler, Benedikt Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Informatics Technical University Munich Germany Icometrix Leuven Belgium ARTORG Center for Biomedical Research University of Bern Bern Switzerland Department of Radiation Oncology University Hospital Bern University of Bern Switzerland University of Bern Bern Switzerland Chan Division of Occupational Science and Occupational Therapy University of Southern California Los AngelesCA United States Stevens Neuroimaging and Informatics Institute Department of Neurology Keck School of Medicine University of Southern California United States University Institute of Diagnostic and Interventional Neuroradiology Inselspital Bern Switzerland University Institute of Diagnostic and Interventional Neuroradiology University Hospital Bern Inselspital University of Bern Bern Switzerland Department of Diagnostic and Interventional neuroradiology University Medical Center Hamburg-Eppendorf Hamburg Germany Department of Medical Imaging Radboud University Medical Center Institute for Health Sciences Nijmegen Netherlands Deepwise AI Lab Beijing China Beijing University of Posts and Telecommunications Bejing China School of Computing and Augmented Intelligence Arizona State University TempeAZ United States NVIDIA Santa ClaraCA United States STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Pohang Korea Republic of School of Biomedical Engineering & Imaging Sciences King’s College London United Kingdom Institute of Computer Vision and Robotics University of Girona Spain Wellcome Centre for Human Neuroimaging University College London London United Kingdom Laboratory of Neuro Imaging Stevens Institute for Neuroimaging and Informatics Keck School of Medicine University of Southern California Los Angeles United States KU Leuven Leuven Belgium CREATIS Université Lyon1 CNRS UMR5220 INSERM U1206 INSA-Lyon Villeurbanne696

Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable AI algorithms with clinical value. We address this gap by presenting a novel ensemble algorithm derived from the 2022 Ischemic Stroke Lesion Segmentation (ISLES) challenge. ISLES’22 provided 400 patient scans with ischemic stroke from various medical centers, facilitating the development of a wide range of cutting-edge segmentation algorithms by the research community. By assessing them against a hidden test set, we identified strengths, weaknesses, and potential biases. Through collaboration with leading teams, we combined top-performing algorithms into an ensemble model that overcomes the limitations of individual solutions. Our ensemble model combines the individual algorithms’ strengths and achieved superior ischemic lesion detection and segmentation accuracy (median Dice score: 0.82, median lesion-wise F1 score: 0.86) on our internal test set compared to individual algorithms. This accuracy generalized well across diverse image and disease variables. Furthermore, the model excelled in extracting clinical biomarkers like lesion types and affected vascular territories. Notably, in a Turing-like test, neuroradiologists consistently preferred the algorithm’s segmentations over manual expert efforts, highlighting increased comprehensiveness and precision. Validation using a real-world external dataset (N=1686) confirmed the model’s generalizability (median Dice score: 0.82, median lesion-wise F1 score: 0.86). The algorithm’s outputs also demonstrated strong correlations with clinical scores (admission NIHSS and 90-day mRS) on par with or exceeding expert-derived results, underlining its clinical relevance. This study offers two key findings. First, we present an ensemble algorithm that detects and segments ischemic stroke lesions on DWI across diverse scenarios on par with expert (neuro)rad

关键词： Diagnosis

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Low cost underwater acoustic localization 173

Low cost underwater acoustic localization

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173rd Meeting of Acoustical Society of America, Acoustics 2017 and 8th Forum Acusticum

作者： Ruland, Eduardo Alexander Iscar Shree, Atulya Goumas, Nicholas Johnson-Roberson, Matthew Naval Architecture and Marine Engineering University of Michigan Ann ArborMI48109 United States Robotics Program University of Michigan Ann ArborMI48109 United States University of Michigan Ann ArborMI48109 United States

Over the course of the last decade, the cost of marine robotic platforms has significantly decreased. In part this has lowered the barriers to entry of exploring and monitoring larger areas of the earth's oceans. However, these advances have been mostly focused on autonomous surface vehicles (ASVs) or shallow water autonomous underwater vehicles (AUVs). One of the main drivers for high cost in the deep water domain is the challenge of localizing such vehicles using acoustics. A low cost one-way travel time underwater ranging system is proposed to assist in localizing deep water submersibles. The system consists of location aware anchor buoys at the surface and underwater nodes. This paper presents a comparison of methods together with details on the physical implementation to allow its integration into a deep sea micro AUV currently in development. Additional simulation results show error reductions by a factor of three. © 2018 Acoustical Society of America.

关键词： Travel time

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