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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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DispSegNet: Leveraging semantics for end-to-end learning of disparity estimation from stereo imagery

arXiv

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arXiv 2018年

作者： Zhang, Junming Skinner, Katherine A. Vasudevan, Ram Johnson-Roberson, Matthew Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States Robotics Program University of Michigan Ann ArborMI48109 United States Department of Mechanical Engineering University of Michigan Ann ArborMI48109 United States Department of Naval Architecture and Marine Engineering University of Michigan Ann ArborMI48109 United States

Recent work has shown that convolutional neural networks (CNNs) can be applied successfully in disparity estimation, but these methods still suffer from errors in regions of low-texture, occlusions and reflections. Concurrently, deep learning for semantic segmentation has shown great progress in recent years. In this paper, we design a CNN architecture that combines these two tasks to improve the quality and accuracy of disparity estimation with the help of semantic segmentation. Specifically, we propose a network structure in which these two tasks are highly coupled. One key novelty of this approach is the two-stage refinement process. Initial disparity estimates are refined with an embedding learned from the semantic segmentation branch of the network. The proposed model is trained using an unsupervised approach, in which images from one half of the stereo pair are warped and compared against images from the other camera. Another key advantage of the proposed approach is that a single network is capable of outputting disparity estimates and semantic labels. These outputs are of great use in autonomous vehicle operation;with real-time constraints being key, such performance improvements increase the viability of driving applications. Experiments on KITTI and Cityscapes datasets show that our model can achieve state-of-the-art results and that leveraging embedding learned from semantic segmentation improves the performance of disparity estimation. Copyright © 2018, The Authors. All rights reserved.

关键词： Semantic Segmentation

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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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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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CWave: High-performance single-source any-angle path planning on a grid

CWave: High-performance single-source any-angle path plannin...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Dmitry A. Sinyukov Taşkin Padir Robotics Engineering Program Worcester Polytechnic Institute Worcester MA USA Department of Electrical and Computer Engineering Northeastern University Boston MA

Path planning on a 2D-grid is a well-studied problem in robotics. It usually involves searching for a shortest path between two vertices on a grid. Single-source path planning is a modified problem which asks to find distances from a given point to all other points on the map. A high-performance algorithm for single-source any-angle path planning on a grid that we named CWave is proposed in this work. “Any-angle” attribute of a path planning algorithm implies that such algorithm can find paths which may include any angle segments, as opposed to standard A* on an 8-connected graph, the path can turn with 45°-increments only. The key idea of the presented algorithm is that it does not represent the grid as a graph and uses discrete geometric primitives to define the wave front. In its purest form, CWave requires for computation only integer arithmetics and multiplication by two, but can accumulate the distance error at turning points. A modified version of CWave with minimal usage of floating-point calculations is also developed. It allows to eliminate any accumulative errors which is proven mathematically and experimentally on several maps. The performance of the algorithm on three maps is demonstrated to be significantly faster than that of Theta*, Lazy Theta* and Field A* adapted for single-source planning. The limitations of the current implementations of the algorithm as well as potential improvements are discussed.

关键词： Path planning Algorithm design and analysis Two dimensional displays Navigation Planning Mobile robots

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Driving in the Matrix: Can virtual worlds replace human-generated annotations for real world tasks?

Driving in the Matrix: Can virtual worlds replace human-gene...

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2017 IEEE International Conference on robotics and Automation, ICRA 2017

作者： Johnson-Roberson, Matthew Barto, Charles Mehta, Rounak Sridhar, Sharath Nittur Rosaen, Karl Vasudevan, Ram Department of Naval Architecture and Marine Engineering University of Michigan Ann ArborMI48109 United States Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States Robotics Program University of Michigan Ann ArborMI48109 United States Mechanical Engineering University of Michigan Ann ArborMI48109 United States

ISBN: (纸本)9781509046331

Deep learning has rapidly transformed the state of the art algorithms used to address a variety of problems in computer vision and robotics. These breakthroughs have relied upon massive amounts of human annotated training data. This time consuming process has begun impeding the progress of these deep learning efforts. This paper describes a method to incorporate photo-realistic computer images from a simulation engine to rapidly generate annotated data that can be used for the training of machine learning algorithms. We demonstrate that a state of the art architecture, which is trained only using these synthetic annotations, performs better than the identical architecture trained on human annotated real-world data, when tested on the KITTI data set for vehicle detection. By training machine learning algorithms on a rich virtual world, real objects in real scenes can be learned and classified using synthetic data. This approach offers the possibility of accelerating deep learning's application to sensor-based classification problems like those that appear in self-driving cars. The source code and data to train and validate the networks described in this paper are made available for researchers. © 2017 IEEE.

关键词： Object detection

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A study for estimating reaction force of robot arm by using PDSPO

A study for estimating reaction force of robot arm by using ...

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Hyun Hee Kim Sun Oh Park Jin Ho Kyung Hyun Min Do Min Cheol Lee Interdisciplinary Program in Robotics Pusan National University Busan Korea School of Mechanical Engineering Pusan National University Busan Korea Department of Robotics and Mechatronics Korea Institute of Machinery and Materials Daejeon Korea

In the industrial field, assembling parts using robot arm requires force information. Some robot arms with torque sensors are commercially available, but they are difficult to use for industrial applications due to durability problems. In addition, mounting a torque sensor on the robot arm increases manufacturing costs and complicates the structure. In this study, we apply Sliding Perturbation Observer (SPO) to 7-axis robot manipulator and estimate reaction force without using torque sensor in simulation. From the estimated perturbation, it can be determined whether the end effector of the robot manipulator will crash part of the assembly.

关键词： Manipulators Service robots Robot sensing systems Collision avoidance Observers Force

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NANOROBOTS: Intracellular manipulation and measurement with multipole magnetic tweezers

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Science robotics 2019年第28期4卷

作者： Wang, X. Ho, C. Tsatskis, Y. Law, J. Zhang, Z. Zhu, M. Dai, C. Wang, F. Tan, M. Hopyan, S. McNeill, H. Sun, Y. Department of Mechanical and Industrial Engineering University of Toronto TorontoONM5S 3G8 Canada Institute of Biomaterials and Biomedical Engineering TorontoONM5S 3G9 Canada Lunenfeld-Tanenbaum Research Institute Mt. Sinai Hospital TorontoONM5G 1X5 Canada Program in Developmental and Stem Cell Biology Hospital for Sick Children TorontoONM5G 1X8 Canada HRG Central Institute of Robotics HIT Robot Group Harbin Heilongjiang150001 China Institute of Automation Chinese Academy of Sciences Beijing100190 China Division of Orthopaedic Surgery Hospital for Sick Children and University of Toronto TorontoONM5G 1X8 Canada Department of Developmental Biology Washington University School of Medicine St. LouisMO63108 United States Department of Electrical and Computer Engineering University of Toronto TorontoONM5S 3G4 Canada

The capability to directly interrogate intracellular structures inside a single cell for measurement and manipulation is important for understanding subcellular and suborganelle activities, diagnosing diseases, and developing new therapeutic approaches. Compared with measurements of single cells, physical measurement and manipulation of subcellular structures and organelles remain underexplored. To improve intracellular physical measurement and manipulation,we have developed amultipole magnetic tweezers system for micromanipulation involving submicrometer position control and piconewton force control of a submicrometermagnetic bead inside a single cell for measurement in different locations (spatial) and different time points (temporal). The beadwas three-dimensionally positioned in the cell using a generalized predictive controller that addresses the control challenge caused by the low bandwidth of visual feedback from high-resolution confocal imaging. The average positioning error was quantified to be 0.4 mm, slightly larger than the Brownianmotion-imposed constraint (0.31 mm). The system is also capable of applying a force up to 60 pN with a resolution of 4 pN for a period of time longer than 30 min. The measurement results revealed that significantly higher stiffness exists in the nucleus' major axis than in the minor axis. This stiffness polarity is likely attributed to the aligned actin filament. We also showed that the nucleus stiffens upon the application of an intracellularly applied force, which can be attributed to the response of structural protein lamin A/C and the intracellular stress fiber actin filaments. © 2019 The Authors.

关键词： Cells

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Towards a soft robotic skin for autonomous tissue palpation

Towards a soft robotic skin for autonomous tissue palpation

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IEEE International Conference on robotics and Automation (ICRA)

作者： Federico Campisano Selim Ozel Anand Ramakrishnan Anany Dwivedi Nikolaos Gkotsis Cagdas D. Onal Pietro Valdastri Department of Mechanical Engineering Vanderbilt University Nashville TN USA Worcester Polytechnic Institute Worcester MA US Department of Mechanical Engineering and Robotics Engineering Program Worcester Polytechnic Institute Worcester MA USA Department of Robotics and Autonomous System University of Leeds Leeds UK

Manual palpation is commonly used to localize tumors and other features buried deep inside organs during open surgery. This approach is not feasible in minimally invasive or robotic surgery, as the contact with the tissue is mediated by instruments. To address this problem, we propose a soft robotic skin (SRS) that can be deployed from a small incision and create a stiffness map in a single step. Such a skin is composed of a matrix of soft robotic tactile elements (SRTEs), each one able to expand and record the tissue response during expansion. In this paper, we firstly prove the feasibility of palpation using a single SRTE. Then, we present and test a soft-suction based anchoring mechanism able to keep the SRS in the desired position in contact with the tissue, allowing surgeons to palpate different sides of the organ. Finally, we detail a calibration method for the SRTE, and assess the feasibility of identifying lumps buried inside a soft tissue phantom, and then inside a chicken liver during an ex-vivo trial. Experimental results show that the SRTE was able to differentiate simulated lumps (up to 3.25 mm deep) from healthy tissue in both the phantom and the ex-vivo trials. These results, added to the ability of the suction gripper to compensate for the expansion forces of each SRTE, are paving the way for soft robotic autonomous tools that can be used for intraoperative mapping of tissue cancers.

关键词： Surgery Rubber Soft robotics Grippers Calibration Robot sensing systems

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Hadamard product for low-rank bilinear pooling 5

Hadamard product for low-rank bilinear pooling

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5th International Conference on Learning Representations, ICLR 2017

作者： Kim, Jin-Hwa On, Kyoung-Woon Lim, Woosang Kim, Jeonghee Ha, Jung-Woo Zhang, Byoung-Tak Interdisciplinary Program in Cognitive Science Seoul National University Seoul08826 Korea Republic of School of Computer Science and Engineering Seoul National University Seoul08826 Korea Republic of School of Computing KAIST Daejeon34141 Korea Republic of NAVER LABS Corp. NAVER Corp Gyeonggi-do13561 Korea Republic of School of Computer Science and Engineering Interdisciplinary Program in Cognitive Science Seoul National University and Surromind Robotics Seoul08826 Korea Republic of

Bilinear models provide rich representations compared with linear models. They have been applied in various visual tasks, such as object recognition, segmentation, and visual question-answering, to get state-of-the-art performances taking advantage of the expanded representations. However, bilinear representations tend to be high-dimensional, limiting the applicability to computationally complex tasks. We propose low-rank bilinear pooling using Hadamard product for an efficient attention mechanism of multimodal learning. We show that our model outperforms compact bilinear pooling in visual question-answering tasks with the state-of-the-art results on the VQA dataset, having a better parsimonious property. © ICLR 2019 - Conference Track Proceedings. All rights reserved.

关键词： Object recognition

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