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Fei Gao

Bio: Fei Gao is an academic researcher from Zhejiang University. The author has contributed to research in topics: Computer science & Trajectory. The author has an hindex of 27, co-authored 191 publications receiving 2436 citations. Previous affiliations of Fei Gao include Arizona State University & Anhui University.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
10 Jul 2019
TL;DR: In this article, a robust and efficient quadrotor motion planning system for fast flight in 3D complex environments is proposed, which adopts a kinodynamic path searching method to find a safe, kinodynamic feasible, and minimum-time initial trajectory in the discretized control space.
Abstract: In this letter, we propose a robust and efficient quadrotor motion planning system for fast flight in three-dimensional complex environments. We adopt a kinodynamic path searching method to find a safe, kinodynamic feasible, and minimum-time initial trajectory in the discretized control space. We improve the smoothness and clearance of the trajectory by a B-spline optimization, which incorporates gradient information from a Euclidean distance field and dynamic constraints efficiently utilizing the convex hull property of B-spline. Finally, by representing the final trajectory as a non-uniform B-spline, an iterative time adjustment method is adopted to guarantee dynamically feasible and non-conservative trajectories. We validate our proposed method in various complex simulational environments. The competence of the method is also validated in challenging real-world tasks. We release our code as an open-source package.

220 citations

Proceedings ArticleDOI
21 May 2018
TL;DR: This paper adopts a fast marching-based path searching method to find a path on a velocity field induced by the Euclidean signed distance field (ESDF) of the map, to achieve better time allocation.
Abstract: In this paper, we propose a framework for online quadrotor motion planning for autonomous navigation in unknown environments. Based on the onboard state estimation and environment perception, we adopt a fast marching-based path searching method to find a path on a velocity field induced by the Euclidean signed distance field (ESDF) of the map, to achieve better time allocation. We generate a flight corridor for the quadrotor to travel through by inflating the path against the environment. We represent the trajectory as piecewise Bezier curves by using Bernstein polynomial basis and formulate the trajectory generation problem as typical convex programs. By using Bezier curves, we are able to bound positions and higher order dynamics of the trajectory entirely within safe regions. The proposed motion planning method is integrated into a customized light-weight quadrotor platform and is validated by presenting fully autonomous navigation in unknown cluttered indoor and outdoor environments. We also release our code for trajectory generation as an open-source package.

201 citations

Journal ArticleDOI
TL;DR: It is shown that it is possible to achieve reliable online autonomous navigation using monocular VINS, and the backbone of the system is a highly accurate optimization‐based monocular visual‐inertial state estimator with online initialization and self‐extrinsic calibration.
Abstract: Autonomous micro aerial vehicles (MAVs) have cost and mobility benefits, making them ideal robotic platforms for applications including aerial photography, surveillance, and search and rescue. As the platform scales down, MAVs become more capable of operating in confined environments, but it also introduces significant size and payload constraints. A monocular visual-inertial navigation system (VINS), consisting only of an inertial measurement unit (IMU) and a camera, becomes the most suitable sensor suite in this case, thanks to its light weight and small footprint. In fact, it is the minimum sensor suite allowing autonomous flight with sufficient environmental awareness. In this paper, we show that it is possible to achieve reliable online autonomous navigation using monocular VINS. Our system is built on a customized quadrotor testbed equipped with a fisheye camera, a low-cost IMU, and heterogeneous onboard computing resources. The backbone of our system is a highly accurate optimization-based monocular visual-inertial state estimator with online initialization and self-extrinsic calibration. An onboard GPU-based monocular dense mapping module that conditions on the estimated pose provides wide-angle situational awareness. Finally, an online trajectory planner that operates directly on the incrementally built three-dimensional map guarantees safe navigation through cluttered environments. Extensive experimental results are provided to validate individual system modules as well as the overall performance in both indoor and outdoor environments.

186 citations

Posted Content
TL;DR: A kinodynamic path searching method to find a safe, kinodynamic feasible, and minimum-time initial trajectory in the discretized control space is adopted and the competence of the method is also validated in challenging real-world tasks.
Abstract: In this paper, we propose a robust and efficient quadrotor motion planning system for fast flight in 3-D complex environments. We adopt a kinodynamic path searching method to find a safe, kinodynamic feasible and minimum-time initial trajectory in the discretized control space. We improve the smoothness and clearance of the trajectory by a B-spline optimization, which incorporates gradient information from a Euclidean distance field (EDF) and dynamic constraints efficiently utilizing the convex hull property of B-spline. Finally, by representing the final trajectory as a non-uniform B-spline, an iterative time adjustment method is adopted to guarantee dynamically feasible and non-conservative trajectories. We validate our proposed method in various complex simulational environments. The competence of the method is also validated in challenging real-world tasks. We release our code as an open-source package.

155 citations

Proceedings ArticleDOI
01 Nov 2019
TL;DR: This paper proposes a mapping system called FIESTA to build global ESDF map incrementally by introducing two independent updating queues for inserting and deleting obstacles separately, and using Indexing Data Structures and Doubly Linked Lists for map maintenance, which has high computational performance and produces near-optimal results.
Abstract: Euclidean Signed Distance Field (ESDF) is useful for online motion planning of aerial robots since it can easily query the distance and gradient information against obstacles. Fast incrementally built ESDF map is the bottleneck for conducting real-time motion planning. In this paper, we investigate this problem and propose a mapping system called FIESTA to build global ESDF map incrementally. By introducing two independent updating queues for inserting and deleting obstacles separately, and using Indexing Data Structures and Doubly Linked Lists for map maintenance, our algorithm updates as few as possible nodes using a BFS framework. Our ESDF map has high computational performance and produces near-optimal results. We show our method outperforms other up-to-date methods in term of performance and accuracy by both theory and experiments. We integrate FIESTA into a completed quadrotor system and validate it by both simulation and onboard experiments. We release our method as open-source software for the community 11https://github.com/hlx1996/FIESTA

123 citations


Cited by
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Journal ArticleDOI
TL;DR: In this article, a robust and versatile monocular visual-inertial state estimator is presented, which is the minimum sensor suite (in size, weight, and power) for the metric six degrees of freedom (DOF) state estimation.
Abstract: One camera and one low-cost inertial measurement unit (IMU) form a monocular visual-inertial system (VINS), which is the minimum sensor suite (in size, weight, and power) for the metric six degrees-of-freedom (DOF) state estimation. In this paper, we present VINS-Mono: a robust and versatile monocular visual-inertial state estimator. Our approach starts with a robust procedure for estimator initialization. A tightly coupled, nonlinear optimization-based method is used to obtain highly accurate visual-inertial odometry by fusing preintegrated IMU measurements and feature observations. A loop detection module, in combination with our tightly coupled formulation, enables relocalization with minimum computation. We additionally perform 4-DOF pose graph optimization to enforce the global consistency. Furthermore, the proposed system can reuse a map by saving and loading it in an efficient way. The current and previous maps can be merged together by the global pose graph optimization. We validate the performance of our system on public datasets and real-world experiments and compare against other state-of-the-art algorithms. We also perform an onboard closed-loop autonomous flight on the microaerial-vehicle platform and port the algorithm to an iOS-based demonstration. We highlight that the proposed work is a reliable, complete, and versatile system that is applicable for different applications that require high accuracy in localization. We open source our implementations for both PCs ( https://github.com/HKUST-Aerial-Robotics/VINS-Mono ) and iOS mobile devices ( https://github.com/HKUST-Aerial-Robotics/VINS-Mobile ).

2,305 citations

Journal ArticleDOI
TL;DR: This set of labels and features should enable direct utilization of the TCGA/TCIA glioma collections towards repeatable, reproducible and comparative quantitative studies leading to new predictive, prognostic, and diagnostic assessments, as well as performance evaluation of computer-aided segmentation methods.
Abstract: Gliomas belong to a group of central nervous system tumors, and consist of various sub-regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for both clinical and computational studies, including radiomic and radiogenomic analyses. Towards this end, we release segmentation labels and radiomic features for all pre-operative multimodal magnetic resonance imaging (MRI) (n=243) of the multi-institutional glioma collections of The Cancer Genome Atlas (TCGA), publicly available in The Cancer Imaging Archive (TCIA). Pre-operative scans were identified in both glioblastoma (TCGA-GBM, n=135) and low-grade-glioma (TCGA-LGG, n=108) collections via radiological assessment. The glioma sub-region labels were produced by an automated state-of-the-art method and manually revised by an expert board-certified neuroradiologist. An extensive panel of radiomic features was extracted based on the manually-revised labels. This set of labels and features should enable i) direct utilization of the TCGA/TCIA glioma collections towards repeatable, reproducible and comparative quantitative studies leading to new predictive, prognostic, and diagnostic assessments, as well as ii) performance evaluation of computer-aided segmentation methods, and comparison to our state-of-the-art method.

1,818 citations

Journal ArticleDOI
Alan R. Jones1

1,349 citations

Journal ArticleDOI
01 Mar 1970

1,097 citations

01 Jan 1999
TL;DR: Damascene copper electroplating for on-chip interconnections, a process that was conceived and developed in the early 1990s, makes it possible to fill submicron trenches and vias with copper without creating a void or a seam and has thus proven superior to other technologies of copper deposition as discussed by the authors.
Abstract: Damascene copper electroplating for on-chip interconnections, a process that we conceived and developed in the early 1990s, makes it possible to fill submicron trenches and vias with copper without creating a void or a seam and has thus proven superior to other technologies of copper deposition. We discuss here the relationship of additives in the plating bath to superfilling, the phenomenon that results in superconformal coverage, and we present a numerical model which accounts for the experimentally observed profile evolution of the plated metal.

1,006 citations