Anurag Sai Vempati


Last Name

Vempati

First Name

Anurag Sai

ORCID

0000-0001-9533-7930

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2018 - 20205
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Publications 1 - 5 of 5
  • A Virtual Reality Interface for an Autonomous Spray Painting UAV
    Item type: Journal Article
    Vempati, Anurag Sai; Khurana, Harshit; Kabelka, Vojtech; et al. (2019)
    IEEE Robotics and Automation Letters
  • PaintCopter: An Autonomous UAV for Spray Painting on Three-Dimensional Surfaces
    Item type: Journal Article
    Vempati, Anurag Sai; Kamel, Mina; Stilinovic, Nikola; et al. (2018)
    IEEE Robotics and Automation Letters
  • A Data-driven Planning Framework for Robotic Texture Painting on 3D Surfaces
    Item type: Conference Paper
    Vempati, Anurag Sai; Siegwart, Roland; Nieto, Juan (2020)
    2020 IEEE International Conference on Robotics and Automation (ICRA)
    Painting textures on 3D surfaces requires an understanding of the surface geometry, paint flow and paint mixing. This work formulates automated painting as a planning problem and proposes a solution based on a self-supervised learning framework that enables a robot to paint monochromatic non-uniform textures on 3D surfaces. We developed a method that iteratively decides the actions to take based on constant feedback of the painting process. Inspired by recent results, we formulate our solution using a recurrent neural network (RNN) to decide where and what to paint on the surface at each time instant. Specifically, the paint delivery tool's flow rate, orientation and position relative to the surface at each time instant are evaluated. This data can then be processed by a robot's planner of choice for generating a painting mission that can achieve the desired end result. We evaluate the proposed approach by providing qualitative and quantitative results of the different components. Furthermore, we validate the effectiveness of the approach for the application by providing renderings from a paint simulation environment and show how a robot executes the planned painting mission on a generic 3D surface. © 2020 IEEE.
  • Unmanned Aerial Vehicles for Maintenance of Themed Environments
    Item type: Doctoral Thesis
    Vempati, Anurag Sai (2019)
    Man-made infrastructure requires performing regular inspection and maintenance such that any structural damages or degradation can be resolved in a timely man- ner. Themed environments pose the need for cleaning and painting large and complex 3D structures on a regular basis in order to maintain their aesthetic ap- peal. Aerial robots could provide a faster and economical way to maintain large areas in a shorter time. This thesis aims to investigate the feasibility of using Unmanned Aerial Vehicles (UAVs) for performing such tasks. In particular, we aim to investigate the type of design, sensing and planning frameworks needed to enable UAVs to perform precise maintenance tasks in close proximity to complex structures. While we develop our robotic solution for themed environments, the so- lutions presented and findings are relevant in other areas of structural maintenance as well. The primary contribution of this thesis is the design of an aerial platform suit- able to perform large-scale painting on 3D surfaces. Developing such a solution de- manded solving several crucial elements. For a UAV to be able to paint a generic 3D surface, it needs to accurately adjust its location with respect to the target surface. Specifically, the UAV has to maintain a certain distance and orientation at each point. This requires very accurate perception of the UAV’s surroundings. Hence, our first contribution is the development of a graphics processing unit (GPU) accel- erated dense reconstruction and localization pipeline that runs completely onboard the UAV with limited computation capabilities. Our perception stack can run at 60Hz fully onboard. Along with the ability to accurately localize relative to the 3D surface, the proposed approach can generate sub-centimeter maps of the surface using a hybrid GPU-CPU framework. These maps form a crucial backbone for other parts of the thesis. The following part of the thesis focuses on the hardware design of the Paint- Copter UAV and several software components that allow automated spraying on a given surface. PaintCopter is designed as a tethered platform, with dedicated power and paint lines, allowing extended mission duration times. With the spray gun mounted on a Pan-Tilt Unit (PTU), targeted spraying on precise locations is achieved, despite the platform disturbances. We show the capability of Paint- Copter in being able to paint any desired linear pattern on generic 3D surfaces in a fully autonomous fashion. However, such an approach makes it extremely hard to accurately modify the surface’s appearance. Therefore, the next contribution is the development of a Virtual Reality (VR) technology based user interface for the PaintCopter UAV. This interface allows the user to immerse in a virtual environ- ment consisting of the 3D model of the surface. The user will be able to virtually paint at desired locations on the target surface using a virtual spray gun. The in- formation from the virtual environment is processed to execute a painting mission by the PaintCopter to generate a similar output as in the virtual environment. In this way, the painter will be able to paint the structure in a similar fashion as he/she would in the real-world. The final part of the thesis focuses on automating the process by performing end-to-end planning of a painting process. With this approach, the user provides the desired appearance of the structure in the form of a colored 3D model and our software plans the entire mission including what to paint and where to paint in order to achieve the desired appearance. Our data-driven approach is fully self-supervised and does not require any sort of intervention from a human expert. Through this thesis, we show that UAVs can be designed to perform accurate and fast cleaning/painting jobs on large 3D surfaces. We provide solutions to address the challenges involved in painting or cleaning such structures with high precision. We develop software that allows planning and executing (a) semi-autonomous mis- sions with human supervision, or, (b) fully autonomous end-to-end missions. The proposed solutions have been extensively tested on the field, over extended periods of time, validating the reliability and effectiveness of the system.
  • StreetMap - Mapping and Localization on Ground Planes using a Downward Facing Camera
    Item type: Conference Paper
    Chen, Xu; Vempati, Anurag Sai; Beardsley, Paul (2018)
    2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
    This paper describes a system to map a ground-plane, and to subsequently use the map for localization of a mobile robot. The robot has a downward-facing camera, and works on a variety of ground textures including general texture like tarmac, man-made designs like carpet, and rectilinear textures like indoor tiles or outdoor slabs. Such textures provide a basis for measuring relative motion (i.e. computer mouse functionality). But the goal here is the more challenging one of absolute localization. The paper describes a complete working pipeline to build a globally consistent map of a given ground-plane and subsequently to localize within this map at real-time. Two algorithms are described. The first is a feature-based approach which is general to any ground plane texture. The second algorithm takes advantage of the extra constraints available for common rectilinear textures like indoor tiling, paving slabs, and laid brickwork. Quantitative and qualitative experimental results are shown for mapping and localization on a variety of ground-planes.
Publications 1 - 5 of 5