Mr. Kumud Nepal Profile

Kumud Nepal

at Trinity College

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Publications (2)

Proceedings Article | 18 January 2010 Paper

Application of a distributed systems architecture for increased speed in image processing on an autonomous ground vehicle

Adam Wright, Orko Momin, Young Ho Shin, Rahul Shakya, Kumud Nepal, David Ahlgren

Proceedings Volume 7539, 75390O (2010) https://doi.org/10.1117/12.840313

KEYWORDS: Robots, Field programmable gate arrays, Image processing, Sensors, LabVIEW, Cameras, Control systems, Distributed computing, Data processing, Global Positioning System

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This paper presents the application of a distributed systems architecture to an autonomous ground vehicle, Q, that participates in both the autonomous and navigation challenges of the Intelligent Ground Vehicle Competition. In the autonomous challenge the vehicle is required to follow a course, while avoiding obstacles and staying within the course boundaries, which are marked by white lines. For the navigation challenge, the vehicle is required to reach a set of target destinations, known as way points, with given GPS coordinates and avoid obstacles that it encounters in the process. Previously the vehicle utilized a single laptop to execute all processing activities including image processing, sensor interfacing and data processing, path planning and navigation algorithms and motor control. National Instruments' (NI) LabVIEW served as the programming language for software implementation. As an upgrade to last year's design, a NI compact Reconfigurable Input/Output system (cRIO) was incorporated to the system architecture. The cRIO is NI's solution for rapid prototyping that is equipped with a real time processor, an FPGA and modular input/output. Under the current system, the real time processor handles the path planning and navigation algorithms, the FPGA gathers and processes sensor data. This setup leaves the laptop to focus on running the image processing algorithm. Image processing as previously presented by Nepal et. al. is a multi-step line extraction algorithm and constitutes the largest processor load. This distributed approach results in a faster image processing algorithm which was previously Q's bottleneck. Additionally, the path planning and navigation algorithms are executed more reliably on the real time processor due to the deterministic nature of operation. The implementation of this architecture required exploration of various inter-system communication techniques. Data transfer between the laptop and the real time processor using UDP packets was established as the most reliable protocol after testing various options. Improvement can be made to the system by migrating more algorithms to the hardware based FPGA to further speed up the operations of the vehicle.

Proceedings Article | 19 January 2009 Paper

Combining a modified vector field histogram algorithm and real-time image processing for unknown environment navigation

Kumud Nepal, Adam Fine, Nabil Imam, David Pietrocola, Neil Robertson, David Ahlgren

Proceedings Volume 7252, 72520G (2009) https://doi.org/10.1117/12.807650

KEYWORDS: Image processing, Laser range finders, Sensors, Cameras, Algorithm development, LabVIEW, Detection and tracking algorithms, Data processing, Global Positioning System, Particle filters

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