Aditya Penumarti

Aditya Penumarti

A graduate student at the University of Florida researching robotic path planning

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portfolio

publications

Mechanical Networks: An Investigation Into Connected Kinematic Systems

Published in University of Florida, 2023

This paper delves into how the kinematic joints and the bodies in a mechanism can be described using directed graphs and the matrices of connectivity and loops that can be generated from it. This is called a mechanical network. Using these mechanical networked joints, a matrix of simple joint freedoms or constraints can be constructed. These matrices can be manipulated using the connectivity, loop, and node descriptions to describe a mechanism's geometric mobility and preloadability. To enhance this information, two case studies are explored, one of a lift mechanism, and another of a 3-RRR Spherical Parallel Platform, or Spherical Wrist.

Recommended citation: Penumarti, Aditya. (2023). "Mechanical Networks: An Investigation Into Connected Kinematic Systems." University of Florida. 1(1).
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Fast Marching based Rendezvous Path Planning for a Team of Heterogeneous Vehicles

Published in IEEE Access, 2024

This paper presents a formulation for deterministically calculating optimized paths for a multi-agent system consisting of heterogeneous vehicles. The key idea is the calculation of the shortest time for each agent to reach every grid point from its known initial position. Such arrival time map is efficiently computed using the Fast Marching Method (FMM), a computational algorithm originally designed for solving boundary value problems of the Eikonal equation. By leveraging the FMM, we demonstrate that the minimal time rendezvous point and paths for all member vehicles can be uniquely determined with minimal computational overhead. The scalability and adaptability of the present method during online execution are investigated, followed by a comparison with a baseline method that highlights the effectiveness of the proposed approach. Then, the potential of the present method is showcased through a virtual rendezvous scenario involving the coordination of a ship, an underwater vehicle, an aerial vehicle, and a ground vehicle, all converging at the optimal location within the Tampa Bay area in minimal time. The results show that the developed framework can efficiently construct continuous paths of heterogeneous vehicles by accommodating operational constraints via an FMM algorithm.

Recommended citation: J. Kim, H. -J. Park, A. Penumarti and J. Shin, "Fast Marching based Rendezvous Path Planning for a Team of Heterogeneous Vehicles," in IEEE Access, doi: 10.1109/ACCESS.2024.3444314.
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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.

EML4930: Autonomous Vehicles – Teaching Assistant

Undergraduate Course - Special Topics, University of Florida, Mechanical and Aerospace Department, 2023

This class taught students the fundamentals of programming a autonomous ground vehicle. It included working with feedback controllers, and sensors such as LiDAR, IMU and wheel encoders. The class was taught using the Robot Operating System (ROS).