Robotics researcher specializing in information theory and spatial field reconstruction. I build robust simulation infrastructure using Linux, Docker, and the PX4 stack for autonomous systems research.
Expert in ROS2, Gazebo, containerized deployments, and Gaussian Process methods.
I'm a robotics researcher and simulation engineer focused on building autonomous systems that can intelligently sample and reconstruct spatial fields. My work bridges theory and practice, from Gaussian Process methods to production-ready containerized deployments.
Applying information-theoretic principles to optimize sampling strategies and sensor placement for environmental monitoring.
Working with stationary, non-stationary, and uncertain-input GP methods for robust spatial field reconstruction.
Building high-fidelity robotics simulations with PX4 SITL, Gazebo, and ROS2 for autonomous vehicle development.
Developing reproducible research infrastructure with Linux systems, Docker containerization, and automated deployments.
Rodney Staggers Jr*, Bharath Vedantha Desikan*, Jnaneshwar Das (*contributed equally)
We present a low-cost ($2,500) Autonomous Surface Vehicle (ASV), R/V Karin Valentine, for high-resolution aquatic field reconstruction. Our approach uses Gaussian Process regression with non-stationary Matérn kernels that adapt spatially to capture varying environmental dynamics across water bodies.
Research tools and simulation infrastructure for autonomous spatial sampling.
Autonomous Spatial Sampling
Complete simulation infrastructure for autonomous spatial field reconstruction using USVs. Features PX4 SITL integration, GP-based reconstruction with multiple methods (Standard GP, McHutchon NIGP, Girard), and a web-based control panel for running batch simulations.
Interested in collaboration or have questions about my research? Feel free to reach out.