Leveraging Predictive Models for Adaptive Sampling of Spatiotemporal Fluid Processes

no code implementations • 3 Apr 2023 • Sandeep Manjanna, Tom Z. Jiahao, M. Ani Hsieh

Our algorithm makes use of the predictions from a learned prediction model to plan a path for an autonomous vehicle to adaptively and efficiently survey the region of interest.

Reinforcement Learning for Agile Active Target Sensing with a UAV

no code implementations • 16 Dec 2022 • Harsh Goel, Laura Jarin Lipschitz, Saurav Agarwal, Sandeep Manjanna, Vijay Kumar

Active target sensing is the task of discovering and classifying an unknown number of targets in an environment and is critical in search-and-rescue missions.

reinforcement-learning Reinforcement Learning (RL)

Scalable Multirobot Planning for Informed Spatial Sampling

no code implementations • 20 May 2021 • Sandeep Manjanna, M. Ani Hsieh, Gregory Dudek

This paper presents a distributed scalable multi-robot planning algorithm for informed sampling of quasistatic spatial fields.

Autonomous Vehicles

Reinforcement Learning with Non-uniform State Representations for Adaptive Search

no code implementations • 15 Jun 2019 • Sandeep Manjanna, Herke van Hoof, Gregory Dudek

In this paper, we present a search algorithm that generates efficient trajectories that optimize the rate at which probability mass is covered by a searcher.

reinforcement-learning Reinforcement Learning (RL)