1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.RO2023
Efficiently Identifying Hotspots in a Spatially Varying Field with Multiple Robots
Varun Suryan, Pratap Tokekar
In this paper, we present algorithms to identify environmental hotspots using mobile sensors. We examine two approaches: one involving a single robot and another using multiple rob…
cs.RO2019
Learning a Spatial Field in Minimum Time with a Team of Robots
Varun Suryan, Pratap Tokekar
We study an informative path-planning problem where the goal is to minimize the time required to learn a spatially varying entity. We use Gaussian Process (GP) regression for learn…
cs.RO2017★ 1 cited
Multi-Fidelity Reinforcement Learning with Gaussian Processes
Varun Suryan, Nahush Gondhalekar, Pratap Tokekar
We study the problem of Reinforcement Learning (RL) using as few real-world samples as possible. A naive application of RL can be inefficient in large and continuous state spaces.…