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20212026
most citedMulti-UAV Adaptive Path Planning Using Deep Reinforcement Learning

6 citations · 6 across the 5 of their papers we have counts for

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cs.RO2026

UGV-Conditioned Multi-UAV Informative Planning on a Shared Exposure Belief

Lars Oerlemans, Moji Shi, Marija Popovic

Safe ground navigation in large, threat-augmented environments requires aerial support that actively reduces the risks that a ground vehicle faces along its route. Existing aerial…

cs.RO2026

MPPI-based Informative Trajectory Planning for Search and Capture of Drifting Targets with ASVs

Sanjeev Ramkumar Sudha, Marija Popović, Erlend M. Coates

Autonomous surface vehicles offer an efficient solution for environmental cleanup as well as search and rescue operations in open waters. Targets in these settings drift continuous…

cs.RO20236 cited

Multi-UAV Adaptive Path Planning Using Deep Reinforcement Learning

Jonas Westheider, Julius Rückin, Marija Popović

Efficient aerial data collection is important in many remote sensing applications. In large-scale monitoring scenarios, deploying a team of unmanned aerial vehicles (UAVs) offers i…

cs.RO2023

Graph-based View Motion Planning for Fruit Detection

Tobias Zaenker, Julius Rückin, Rohit Menon +2

Crop monitoring is crucial for maximizing agricultural productivity and efficiency. However, monitoring large and complex structures such as sweet pepper plants presents significan…

cs.RO2021

Adaptive Path Planning for UAV-based Multi-Resolution Semantic Segmentation

Felix Stache, Jonas Westheider, Federico Magistri +2

In this paper, we address the problem of adaptive path planning for accurate semantic segmentation of terrain using unmanned aerial vehicles (UAVs). The usage of UAVs for terrain m…