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Julius Rückin

4 papers hereh-index 14 citations1 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.RO4

identity via Semantic Scholar / OpenAlex

activity
20212024
most citedMulti-UAV Adaptive Path Planning Using Deep Reinforcement Learning

6 citations · 7 across the 3 of their papers we have counts for

collaborators
Showing cs.ROShow all

4 papers · 1 filter

cs.RO2024

Learning-based Methods for Adaptive Informative Path Planning

Marija Popovic, Joshua Ott, Julius Rückin +1

Adaptive informative path planning (AIPP) is important to many robotics applications, enabling mobile robots to efficiently collect useful data about initially unknown environments…

cs.RO2023★ 6 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★ 1 cited

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 Informative Path Planning Using Deep Reinforcement Learning for UAV-based Active Sensing

Julius Rückin, Liren Jin, Marija Popović

Aerial robots are increasingly being utilized for environmental monitoring and exploration. However, a key challenge is efficiently planning paths to maximize the information value…

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