9 citations · 9 across the 2 of their papers we have counts for
7 papers · 1 filter
STAIR: Semantic-Targeted Active Implicit Reconstruction
Liren Jin, Haofei Kuang, Yue Pan +2
Many autonomous robotic applications require object-level understanding when deployed. Actively reconstructing objects of interest, i.e. objects with specific semantic meanings, is…
Semi-Supervised Active Learning for Semantic Segmentation in Unknown Environments Using Informative Path Planning
Julius Rückin, Federico Magistri, Cyrill Stachniss +1
Semantic segmentation enables robots to perceive and reason about their environments beyond geometry. Most of such systems build upon deep learning approaches. As autonomous robots…
Perceptual Factors for Environmental Modeling in Robotic Active Perception
David Morilla-Cabello, Jonas Westheider, Marija Popovic +1
Accurately assessing the potential value of new sensor observations is a critical aspect of planning for active perception. This task is particularly challenging when reasoning abo…
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…
3D Lidar Reconstruction with Probabilistic Depth Completion for Robotic Navigation
Yifu Tao, Marija Popović, Yiduo Wang +3
Safe motion planning in robotics requires planning into space which has been verified to be free of obstacles. However, obtaining such environment representations using lidars is c…
Dynamic System Identification, and Control for a cost effective open-source VTOL MAV
Inkyu Sa, Mina Kamel, Raghav Khanna +3
This paper describes dynamic system identification, and full control of a cost-effective vertical take-off and landing (VTOL) multi-rotor micro-aerial vehicle (MAV) --- DJI Matrice…