Receding Horizon "Next-Best-View" Planner for 3D Exploration
By Andreas Bircher, Mina Kamel, K. Alexis, Helen Oleynikova, Roland Yves Siegwart. 2016
713 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Luca Carlone
- Wolfram Burgard
- Shaojie Shen
- Dieter Fox
- Niko Sünderhauf
- Michael Milford
- Roland Yves Siegwart
- Davide Scaramuzza
In Computer Vision and Pattern Recognition
- Lei Tai
- Luc Van Gool
- Vladlen Koltun
- Trevor Darrell
- Jitendra Malik
- Sergey Levine
- Andrew Zisserman
- Xiaogang Wang
Citations in the corpus
- The limits and potentials of deep learning for robotics (2018, background): “Some work is undertaken in the area of next-best view-point prediction to improve object detection [5], [25], [73], [130] or path planning for exploration on a mobile robot [14], but a more holistic approach to active scene understanding is still missing from current research.”
- FUEL: Fast UAV Exploration Using Incremental Frontier Structure and Hierarchical Planning (2020, methodology): “Three methods are compared: the NBVP [12], the classic frontier method [7] and the rapid frontier method [1].”
- A Comprehensive Review of Coverage Path Planning in Robotics Using Classical and Heuristic Algorithms (2021, background): “O ( n log n+ n log ( V/r3 ) ( NM/r4 + 1/r3 )) , where N is the number of horizontal rays,M is the number of vertical rays, r is the map resolution and V is the volume of the environment to be explored [122].”
- An Efficient Sampling-Based Method for Online Informative Path Planning in Unknown Environments (2019, methodology): “We compare our method to the receding horizon NBV planner (RH-NBVP) presented in [1] and the more recent autonomous exploration planner (AEP) [16].”
- weedNet: Dense Semantic Weed Classification Using Multispectral Images and MAV for Smart Farming (2017, background): “, monitoring- [3] or exploration-based [4], for informed data collection and complete”
- A Survey on Active Simultaneous Localization and Mapping: State of the Art and New Frontiers (2022, background): “[46] ROVIO [47] & mapping Stereo & IMU Octomap MPC RRT paths Coverage & distance Sim.”
- Survey on Computer Vision for UAVs: Current Developments and Trends (2017, background): “In [149] a path planning algorithm for autonomous exploration in bounded unknown environments has been presented.”