Corpus ID: 236772556

Rapidly-Exploring Random Graph Next-Best View Exploration for Ground Vehicles

@article{Steinbrink2021RapidlyExploringRG,
  title={Rapidly-Exploring Random Graph Next-Best View Exploration for Ground Vehicles},
  author={Marco Steinbrink and Philipp Koch and B. Jung and S. May},
  journal={ArXiv},
  year={2021},
  volume={abs/2108.01012}
}
In this paper, a novel approach is introduced which utilizes a Rapidly-exploring Random Graph to improve sampling-based autonomous exploration of unknown environments with unmanned ground vehicles compared to the current state of the art. Its intended usage is in rescue scenarios in large indoor and underground environments with limited teleoperation ability. Local and global sampling are used to improve the exploration efficiency for large environments. Nodes are selected as the next… Expand

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References

SHOWING 1-10 OF 25 REFERENCES
Receding Horizon "Next-Best-View" Planner for 3D Exploration
TLDR
A novel path planning algorithm for the autonomous exploration of unknown space using aerial robotic platforms that employs a receding horizon “next-best-view” scheme and its good scaling properties enable the handling of large scale and complex problem setups. Expand
Graph-based Path Planning for Autonomous Robotic Exploration in Subterranean Environments
TLDR
This paper presents a novel strategy for autonomous graph-based exploration path planning in subterranean environments that is structured around a bifurcated local- and global-planner architecture. Expand
Online inspection path planning for autonomous 3D modeling using a micro-aerial vehicle
  • Soohwan Song, Sungho Jo
  • Engineering, Computer Science
  • 2017 IEEE International Conference on Robotics and Automation (ICRA)
  • 2017
TLDR
An online inspection algorithm that consistently provides an optimal coverage path toward the next-best-view (NBV) in real time is proposed and outperforms the other approaches in both exploration and 3D modeling scenarios. Expand
An Efficient Sampling-Based Method for Online Informative Path Planning in Unknown Environments
TLDR
A new RRT*-inspired online informative path planning algorithm that continuously expands a single tree of candidate trajectories and rewires nodes to maintain the tree and refine intermediate paths, allowing the algorithm to achieve global coverage and maximize the utility of a path in a global context, using a single objective function. Expand
Efficient Autonomous Exploration Planning of Large-Scale 3-D Environments
TLDR
This letter presents a method that combines both approaches, with FEP as a global exploration planner and RH-NBVP for local exploration, and presents techniques to estimate potential information gain faster, to cache previously estimated gains and to exploit these to efficiently estimate new queries. Expand
An incremental sampling-based approach to inspection planning: the rapidly exploring random tree of trees
TLDR
A new algorithm, called rapidly exploring random tree of trees (RRTOT) is proposed, that aims to address the challenge of planning for autonomous structural inspection by computes inspection paths that provide full coverage. Expand
Autonomous robotic exploration based on multiple rapidly-exploring randomized trees
TLDR
This paper presents a new exploration strategy based on the use of multiple Rapidly-exploring Random Trees (RRTs), which uses local and global trees for detecting frontier points, which enables efficient robotic exploration. Expand
Autonomous Robotic Exploration Based on Frontier Point Optimization and Multistep Path Planning
TLDR
This paper proposes a strategy based on frontier point optimization and multistep path planning and presents a random frontier points’ optimization (RFPO) algorithm to select the frontier point with the highest evaluation value as the target frontier point. Expand
Tree-based search of the next best view/state for three-dimensional object reconstruction
TLDR
This article directly finds the state of the robot whose corresponding sensor view observes the object by directly guiding the search with a tree structure based on a rapidly exploring random tree overcoming previous sampling techniques. Expand
A frontier-based approach for autonomous exploration
  • Brian Yamauchi
  • Computer Science
  • Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97. 'Towards New Computational Principles for Robotics and Automation'
  • 1997
TLDR
A method for detecting frontiers in evidence grids and navigating to these frontiers, regions on the boundary between open space and unexplored space, is described and a technique for minimizing specular reflections inevidence grids using laser-limited sonar is introduced. Expand
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