Efficient Informative Path Planning via Normalized Utility in Unknown Environments Exploration

Exploration is an important aspect of autonomous robotics, whether it is for target searching, rescue missions, or reconnaissance in an unknown environment. In this paper, we propose a solution to efficiently explore the unknown environment by unmanned aerial vehicles (UAV). Innovatively, a topologi...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2022-11, Vol.22 (21), p.8429
Main Authors: Yu, Tianyou, Deng, Baosong, Gui, Jianjun, Zhu, Xiaozhou, Yao, Wen
Format: Article
Language:English
Subjects:
autonomous robot
Drone aircraft
Efficiency
Entropy
exploration
informative path planning
navigation
Path planning
Planning
Robotics
Robots
Searching
Topology
Unknown environments
Unmanned aerial vehicles
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Summary:Exploration is an important aspect of autonomous robotics, whether it is for target searching, rescue missions, or reconnaissance in an unknown environment. In this paper, we propose a solution to efficiently explore the unknown environment by unmanned aerial vehicles (UAV). Innovatively, a topological road map is incrementally built based on Rapidly-exploring Random Tree (RRT) and maintained along with the whole exploration process. The topological structure can provide a set of waypoints for searching an optimal informative path. To evaluate the path, we consider the information measurement based on prior map uncertainty and the distance cost of the path, and formulate a normalized utility to describe information-richness along the path. The informative path is determined in every period by a local planner, and the robot executes the planned path to collect measurements of the unknown environment and restructure a map. The proposed framework and its composed modules are verified in two 3-D environments, which exhibit better performance in improving the exploration efficiency than other methods.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22218429