- 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 exploration goal based on a
gain-cost ratio derived from the assumed 3D map coverage
at the particular node and the distance to it. The proposed
approach features a continuously-built graph with a decoupled
calculation of node gains using a computationally efficient ray
tracing method. The Next-Best View is evaluated while the robot
is pursuing a goal, which eliminates the need to wait for gain
calculation after reaching the previous goal and significantly
speeds up the exploration. Furthermore, a grid map is used to
determine theIn 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 exploration goal based on a
gain-cost ratio derived from the assumed 3D map coverage
at the particular node and the distance to it. The proposed
approach features a continuously-built graph with a decoupled
calculation of node gains using a computationally efficient ray
tracing method. The Next-Best View is evaluated while the robot
is pursuing a goal, which eliminates the need to wait for gain
calculation after reaching the previous goal and significantly
speeds up the exploration. Furthermore, a grid map is used to
determine the traversability between the nodes in the graph
while also providing a global plan for navigating towards
selected goals. Simulations compare the proposed approach
to state-of-the-art exploration algorithms and demonstrate its
superior performance.…

