Autonomous robot exploration and map building for unknown environments is essential in a wide range of applications such as search and rescue, surveillance, military and other high risk scenarios. As the robot starts exploring its surroundings, it accumulatively builds a partial map of the environment composing of the areas that are currently known by the robot. In this work we present a new exploration and mapping solution that will capture the environment structure geometrically. The proposed Triangulation-Based exploration maps the environment using the Dynamic Triangulation Tree structure (DTT) developed in this study. Using triangles to store the geometry of the environment will significantly reduce the storage space required when compared to the occupancy grids used in many exploration and map building solutions. The efficiency of the proposed mapping structure is validated experimentally through simulations.
[1]
Steven M. LaValle,et al.
Distance-Optimal Navigation in an Unknown Environment Without Sensing Distances
,
2007,
IEEE Transactions on Robotics.
[2]
Lakmal D. Seneviratne,et al.
Mapping for Unknown Environments Using Triangulated Maps
,
2013,
2013 IEEE International Conference on Systems, Man, and Cybernetics.
[3]
Maria L. Gini,et al.
Good Experimental Methodologies for Robotic Mapping: A Proposal
,
2007,
Proceedings 2007 IEEE International Conference on Robotics and Automation.
[4]
Lakmal D. Seneviratne,et al.
Frontier-based exploration for unknown environments using incremental triangulation
,
2013,
2013 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR).
[5]
Sebastian Thrun,et al.
Robotic mapping: a survey
,
2003
.