Jiménez Bermejo, Víctor (Consejo Superior de Investigaciones Científicas), Godoy, Jorge (Centre for Automation and Robotics (UPM-CSIC)), Artuñedo, Antonio (Centre for Automation and Robotics (CSIC-UPM)), Villagra, Jorge (Centre for Automation and Robotics (CSIC-UPM))

Categorized Grid and Unknown Space Causes for LiDAR-Based Dynamic Occupancy Grids

Scheduled for presentation during the Regular Session "LiDAR-based perception" (FrBT6), Friday, September 27, 2024, 13:50−14:10, Salon 14

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 3, 2024

Abstract

Occupancy Grids have been widely used for perception of the environment as they allow to model the obstacles in the scene, as well as free and unknown space. Recently, there has been a growing interest in the unknown space due to the necessity of better understanding the situation. Despite OGs have received numerous extensions over the years to address emerging needs, currently, few works go beyond the delimitation of the unknown space area and seek to incorporate additional information. This work builds upon the already well-established LiDAR-based Dynamic Occupancy Grid to introduce a complementary Categorized Grid that conveys its estimation using semantic labels while adding new insights into the possible causes of unknown space. The proposed categorization first divides the space by occupancy and then further categorizes the occupied and unknown space. Occupied space is labeled based on its dynamic state and reliability, while the unknown space is labeled according to its possible causes, whether they stem from the perception system's inherent constraints, limitations induced by the environment, or other causes. The proposed Categorized Grid is showcased in real-world scenarios demonstrating its usefulness for better situation understanding.