Occupancy grid mapping

Occupancy grid mapping is a technique used to represent an environment by dividing it into a grid of evenly spaced cells, each of which is assigned a binary random variable indicating whether it is occupied or unoccupied based on the presence of obstacles detected by a range sensor. The resulting mapping approach is known as occupancy-grid mapping.From: Smart Autonomous Aircraft [2019], Development of an efficient laser grid mapping technique: P-SLAM [2019]

Sensors for Autonomous Vehicles in Infrastructure Inspection Applications

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Published in Diego Galar, Uday Kumar, Dammika Seneviratne, Robots, Drones, UAVs and UGVs for Operation and Maintenance, 2020

Diego Galar, Uday Kumar, Dammika Seneviratne

Occupancy grid mapping is used for navigation and localization of autonomous vehicles in dynamic environments (see Figure 4.28). Sensor data from cameras and LiDAR are fused. The camera provides high-level 2D information, such as color, intensity, density, and edge information, and LiDAR provides 3D point cloud data. The usual approach to occupancy grid mapping is to independently filter all grid cells. However, the new trend is to use super pixels for the grid map; the grid cells occupied by an obstacle are included (Oh & Kang, 2016).

Development of an efficient laser grid mapping technique: P-SLAM

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Published in International Journal of Image and Data Fusion, 2019

Ravinder Singh, K. S. Nagla

Occupancy grid mapping represents the environment in the form of an evenly spaced grid cell having filled with binary random variables which are occupied or unoccupied corresponding to the presence of the obstacle in the field of view of range sensor (Park et al. 2010, Pajaziti 2014, Singh and Nagla 2018a).

Occupancy grid mapping

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Sensors for Autonomous Vehicles in Infrastructure Inspection Applications

Development of an efficient laser grid mapping technique: P-SLAM