Time-of-Flight LiDAR-based Precise Mapping
This addresses the incremental challenge of improving mapping accuracy for robotics applications, focusing on cost efficiency.
The paper tackles the problem of obtaining accurate maps from noisy Time-of-Flight LiDAR sensor data by proposing a probabilistic map update method based on multiple robot explorations, which estimates the required number of exploration rounds to reduce hardware and time costs.
Last two decades, the problem of robotic mapping has made a lot of progress in the research community. However, since the data provided by the sensor still contains noise, how to obtain an accurate map is still an open problem. In this note, we analyze the problem from the perspective of mathematical analysis and propose a probabilistic map update method based on multiple explorations. The proposed method can help us estimate the number of rounds of robot exploration, which is meaningful for the hardware and time costs of the task.