Real-time Volume Estimation of Mass in Excavator Bucket with LiDAR Data

In the autonomous excavation task, the real-time estimation of the bucket filling rate and the volume of the excavated mass are essential feedbacks to measure the excavation quality. In this work, facilitated by the LiDAR and inclination sensors mounted on an autonomous excavator, we introduce an online method to calculate the volume of the mass in the excavator bucket during digging process. The LiDAR is mainly used for acquiring the 3D point clouds of the excavated mass and bucket, and the inclination sensors are utilized for localization acquisition of the bucket. In specific, a pre-process is first used to obtain the empty bucket model by scanning it with LiDAR. Then, to reduce the influence of the noises of the inclination sensors in the digging process, a registration algorithm is employed to transform the real-time captured point clouds of the bucket and excavated mass to the empty bucket model (obtained in the pre-process). Finally, based on the height map construction and point clouds interpolation, volume estimation algorithm is utilized to obtain the final results. Note that our method is validated in real-world scenarios, and the experiment results demonstrate the accuracy and reliability of our volume estimation scheme.