Nagavarapu, S. C., Abraham, A., Selvaraj, N. M., & Dauwels, J. (2023, December 11). A Dynamic Object Removal and Reconstruction Algorithm for Point Clouds. 2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI). https://doi.org/10.1109/soli60636.2023.10425733
Abstract:
Autonomous vehicles (AV) are one of the greatest technological advancements of this decade and a giant leap in the transportation industry and mobile robotics. Autonomous vehicles face several major challenges in achieving higher levels of autonomy. One of these is to find a fast and reliable algorithm to process the sensor data so that the simultaneous localization and mapping (SLAM) algorithms run in real-time to achieve autonomous navigation. The major limitation of the SLAM algorithm, especially while building a map is to have static environmental features, i.e. without any dynamic or moving objects. To achieve this, our paper introduces a novel algorithm to remove dynamic objects from point cloud data. The algorithm focuses on identifying and removing dynamic objects from sensor data, thereby creating a static scene suitable for traditional SLAM algorithms. Simulations conducted on the benchmark dataset demonstrate the algorithm's efficacy in successfully eliminating dynamic objects and reconstructing a stable static scene.
License type:
Publisher Copyright
Funding Info:
There was no specific funding for the research done