Detail publikace

Collision Avoidance for ATEROS Robotic System

LIGOCKI, A.

Originální název

Collision Avoidance for ATEROS Robotic System

Anglický název

Collision Avoidance for ATEROS Robotic System

Jazyk

en

Originální abstrakt

This paper describes the details of a collision avoidance algorithm for an ATEROS robotic system. The solution, developed and tested on the Orpheus robotic platform is based on a Velodyne HDL-32E laser scanner. The LiDAR point cloud input data are filtered to remove data redundancy and clustered to separate possible collision objects from the background. Based on prior environment knowledge and the current LiDAR scan, the surrounding occupancy grid map is estimated, and the planned path is validated against possible collision. In the case of a non-zero probability that the robot collides with an obstacle, a new path is proposed by the A* algorithm. Subsequently, the newly estimated waypoints are relaxed, and the mission plan is updated.

Anglický abstrakt

This paper describes the details of a collision avoidance algorithm for an ATEROS robotic system. The solution, developed and tested on the Orpheus robotic platform is based on a Velodyne HDL-32E laser scanner. The LiDAR point cloud input data are filtered to remove data redundancy and clustered to separate possible collision objects from the background. Based on prior environment knowledge and the current LiDAR scan, the surrounding occupancy grid map is estimated, and the planned path is validated against possible collision. In the case of a non-zero probability that the robot collides with an obstacle, a new path is proposed by the A* algorithm. Subsequently, the newly estimated waypoints are relaxed, and the mission plan is updated.

Dokumenty

BibTex


@inproceedings{BUT156703,
  author="Adam {Ligocki}",
  title="Collision Avoidance for ATEROS Robotic System",
  annote="This paper describes the details of a collision avoidance algorithm for an ATEROS robotic system. The solution, developed and tested on the Orpheus robotic platform is based on a Velodyne HDL-32E laser scanner. The LiDAR point cloud input data are filtered to remove data redundancy and clustered to separate possible collision objects from the background. Based on prior environment knowledge and the current LiDAR scan, the surrounding occupancy grid map is estimated, and the planned path is validated against possible collision. In the case of a non-zero probability that the robot collides with an obstacle, a new path is proposed by the A* algorithm. Subsequently, the newly estimated waypoints are relaxed, and the mission plan is updated.",
  address="Vysoké učení technické vBrně, Fakulta elektrotechniky a komunikačních technologií",
  booktitle="Proceedings of the 25thConference STUDENT EEICT 2019",
  chapter="156703",
  howpublished="online",
  institution="Vysoké učení technické vBrně, Fakulta elektrotechniky a komunikačních technologií",
  year="2019",
  month="april",
  pages="576--580",
  publisher="Vysoké učení technické vBrně, Fakulta elektrotechniky a komunikačních technologií",
  type="conference paper"
}