Authors:
Shotaro Muro
1
;
Yohei Matsui
1
;
Masafumi Hashimoto
2
and
Kazuhiko Takahashi
2
Affiliations:
1
Graduate School of Doshisha University, Kyotanabe, Kyoto 6100321 and Japan
;
2
Faculty of Science and Engineering, Doshisha University, Kyotanabe, Kyoto 6100321 and Japan
Keyword(s):
Moving-object Tracking, Lidar, Two-wheeled Vehicle, Distortion Correction, Map Subtraction.
Related
Ontology
Subjects/Areas/Topics:
Image Processing
;
Informatics in Control, Automation and Robotics
;
Intelligent Transportation Technologies and Systems
;
Mechatronics Systems
;
Perception and Awareness
;
Robotics and Automation
;
Sensors Fusion
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
This paper presents a tracking (estimating position, velocity and size) of moving objects, such as cars, two-wheeled vehicles, and pedestrians, using a multilayer lidar mounted on a two-wheeled vehicle. The vehicle obtains its own pose (position and attitude angle) by on-board global navigation satellite system/inertial navigation system (GNSS/INS) unit and corrects the distortion in the lidar-scan data by interpolating the pose information. The corrected lidar-scan data is mapped onto 3D voxel map represented in the world coordinate frame. Subsequently, the vehicle extracts the interested lidar-scan data from the current lidar-scan data using the normal distributions transform (NDT) scan matching based map-subtraction method. The extracted scan data are mapped onto an elevation map, and moving objects are detected based on an occupancy grid method. Finally, detected moving objects are tracked based on the Bayesian Filter. Experimental results show the performance of the proposed met
hod.
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