【文件属性】：
文件名称：Obstacle Detection and Tracking for the Urban Challenge 障碍物检测跟踪
文件大小：369KB
文件格式：PDF
更新时间：2021-03-01 04:37:43
Obstacle Detection， Tracking
This paper describes the obstacle detection and
tracking algorithms developed for Boss, which is Carnegie Mellon
University ’s winning entry in the 2007 DARPA Urban Challenge.
We describe the tracking subsystem and show how it functions in
the context of the larger perception system. The tracking subsystem
gives the robot the ability to understand complex scenarios of
urban driving to safely operate in the proximity of other vehicles.
The tracking system fuses sensor data from more than a dozen
sensors with additional information about the environment to
generate a coherent situational model. A novel multiple-model
approach is used to track the objects based on the quality of the
sensor data. Finally, the architecture of the tracking subsystem
explicitly abstracts each of the levels of processing. The subsystem
can easily be extended by adding new sensors and validation
algorithms.