Image-based path planning for outdoor mobile robots

被引:5
|
作者
Ollis, Mark [2 ]
Huang, Wesley H. [1 ]
Happold, Michael [3 ]
Stancil, Brian A. [1 ]
机构
[1] Appl Percept Inc, 220 Execut Dr,Suite 400, Cranberry Township, PA 16066 USA
[2] Lockheed Martin, Bethesda, MD USA
[3] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
关键词
D O I
10.1109/ROBOT.2008.4543623
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Traditionally, path planning for field robotic systems is performed in Cartesian space: sensor readings are transformed into terrain costs in a (Cartesian) costmap, and a path to the goal is planned in that map. In this paper, we propose a new approach: planning a path for the robot in the image-space of an on-board camera. We apply a learned color-to-cost mapping to transform a raw image into a cost-image, which then undergoes a pseudo-configuration-space transform. We search in the resulting cost-image for a path to the projected goal point in the image. One benefit of our approach is the ability to react to obstacles at ranges well beyond our 3D sensor range - independent testing has confirmed our system has effectively reacted to obstacles at a range of 93 to while our stereo sensor provides reliable data only up to 5 m away. We describe the details of our technique and the results from testing under the DARPA LAGR and UPI programs.
引用
收藏
页码:2723 / +
页数:2
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