Detecting and tracking vehicles is crucial for safe operation of Unmanned Ground Vehicles (UGVs), but is challenging in cluttered, real-world environments. Here we present a method for discriminating vehicles from clutter found in natural terrain such as foliage, steep slopes, rock-outcrops, etc. Our method relies on a scanning LADAR and combines an obstacle detector and tracker, a vehicle modeling scheme, and a Support Vector-based discriminator. The output of our real-time system is a list of labeled obstacles and vehicles along with their positions, sizes and velocity estimates. This is used by a planner to enable autonomous navigation in the presence of other vehicles and significant clutter. We provide a quantitative analysis of the performance of our algorithm.
Ladar-Based Vehicle Detection and Tracking in Cluttered Environments
2008
8 pages
Report
No indication
English
Computers, Control & Information Theory , Infrared & Ultraviolet Detection , Bionics & Artificial Intelligence , Detection , Ground vehicles , Unmanned , Optical radar , Clutter , Tracking , Autonomous navigation , Discrimination , Symposia , Algorithms , Scanning , Robots , Ugv(Unmanned ground vehicles) , Ladar , Component reports
PCRLB for Tracking in Cluttered Environments: Measurement Sequence Conditioning Approach
Online Contents | 2006
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