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Obstacle fusion algorithms usually perform obstacle association and gating in order to improve the obstacle position if it was detected by multiple sensors. However, this strategy is not common in multi sensor occupancy grid fusion. Thus, the quality of the fused grid, in terms of obstacle position accuracy, largely depends on the sensor with the lowest accuracy. In this paper an efficient method...
Environment sensors with a narrow vertical field of view often fail to detect obstacles with a small vertical extent from close range. Because an inverse beam sensor model infers free space when there was no measurement, those obstacles are deleted from an occupancy grid eventhough they have been observed in past measurements. This is extremely critical if the car is driving autonomously. Our approach...
The ability to perceive a robot's local environment is one of the main challenges in the development of mobile ground robots. Here, we present a robust model-based approach for detection and tracking of road networks in rural terrain. To get a rich environment representation, we fuse the complementary data provided by a 3D LIDAR and an active camera platform into an accumulated, colored 3D elevation...
The ability to perceive a robot's local environment is one of the main challenges in the development of mobile ground robots. Here, we present a robust model-based approach for detection and tracking of road networks in rural terrain. To get a rich environment representation, we fuse the complementary data provided by a 3D LIDAR and an active camera platform into an accumulated, colored 3D elevation...
In this paper we describe a novel approach to model-based monocular vehicle tracking out of a moving vehicle using active vision. The designed algorithm can cope with cluttered color images, complex lighting conditions as well as partial occlusion of the leading vehicle and is able to detect and track a vehicle even within unstructured offroad environments. Thanks to the used 3D model which describes...
In this paper we describe a novel approach to autonomous dirt road following. The algorithm is able to recognize highly curved roads in cluttered color images quite often appearing in offroad scenarios. To cope with large curvatures we apply gaze control and model the road using two different clothoid segments. A Particle Filter incorporating edge and color intensity information is used to simultaneously...
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