Recovering heading for visually-guided navigation

Recovering heading for visually-guided navigation.

We present a model for recovering the direction of heading of an observer who is moving relative to a scene that may contain self-moving objects. The model builds upon an algorithm proposed by Rieger and Lawton, based on earlier work by Longuet-Higgins and Prazdny. The algorithm uses velocity differences computed in regions of high depth variation to locate the focus of expansion, which indicat...

Visually Guided Navigation

Visually-Guided Navigation by Comparing Edge Images

We present a method for navigating a robot from an initial position to a speciied landmark in its visual eld, using a sequence of monocular images. The location of the landmark with respect to the robot is determined based on the change in size and location of the landmark in the image, as a function of the motion of the robot. The change in size and location of the landmark in the image are de...

Natural Landmark Detection for Visually-Guided Robot Navigation

The main difficulty to attain fully autonomous robot navigation outdoors is the fast detection of reliable visual references, and their subsequent characterization as landmarks for immediate and unambiguous recognition. Aimed at speed, our strategy has been to track salient regions along image streams by just performing on-line pixel sampling. Persistent regions are considered good candidates f...

Comparing parallel hardware architectures for visually guided robot navigation

1Computer Engineering Group, Faculty of Technology, Bielefeld University, Universitätsstraße 25, 33615 Bielefeld, Germany 2Simulation Lab Neuroscience — Bernstein Facility for Simulation and Database Technology, Institute for Advanced Simulation, Jülich Aachen Research Alliance, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany 3DFKI GmbH, Robotics Innovation Center, Robert-Hooke-Straße 1, 2...