Recognition by Linear Combinations of Models
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part I
Bilinear coons patch image warping
Graphics gems IV
Mapping a manifold of perceptual observations
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
International Journal of Computer Vision
Recovering Shading from Color Images
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Editorial: Mobile robotics in the UK and worldwide: Fast changing, and as exciting as ever
Robotics and Autonomous Systems
Robust Appearance Based Visual Route Following for Navigation in Large-scale Outdoor Environments
International Journal of Robotics Research
Expert Systems with Applications: An International Journal
Three 2D-warping schemes for visual robot navigation
Autonomous Robots
Image-based homing navigation with landmark arrangement matching
Information Sciences: an International Journal
Fuzzy embedded mobile robot systems design through the evolutionary PSO learning algorithm
WSEAS TRANSACTIONS on SYSTEMS
Analyzing the effect of landmark vectors in homing navigation
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Robotics and Autonomous Systems
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In this paper, we present a method that uses panoramic images to perform long-range navigation as a succession of short-range homing steps along a route specified by appearances of the environment of the robot along the route. Our method is different from others in that it does not extract any features from the images and only performs simple image processing operations. The method does only make weak assumptions about the surroundings of the robot, assumptions that are discussed. Furthermore, the method uses a technique borrowed from computer graphics to simulate the effect in the images of short translations of the robot to compute local motion parameters. Finally, the proposed method shows that it is possible to perform navigation without explicitly knowing where the destination is nor where the robot currently is. Results in our Lab are presented that show the performance of the proposed system.