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This paper describes a landmark-based algorithm for map matching, and demonstrates its use in eeciently combining topological maps of indoor environments built by autonomous mobile robots. Results of the rst implementation are presented, in which t wo robots with diierent m e c hanics and sensory capabilities independently explore their environments with no(More)
We propose a method to detect and identify faults in wheeled mobile robots. The idea behind the method is to use adaptive estimation to predict the outcome of several faults, and to learn them collectively as a failure pattern. Models of the system behavior under each type of fault are embedded in multiple parallel Kalman Filter (KF) estimators. Each KF is(More)
We present a behavior-based technique for incremental on-line mapping and autonomous navigation for mobile robots, speciically geared for time-critical indoor exploration tasks. The experimental platform used is a Pioneer AT mobile robot endowed with seven sonar transducers, a drift-stabilized gyro, a compass and a pan-tilt color camera. While the thrust of(More)
Most image registration problems are formulated in an asymmetric fashion. Given a pair of images, one is implicitly or explicitly regarded as a template and warped onto the other to match as well as possible. In this paper, we focus on this seemingly arbitrary choice of the roles and reveal how it may lead to biased warp estimates in the presence of(More)
Active Appearance Models (AAM) are compact representations of the shape and appearance of objects. Fitting AAMs to images is a difficult, non-linear optimization task. Traditional approaches minimize the L2 norm error between the model instance and the input image warped onto the model coordinate frame. While this works well for high resolution data, the(More)
During the performance optimization of a computer vision system, developers frequently run into platform-level inefficiencies and bottlenecks that can not be addressed by traditional methods. OpenVX is designed to address such system-level issues by means of a graph-based computation model. This approach differs from the traditional acceleration of one-off(More)
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