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In this paper, we propose a novel appearance-based approach for topological mapping based on a hierarchical decomposition of the environment. In our map, images with similar visual properties are grouped together in nodes, which are represented by means of an average global descriptor and an index of binary features based on a bag-of-words online approach. Each image is represented by means of a global...
In this paper, we present a method for vision-based place recognition in environments with a high content of similar features and that are prone to variations in illumination. The high similarity of features makes difficult the disambiguation between two different places. The novelty of our method relies on using the Bag of Words (BoW) approach to derive an image descriptor from a set of relevant...
A sequence of 3-D motion images of a human facing an imitator [i.e., a humanoid robot (HR)] is captured using a stereo-vision system installed on the HR. After acquiring enough motion sequences via image ratio and background registration, the estimation of seven feature points (i.e., the head, two arm tips, two leg tips, and two elbows) of the human are obtained. Using five feature points (i.e., the...
The recognition of places that have already been visited is a fundamental requirement for a mobile robot. This particularly concerns the detection of loop closures while mapping environments as well as the global localization w.r.t. to a prior map. This paper introduces a novel solution to place recognition with 2D LIDAR scans. Existing approaches utilize descriptors covering the local appearance...
One of the main important parts in the robot vision system of the mushroom harvesting robot is to detect mushroom damage either caused by microbial or mechanical origin. Mushrooms must be classified as healthy or unhealthy to ensure proper handling and maximize crop yield. To solve the problem of identification, a fast and non-destructive method, Support Vector Machine (SVM), is applied to improve...
Topological localization is a problem in mobile robotics that implies the ability of an agent to self locate in an environment. In this paper, we approach the task of topological localization without using a temporal continuity of the images of the places the robot has been. The environment is represented by an office under different illumination settings acquired with a perspective camera mounted...
We present an approach to automatically learn the visual appearance of an environment in terms of object classes. The procedure is totally unsupervised, incremental, and can be executed in real time. The traversability property of an unseen object is also learnt without human supervision by the interaction between the robot and the environment. An incremental version of affinity propagation, a state-of-the-art...
In this research, we developed a visual inspection robot with human consciousness of attention based on body and sight motions. This robot could inspect cast metal object that is irregular both in illumination reflection and surface structure. We capture in advance images of body and sight motions of inspector performance by using 3D motion capture system and gaze analysis system, and analyzed the...
In this paper we present a system for appearance-based topological mapping and localisation using vision data. The algorithms are designed for robots which are equipped with FPGA cameras. Such cameras do not provide the entire image to the robot but simple image features like colour histograms.
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