System Overview

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Testing the detection and recognition of objects

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Recognizing and manipulating objects is an important task for mobile robots  performing useful services in everyday environments. While existing techniques  for object recognition related to manipulation provide very good results even for  noisy and incomplete data, they are typically trained using data generated in an offline  process.Specifically, we develop an approach to building a 3D surface model of an unknown object based on data collected by a kinect sensor observing the robot’s hand moving the object.
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T u t o r i a l

If you are interested in obtaining more informations about in hand object modeling please have a look over the next tutorial. You can find the source code and also a briefly description about how to run the program . http://www.ros.org/wiki/model_completion
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My project : Objects Modelling

The ability to recognize objects and to localize them precisely is essential in all service robotic applications. One of the main challenges for service robots during operation lies in the handling of unavoidable uncertainties which originate from model sensor inaccuracies are characteristic for realistic application scenarios. ODUfinder is a perception system for autonomous service robots acting in human living environments. The perception system enables robots to detect and recognize large sets of textured objects of daily use .We need a robot object detection and recognition  system that can recognize thousands of objects by learning and using vocabulary three of SIFT descriptors . The usage of robots to aid humans is becoming more and more widespread, typically in the industry, but increasingly also in public services and in some cases, home applications too. Robots are starting to be more ...
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