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Combining Depth and Intensity Images to Produce Enhanced Object Detection for Use in a Robotic Colony

  • Steven BaldingEmail author
  • Darryl N. Davis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10454)

Abstract

Robotic colonies that can communicate with each other and interact with their ambient environments can be utilized for a wide range of research and industrial applications. However amongst the problems that these colonies face is that of the isolating objects within an environment. Robotic colonies that can isolate objects within the environment can not only map that environment in detail, but interact with that ambient space. Many object recognition techniques exist, however these are often complex and computationally expensive, leading to overly complex implementations. In this paper a simple model is proposed to isolate objects, these can then be recognize and tagged. The model will be using 2D and 3D perspectives of the perceptual data to produce a probability map of the outline of an object, therefore addressing the defects that exist with 2D and 3D image techniques. Some of the defects that will be addressed are; low level illumination and objects at similar depths. These issues may not be completely solved, however, the model provided will provide results confident enough for use in a robotic colony.

Keywords

Anchoring Robotic vision Sobel Depth map Robotic colony 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Faculty of Engineering and Computer ScienceUniversity of HullHullEngland

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