Combining depth and intensity images to produce enhanced object detection for use in a robotic colony

Balding, Steven; Davis, Darryl N.

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 de-tail, but interact with that ambient space. Many object recognition techniques ex-ist, 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.

Citation

Balding, S., & Davis, D. N. (2017). Combining depth and intensity images to produce enhanced object detection for use in a robotic colony. Lecture notes in computer science, 10454, 115-125. https://doi.org/10.1007/978-3-319-64107-2_10

• Journal Article Type: Article
• Acceptance Date: May 5, 2017
• Online Publication Date: Jul 20, 2017
• Publication Date: Jul 20, 2017
• Deposit Date: Jul 11, 2017
• Publicly Available Date: Jul 20, 2017
• Journal: Lecture notes in computer science : Lecture notes in artificial intelligence
• Print ISSN: 0302-9743
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 10454
• Pages: 115-125
• Series Title: Lecture notes in computer science
• Series Number: 10454
• Book Title: Towards autonomous robotic systems
• ISBN: 9783319641065; 9783319641072
• DOI: https://doi.org/10.1007/978-3-319-64107-2_10
• Keywords: Anchoring; Robotic vision; Sobel; Depth map; Robotic colony
• Public URL: https://hull-repository.worktribe.com/output/453491
• Publisher URL: https://link.springer.com/chapter/10.1007/978-3-319-64107-2_10
• Additional Information: Authors' accepted manuscript of article:Balding S., Davis D.N. (2017) Combining Depth and Intensity Images to Produce Enhanced Object Detection for Use in a Robotic Colony. In: Gao Y., Fallah S., Jin Y., Lekakou C. (eds) Towards Autonomous Robotic Systems. TAROS 2017. Lecture Notes in Computer Science, vol 10454. Springer, Cham. The final publication is available https://link.springer.com/chapter/10.1007/978-3-319-64107-2_10
• Contract Date: Jul 11, 2017