Name
Abstract | ||
|---|---|---|
Current pig house cleaning procedures are hazardous to the health of farm workers, and yet necessary if the spread of disease between batches of animals is to be satisfactorily controlled. Autonomous cleaning using robot technology offers salient benefits. This paper addresses the feasibility of designing a vision-based system to locate dirty areas and subsequently direct a cleaning robot to remove dirt. Novel results include the characterisation of the spectral properties of real surfaces and dirt in a pig house and the design of illumination to obtain discrimination of clean from dirty areas with a low probability of misclassification. A Bayesian discriminator is shown to be efficient in this context and implementation of a prototype tool demonstrates the feasibility of designing a low-cost vision-based sensor for autonomous cleaning. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1155/ASP.2005.2005 | EURASIP J. Adv. Sig. Proc. |
Keywords | Field | DocType |
vision-based system,low-cost vision-based sensor,bayesian discriminator,autonomous pig house cleaning,autonomous cleaning,robot technology,farm worker,cleaning robot,pig house,current pig house,dirty area,computer vision | Spectral properties,Computer vision,Image sensor,Computer science,Vision based,Dirt,Artificial intelligence,Robot,Robotics,Machine learning | Journal |
Volume | Issue | ISSN |
2005, | 13 | 1687-6180 |
Citations | PageRank | References |
2 | 0.40 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ian Braithwaite | 1 | 2 | 0.40 |
| Mogens Blanke | 2 | 81 | 18.78 |
| Guo-Qiang Zhang | 3 | 2 | 0.40 |
| Jens Michael Carstensen | 4 | 83 | 14.27 |