Monitoring and mapping with robot swarms for agricultural applications
Dario Albani, Joris IJsselmuiden, Ramon Haken, Vito Trianni
- Year
- 2017
- Citations
- 128
Abstract
Robotics is expected to play a major role in the agricultural domain, and often multi-robot systems and collaborative approaches are mentioned as potential solutions to improve efficiency and system robustness. Among the multi-robot approaches, swarm robotics stresses aspects like flexibility, scalability and robustness in solving complex tasks, and is considered very relevant for precision farming and large-scale agricultural applications. However, swarm robotics research is still confined into the lab, and no application in the field is currently available. In this paper, we describe a roadmap to bring swarm robotics to the field within the domain of weed control problems. This roadmap is implemented within the experiment SAGA, founded within the context of the ECORD++ EU Project. Together with the experiment concept, we introduce baseline results for the target scenario of monitoring and mapping weed in a field by means of a swarm of UAVs.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002