Multi-Robot Item Delivery and Foraging: Two Sides of a Coin
Somchaya Liemhetcharat, Rui-Jun Yan, Keng Peng Tee, Matthew Lee
- Year
- 2015
- Citations
- 8
- Access
- Open access
Abstract
Multi-robot foraging has been widely studied in the literature, and the general assumption is that the robots are simple, i.e., with limited processing and carrying capacity. We previously studied continuous foraging with slightly more capable robots, and in this article, we are interested in using similar robots for item delivery. Interestingly, item delivery and foraging are two sides of the same coin: foraging an item from a location is similar to satisfying a demand. We formally define the multi-robot item delivery problem and show that the continuous foraging problem is a special case of it. We contribute distributed multi-robot algorithms that solve the item delivery and foraging problems and describe how our shared world model is synchronized across the multi-robot team. We performed extensive experiments on simulated robots using a Java simulator, and we present our results to demonstrate that we outperform benchmark algorithms from multi-robot foraging.
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