Two foraging algorithms for robot swarms using only local communication
By Nicholas Hoff, Amelia Sagoff, Robert J. Wood, Radhika Nagpal. 2010
109 citations recorded by the source corpus.
Large collections of robots have the potential to perform tasks collectively using distributed control algorithms. These algorithms require communication between robots to allow the robots to coordinate their behavior and act as a collective. In this paper we describe two algorithms which allow coordination between robots, but do not require physical environment marks such as pheromones. Instead, these algorithms rely on simple, local, low bandwidth, direct communication between robots. We describe the algorithms and measure their performance in worlds with and without obstacles.
Subfields: Computer Networks and Communications, Genetics, Mechanical Engineering
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Gerhard Neumann
- Maximilian Hüttenrauch
- Adrian Šošić
- Michael Rubenstein
- Christian Ahler
- Radhika Nagpal
- Levent Bayindir
In Genetics
In Mechanical Engineering
- Gerhard Neumann
- Maximilian Hüttenrauch
- Adrian Šošić
- Michael Rubenstein
- Christian Ahler
- Radhika Nagpal
- Levent Bayindir
Citations in the corpus
- Guided Deep Reinforcement Learning for Swarm Systems (2017, background): “Further work can be found in [9], [4], [11].”
- Kilobot: A low cost scalable robot system for collective behaviors (2012, methodology): “For a more detailed explanation of this algorithm, please see [7].”
- Kilobot: A low cost robot with scalable operations designed for collective behaviors (2014, methodology): “In this demonstration, the foraging algorithm from [23] is implemented directly on a Kilobot collective.”
- A review of swarm robotics tasks (2016, background): “[73] included also communication between robots in their cost metric.”