Gabriele Valentini,1,2
Anthony Antoun,2
Marco Trabattoni,2
Bernát Wiandt,2
Yasumasa Tamura,3
Etienne Hacquard,4
Vito Trianni,5
Marco Dorigo2 (2017)
1Beyond Center, School of Earth and Space Exploration, Arizona State University, Tempe, Arizona, USA
2IRIDIA, Université Libre de Bruxelles, Brussels, Belgium
3Department of Networked Systems and Services, Budapest University of Technology and Economics, Budapest, Hungary
4School of Computing, Tokyo Institute of Technology, Tokyo, Japan
5IRT Jules Verne, Nantes, France
6ISTC, Consiglio Nazionale Delle Ricerche, Rome, Italy
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Table of Contents |
We present the Kilogrid, an open-source virtualization environment and data logging manager for the Kilobot robot, Kilobot for short. The Kilogrid has been designed to extend the sensory-motor abilities of the Kilobot, to simplify the task of collecting data during experiments, and to provide researchers with a tool to fine-control the experimental setup and its parameters. Based on the design of the Kilobot and compatible with existing hardware, the Kilogrid is a modular system composed of a grid of computing nodes, or modules, that provides a bidirectional communication channel between the Kilobots and a remote workstation. In this paper, we describe the hardware and software architecture of the Kilogrid system as well as its functioning to accompany its release as a new open-hardware tool for the swarm robotics community. We demonstrate the capabilities of the Kilogrid using a 200-module Kilogrid, swarms of up to 100 Kilobots, and four different case studies: exploration and obstacle avoidance, site selection based on multiple gradients, plant watering, and pheromone-based foraging. Through this set of case studies, we show how the Kilogrid allows the experimenter to virtualize sensors and actuators not available to the Kilobot and to automatize the collection of data essential for the analysis of the experiments.
The following videos are high definition versions of two experimental runs from the obstacle avoidance case study. In the video on the left, Kilobots perform obstacle avoidance in an environment with only the arena walls as obstacles. In the video on the right, in addition to the arena walls two circular objects are placed in the middle of the arena.
Videos: Arena borders and two obstacles |
The following videos is a high definition version of an experimental run from the site selection case study.
The following videos are high definition versions of two experimental runs from the plant watering case study. In the video on the left, Kilobots perform plant watering with an evaportation time of 60 seconds while in the video on the right the evaporation time is set to 120 seconds.
Videos: Evaporation time 60 seconds |
Videos: Evaporation time 120 seconds |
The following videos is a high definition version of an experimental run from the pheromone-based foraging case study.