A self-guided approach for navigation in a minimalistic foraging robotic swarm

Journal article (2023)

Authors

S.J.L. Adams Team Luca Laurenti - Mechanical, Maritime and Materials Engineering
D. Jarne Ornia Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering
M. Mazo Team Manuel Mazo Jr - Mechanical, Maritime and Materials Engineering
Research Group
Team Luca Laurenti (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2023 S.J.L. Adams, D. Jarne Ornia, M. Mazo
DOI: https://doi.org/10.1007/s10514-023-10102-y
More Info
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Published Date

2023

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Luca Laurenti

Abstract

We present a biologically inspired design for swarm foraging based on ant’s pheromone deployment, where the swarm is assumed to have very restricted capabilities. The robots do not require global or relative position measurements and the swarm is fully decentralized and needs no infrastructure in place. Additionally, the system only requires one-hop communication over the robot network, we do not make any assumptions about the connectivity of the communication graph and the transmission of information and computation is scalable versus the number of agents. This is done by letting the agents in the swarm act as foragers or as guiding agents (beacons). We present experimental results computed for a swarm of Elisa-3 robots on a simulator, and show how the swarm self-organizes to solve a foraging problem over an unknown environment, converging to trajectories around the shortest path, and test the approach on a real swarm of Elisa-3 robots. At last, we discuss the limitations of such a system and propose how the foraging efficiency can be increased.