Shinerbots: A robotic swarm navigation platform inspired by the golden shiner fish

This thesis describes a swarm robots navigation algorithm inspired by the golden shiner fish. The goal of this algorithm is to have the swarm of robots navigate to their destination with minimal requirements on each robot. There is little sensing complexity required. Each robot only needs to sense information at its current location without the need to understand the whole environment. In addition, it only needs to sense its neighbors in a limited radius. Furthermore, each robot requires minimal computation as it operates on basic rules on what it senses, instead of performing localization and path planning like traditional robotics. The algorithm proposed in this thesis is based on simple rules such as modulating speed according to the environment, as well as staying close to neighboring robots. Simulation results show that the swarm of robots converge to the desired region with this algorithm. A swarm robotic platform was designed and built to experiment with this algorithm. It is named Shinerbots due to the inspiration taken from the golden shiners. Each robot is 40.6 mm in diameter, actuated by vibration, senses ambient light using a photo diode, and senses neighbors using infrared. Scalable ways of charging and control of the swarm are achieved by a charging plate, as well as relayed system messages. A total of 85 robots were built. Experiments on the swarm behavior were conducted on a 4 ft by 4 ft platform, using an overhead digital projector to create the light environment that the Shinerbots are supposed to navigate in. The Shinerbots were able to swarm to a target region with minimal sensing and control.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2018

Author dc:creator

• Luo, Enyu

Contributors dc:contributor

• Gao, Grace Xingxin

• Swarm robotics
• Navigation

Statement dc:rights

• Copyright 2017 Enyu Luo

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/99256

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/99256