This research looks at the robotic shape formation problem, which is one of the fundamental problems in robotic swarm systems. Here, the task is to move a group of robots to form a user-specified shape. In this dissertation, the task of shape formation is divided to four problems: (i) using local information to estimate the swarm size; (ii) using arbitrary number of robots to display a user-specified shape; (iii) localizing a swarm of robots with peer-to-peer measurements; and (iv) assigning each robot a location in the shape and routing each robot to quickly reach its assigned goal location. Accordingly, four algorithms, each solves a problem above, are presented. The presented algorithms are validated using a custom physical 100-robot swarm, and a custom efficient swarm system simulator. The results from both the simulation and physical experiments show that: each presented algorithm is able to solve its corresponding problem efficiently and reliably. Furthermore, those four presented algorithms are brought together into a fully decentralized persistent shape formation algorithm. With the developed simulator and physical robotic swarm, it is further demonstrated that: this integrated algorithm allows the swarms with any size to persistently form arbitrary user-specified shapes, requiring only the use of local information.

Creator

• wang, hanlin

DOI

• https://doi.org/10.21985/n2-gd95-km80

Subject

• Robotics
• Computer engineering
• Computer science

Language

• en

Alternate Identifier

• http://dissertations.umi.com/northwestern:15732
• etdadmin_upload_844241

Keyword

• algorithms
• swarm systems
• scheduling and planning
• sensor networks
• distributed systems

Date created

• 2021-01-01

Resource type

• Dissertation

Rights statement

• In Copyright