A Hardware and Software Testbed for Underactuated Self-Assembling Robots: Extended Abstract

Alexandra Nilles, Justin Wasserman, Austin Born, Chris Horn, John Born, Steven M. Lavalle

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present the implementation and characterization of an affordable testbed for underactuated multi-agent, self-assembling systems. There has been recent interest into the control of nano- A nd micro-scale active particle systems, but these systems are often difficult to manufacture and observe, hindering control research. Our testbed offers an accessible way to experiment with different design and control approaches. The testbed is composed of an off-the-shelf rolling weaselball toy and a 3D printed external hub that modifies the agent's dynamics. The software toolbox includes simulations and code for data extraction and analysis of the weaselballs. The advantage of our testbed for studying distributed robotic systems is that these robots can be made quickly and cheaply, are relatively small, and do not require complex or expensive environments. The software in our toolbox includes a high fidelity Gazebo simulation, and Python code for analyzing trajectories from both simulation and overhead video of the system. Using this toolbox, we present useful computed properties of the system with regards to object clustering.

Original languageEnglish (US)
Title of host publicationInternational Symposium on Multi-Robot and Multi-Agent Systems, MRS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7-9
Number of pages3
ISBN (Electronic)9781728128764
DOIs
StatePublished - Aug 2019
Event2nd International Symposium on Multi-Robot and Multi-Agent Systems, MRS 2019 - New Brunswick, United States
Duration: Aug 22 2019Aug 23 2019

Publication series

NameInternational Symposium on Multi-Robot and Multi-Agent Systems, MRS 2019

Conference

Conference2nd International Symposium on Multi-Robot and Multi-Agent Systems, MRS 2019
Country/TerritoryUnited States
CityNew Brunswick
Period8/22/198/23/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Optimization

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