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Autonomous Robots

, Volume 42, Issue 7, pp 1337–1354 | Cite as

Accomplishing high-level tasks with modular robots

  • Gangyuan Jing
  • Tarik Tosun
  • Mark Yim
  • Hadas Kress-Gazit
Article
Part of the following topical collections:
  1. Special Issue on Robotics: Science and Systems 2016

Abstract

The advantage of modular self-reconfigurable robot systems is their flexibility, but this advantage can only be realized if appropriate configurations (shapes) and behaviors (controlling programs) can be selected for a given task. In this paper, we present an integrated system for addressing high-level tasks with modular robots, and demonstrate that it is capable of accomplishing challenging, multi-part tasks in hardware experiments. The system consists of four tightly integrated components: (1) a high-level mission planner, (2) a large design library spanning a wide set of functionality, (3) a design and simulation tool for populating the library with new configurations and behaviors, and (4) modular robot hardware. This paper builds on earlier work by Jing et al. (in: Robotics: science and systems, 2016), extending the original system to include environmentally adaptive parametric behaviors, which integrate motion planners and feedback controllers with the system.

Keywords

Modular robots Formal methods Controller synthesis Reactive mission planning 

Notes

Acknowledgements

This work was funded by NSF Grant Nos. CNS-1329620 and CNS-1329692.

Supplementary material

Supplementary material 1 (mp4 47803 KB)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Cornell UniversityIthacaUSA
  2. 2.University of PennsylvaniaPhiladelphiaUSA

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