Evolutionary Design and Assembly Planning for Stochastic Modular Robots

  • Michael T. Tolley
  • Jonathan D. Hiller
  • Hod Lipson
Part of the Studies in Computational Intelligence book series (SCI, volume 341)


A persistent challenge in evolutionary robotics is the transfer of evolved morphologies from simulation to reality, especially when these morphologies comprise complex geometry with embedded active elements. In this chapter we describe an approach that automatically evolves target structures based on functional requirements and plans the error-free assembly of these structures from a large number of active components. Evolution is conducted by minimizing the strain energy in a structure due to prescribed loading conditions. Thereafter, assembly is planned by sampling the space of all possible paths to the target structure and following those that leave the most options open. Each sample begins with the final completed structure and removes one accessible component at a time until the existing substructure is recovered. Thus, at least one path to a complete target structure is guaranteed at every stage of assembly. Automating the entire process represents a step towards an interactive evolutionary design and fabrication paradigm, similar to that seen in nature.


Assembly Time Target Structure Assembly Algorithm Evolutionary Design Assembly Planning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Michael T. Tolley
    • 1
  • Jonathan D. Hiller
    • 1
  • Hod Lipson
    • 1
  1. 1.Cornell UniversityIthacaUSA

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