Evolutionary Design and Assembly Planning for Stochastic Modular Robots

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.

[1]  Hod Lipson,et al.  Stochastic self-reconfigurable cellular robotics , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[2]  Hod Lipson,et al.  Three Dimensional Stochastic Reconfiguration of Modular Robots , 2005, Robotics: Science and Systems.

[3]  Hod Lipson,et al.  Freeform fabrication and characterization of Zn‐air batteries , 2008 .

[4]  H. Kim Rapid prototyping of micropower sources by laser direct-write , 2004 .

[5]  W. McCarthy Programmable matter , 2000, Nature.

[6]  Irah H. Donner Intellectual Property Protection for Multimedia Applications, Part 2: Putting the Pieces Together , 1995, Computer.

[7]  Jordan B. Pollack,et al.  Automatic design and manufacture of robotic lifeforms , 2000, Nature.

[8]  Hod Lipson,et al.  Multi material topological optimization of structures and mechanisms , 2009, GECCO.

[9]  Wolfram Burgard,et al.  Robotics: Science and Systems XV , 2010 .

[10]  Gregory S. Chirikjian,et al.  Modular Self-Reconfigurable Robot Systems [Grand Challenges of Robotics] , 2007, IEEE Robotics & Automation Magazine.

[11]  Hod Lipson,et al.  Freeform fabrication of ionomeric polymer‐metal composite actuators , 2006, Rapid Prototyping Journal.

[12]  Gregory S. Hornby,et al.  Functional Scalability through Generative Representations: The Evolution of Table Designs , 2004 .

[13]  Hod Lipson,et al.  Experiment Design for Stochastic Three-Dimensional Reconfiguration of Modular Robots , 2007 .

[14]  Iuliu Vasilescu,et al.  Miche: Modular Shape Formation by Self-Disassembly , 2008, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[15]  Gregory S. Chirikjian,et al.  Modular Self-Reconfigurable Robot Systems , 2007 .

[16]  D. Gillespie Exact Stochastic Simulation of Coupled Chemical Reactions , 1977 .

[17]  Michael A. Gibson,et al.  Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels , 2000 .

[18]  Hod Lipson,et al.  Dynamically programmable fluidic assembly , 2008 .

[19]  Jonas Neubert,et al.  Stochastic Modular Robotic Systems: A Study of Fluidic Assembly Strategies , 2010, IEEE Transactions on Robotics.