Modular robots are composed of many elementary mechatronic modules that can be connected to form a robot body of various shapes. This feature allows such a robot to adapt for a given task and particular environment. A motion of the modular robot is based on control of individual angles between the modules, and the robot locomotion can be realized using Central Pattern Generators (CPG). A robot motion in the environment with obstacles can be achieved using several locomotion controllers that are switched by a strategy based on motion planning techniques. Preparation of CPG-based gaits leads to a high-dimensional optimization that requires to design proper cost functions. Existing approaches optimize the gaits separately according to human-designed cost functions. In this paper, we investigate how to automatically derive a set of gaits suitable for modular robots without specifying low-level details about the gaits. We propose to optimize multiple gaits simultaneously using a single cost function. This cost function is based on the ability of motion planning to solve the task using the gaits being optimized. The proposed system is verified on several modular robots with unusual shapes including robots with failed modules.


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    Title :

    Evolution of multiple gaits for modular robots


    Contributors:


    Publication date :

    2016-12-01


    Size :

    5987452 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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