Kernel for Modular Robot Applications: Automatic Modeling Techniques

A modular robotic system consists of standardized joint and link units that can be assembled into various kinematic configurations for different types of tasks. For the control and simulation of such a system, manual derivation of the kinematic and dynamic models, as well as the error model for kinematic calibration, require tremendous effort, because the models constantly change as the robot geometry is altered after module reconfiguration. This paper presents a framework to facilitate the model-generation procedure for the control and simulation of the modular robot system. A graph technique, termed kinematic graphs and realized through assembly incidence matrices (AIM), is introduced to represent the module-assembly sequence and robot geometry. The kinematics and dynamics are formulated based on a local representation of the theory of Lie groups and Lie algebras. The automatic model-generation procedure starts with a given assembly graph of the modular robot. Kinematic, dynamic, and error models of the robot are then established, based on the local representations and iterative graph-traversing algorithms. This approach can be applied to a modular robot with both serial and branch-type geometries, and arbitrary degrees of freedom. Furthermore, the AIM of the robot naturally leads to solving the task-oriented optimal configuration problem in modular robots. There is no need to maintain a huge library of robot models, and the footprint of the overall software system can be reduced.

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