Title: Reconfigurable Manipulator Simulation for Robotics and Multimodal Machine Learning Application: Aaria,
Abstract: This paper represents a systematic way for generation of Aaria, a simulated
model for serial manipulators for the purpose of kinematic or dynamic analysis
with a vast variety of structures based on Simulink SimMechanics. The proposed
model can receive configuration parameters, for instance in accordance with
modified Denavit-Hartenberg convention, or trajectories for its base or joints
for structures with 1 to 6 degrees of freedom (DOF). The manipulator is
equipped with artificial joint sensors as well as simulated Inertial
Measurement Units (IMUs) on each link. The simulation output can be positions,
velocities, torques, in the joint space or IMU outputs; angular velocity,
linear acceleration, tool coordinates with respect to the inertial frame. This
simulation model is a source of a dataset for virtual multimodal sensory data
for automation of robot modeling and control designed for machine learning and
deep learning approaches based on big data.