  This paper illustrates the MIR (Mobile Intelligent Robotics) Vehicle: a
feasible option of transforming an electric ride-on-car into a modular Graphics
Processing Unit (GPU) powered autonomous platform equipped with the capability
that supports test and deployment of various intelligent autonomous vehicles
algorithms. To use a platform for research, two components must be provided:
perception and control. The sensors such as incremental encoders, an Inertial
Measurement Unit (IMU), a camera, and a LIght Detection And Ranging (LIDAR)
must be able to be installed on the platform to add the capability of
environmental perception. A microcontroller-powered control box is designed to
properly respond to the environmental changes by regulating drive and steering
motors. This drive-by-wire capability is controlled by a GPU powered laptop
computer where high-level perception algorithms are processed and complex
actions are generated by various methods including behavior cloning using deep
neural networks. The main goal of this paper is to provide an adequate and
comprehensive approach for fabricating a cost-effective platform that would
contribute to the research quality from the wider community. The proposed
platform is to use a modular and hierarchical software architecture where the
lower and simpler motor controls are taken care of by microcontroller programs,
and the higher and complex algorithms are processed by a GPU powered laptop
computer. The platform uses the Robot Operating System (ROS) as middleware to
maintain the modularity of the perceptions and decision-making modules. It is
expected that the level three and above autonomous vehicle systems and Advanced
Driver Assistance Systems (ADAS) can be tested on and deployed to the platform
with a decent real-time system behavior due to the capabilities and
affordability of the proposed platform.
