Research

The major topics of research interest of the MIR Lab include (but not limited to):

Autonomous Vehicle

We specifically focus on driving control based on behavior cloning using deep learning techniques.

Cost Effective Research Platform for Autonomous Vehicle Applications

This platform is a small but scalable research platform for autonomous vehicle applications. The whole framework is designed based on the ROS (Robot Operating System).

Simulation of Self-Driving Car on TORCS

We collected a human driver’s behavior in a racing car simulator. The driver’s view image data with steering angles and throttle values were collected for approximately four hours. Then we trained a Convolutional Neural Network model and had it to drive a racing car. Here is a fully autonomous test drive. Source code can be found at https://github.com/jrkwon/mir_torcs.

We used the same CNN model on a different track to show the flexibility of this approach. The followings show as successful driving on a different track from one where the model was trained.

ROS Gazebo and Rviz with Chevy Bolt

Drive by Wire Testing

Transforming a Model Car to a Self-Driving Car

Intelligent Mobile Robotics and Applications:

Architectures, localization, mapping, exploration, navigation
Multi-robot systems, coordination, coverage control, task allocation
Applications: domestic service applications, commercial, health-care

Wireless sensor networks and applications:

Architectures, sensor localizations, communication topologies, coverage
Mobile sensor networks, coverage control, workload distribution
Energy harvesting strategies
Applications: security & surveillance, environmental monitoring, personal health monitoring