Welcome to Autonomous Systems and Control Laboratory!
Our laboratory is with the Robotics and Mechatronics Engineering Department, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Korea.
Our interdisciplinary research focuses on sensing, perception, decision and control algorithms using artificial intelligent (Al) for the applications ranging from autonomous driving and flying robotic systems.
If you are a perspective student, please click HOW HOW TO APPLY first.
Updated Date : November 26, 2024
Recent Researches
Lane Segmentation Data Augmentation for Heavy Rain Sensor Blockage using Realistically Translated Raindrop Images and CARLA Simulator
BEV Image-based Lane Tracking Control System for Autonomous Lane
Repainting Robot
Improving Lane Detection Performance with Rain Style Diversification Module for Image Synthesis Enhancement using Feature-Level Style Distribution on Adverse Weather Conditions
Investigating the Impact of Adverse Weather Conditions on Object Detection Performance and Time to Collision for Self-Driving Cars
LuminanceGAN: Controlling the Brightness of Generated Image
for Data Augmentation in Various Night Conditions
Deep Reinforcement Learning (DRL) based autonomous mobile robot (AMR) on static & dynamic environments
Deep Learning based object for self-driving car in abnormal weather conditions
Horizontal Attention Based Generation Module For Unsupervised Domain Adaptive Stereo Matching
Advancements in Amphibious Reconnaissance Robots with Screw
Wheel Propulsion
Investigating the Impact on Darkness Environment with Rain and Snow Weather Conditions on Object Detection Performance and Time to Collision for Self-Driving Cars
Integrated path tracking with DYC and MPC using LSTM based tire force estimator for four-wheel independent
steering and driving vehicle
LSTM based MPC tracking control for self-driving car w/ four-wheel independent steering (4WIS) system for different friction roads (black-ice)
Deep Learning based lane detection for self-driving car in abnormal weather conditions
Dynamic Hybrid Path Planning using Grey Wolf Optimizer with Artificial Potential field for Autonomous UAVs
Deep Learning based object for self-driving car in abnormal weather conditions