Intelligent Robotic Autonomy and Perception (IRAP) Lab focuses on robotics problems in civil and environmental engineering applications. Targeting many hardly accessible or dangerous sites in the environment, we solves for robot autonomy dealing with perceptual sensor data. Main research interest and detailed robotics topics include perception based environment mapping, intelligent sensor fusion, decision making and control of the robotic agents, robotic operation and navigation in GPS-denied enthronements (e.g., underwater, indoor).

Research Interests

  • Intelligent perception and mapping
  • Autonomous robotic navigation
  • Decision making and multitasking in robotic navigation
  • Underwater imaging and navigation

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Three papers accepted for IROS 2018
Congratulations to Younggun Cho, Youngji Kim and Giseop Kim for their accepted papers at IROS 2018

Model based Visibility Enhancement paper is accepted for JFR

Multi-band Fusion for Single Image Dehazing Paper is accepted for RA-L
Multi-band Fusion Dehazing is available from early access

Younggun Cho and Jinyong Jeong and Ayoung Kim, Model Assisted Multi-band Fusion for Single Image Enhancement and Applications to Robot Vision. IEEE RA Letters, 2018.

Best Paper Award at ICRA LTAWS (Long-term autonomy) workshop
Congratulations to Giseop Kim for winning the best paper award at ICRA LTAWS 2018

One paper accepted for UR 2018
Congratulations to Jinyong Jeong for his accepted papers at UR 2018

Two Posters will be preseted at LTAWS (Long-term autonomy) workshop
Congratulations to Younggun Cho and Giseop Kim for their accepted posters at ICRA LTAWS 2018

URP (creative) has been awarded
Congratulations to Hyesu Jang for the award CEE homepage

Complex Urban LiDAR Data Set Released
We introduce our complex urban LiDAR dataset accepted for ICRA 2018.

Three papers accepted for ICRA 2018
Congratulations to Jinyong Jeong, Young-Sik Shin, and Joowan Kim for their accepted papers at ICRA 2018

[More to the history of our group...]

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Page last modified on August 31, 2018, at 06:23 PM