Inmo Jang
Assistant Professor at Korea Aerospace University
About myself
Hi, I am Inmo Jang, an Assistant Professor at Korea Aerospace University. My research interests range over the areas of multi-robot/agent systems, decentralised autonomous decision-making, control and navigation for robots, human multi-robot interaction, and their real-world applications.
Prior to joining the university, I was a Principal Robotics Research Engineer and Head of EHS Automation Part at Samsung Electronics, where I worked with the mission of "Creating a Robot/AI System for inspecting semiconductor fabrication plants". Before that, I was a postdoctoral research associate in Robotics for Extreme Environment Group at the University of Manchester, where I was involved in RAIN(Robotics and AI in Nuclear) project, one of the four big robotics and AI projects funded by EPSRC. I was also a JAEA NEST Fellow (visiting researcher) at the University of Tokyo, Japan in 2020. Since 2015, I have worked towards decision making of multi-robot systems and finished PhD in Cranfield University, UK, under Prof Hyo-Sang Shin and Prof Antonios Tsourdos. In South Korea, I had worked at Korea Aerospace Industries, Ltd., and also worked at Korea Institute of Aviation Safety Technology in total 5+ years. Before that, I completed MSc/BSc in Mechanical and Aerospace Engineering in Seoul National University, S.Korea.
As I am very keen on collaborating on any kind research topics of multi-agent/robot systems, feel free to contact me. Also, check out my GitHub and YouTube channel where you can see glimpses of my ongoing work!
Education
PhD in Autonomous Intelligent Multi-Robot/Agent Systems (Centre for Autonomous and Cyber-physical Systems), Cranfield University, UK (Apr 2015 – Apr 2018)
MSc in Mechanical and Aerospace Engineering, Seoul National University, S. Korea (Mar 2008 – Feb 2010)
BSc in Mechanical and Aerospace Engineering, Seoul National University, S. Korea (Mar 2004 – Feb 2008)
Professional Experience
Assistant Professor, Korea Aerospace University, S.Korea (Mar 2024 – Now)
Robotics Applied Scientist/Engineer, Samsung Electronics, S Korea (Sep 2020 – Feb 2024)
Postdoctoral Research Associate, The University of Manchester, UK (Apr 2018 – Aug 2020)
JAEA Fellow (Visiting Researcher), The University of Tokyo, Japan (Jan 2020 – Feb 2020)
PhD Candidate Researcher, Cranfield University, UK (Apr 2015 – Apr 2018)
Aviation Safety Certification Specialist, Korea Institute of Aviation Safety Technology, S. Korea (Mar 2014 – Apr 2015)
Flight Dynamics Engineer, Korea Aerospace Industries Ltd, S. Korea (Jan 2010 – Mar 2014)
Research Assistant, Seoul National University, S. Korea (Jan 2008 – Dec 2009)
Research Interests
Multi-Agent(Robot) System, Autonomous Decision Making, and Human-Swarm Interaction
Robotics for Inspection and Maintenance
Services
Journal reviewer - IEEE T-RO / IEEE T-SMC / IEEE T-CNS / Swarm Intelligence / IEEE RAL / AIAA JAIS / AGNT / IMechE Part G / IJASS /
Conference reviewer - ICRA / IROS / SMC / SII / TAROS / UKACC / RED-UAS
Recent Updates
Begin a new chapter as an Assistant Professor at Korea Aerospace University since 2024
Participated as an industrial panelist for RSS 2023, Daegu
Really honoured to be involved as an industrial panellist for RSS (Robotics: Science and Systems) 2023, which is one of the top-tier conferences in robotics!
Delivered a talk as for Young Researcher Session for KRoC 2023, Pyeonchang
Conference papers accepted in 2022
Our paper "Change Detection in Unmanned Aerial Vehicle Images for Industrial Infrastructure Rooftop Monitoring" is accepted to UR 2022
Conference papers accepted in 2021
Our paper "Distributed Hedonic Coalition Formation for Multi-Robot Task Allocation" is accepted to IEEE CASE 2021
Our paper "Omnipotent Virtual Giant for Remote Human–Swarm Interaction" is accepted to IEEE ROMAN 2021
Our work about "cluster formation containment of a multi-robot system" published in T-RO
Our paper "Virtual Kinesthetic Teaching for Bimanual Telemanipulation" is accepted to IEEE/SICE SII 2021
Our work about "decision-making about EV Charging Station" published in T-ITS
This work shows that a decision-making framework for a multi-robot system can be utilised as a modelling tool for EV (Electric Vehicle) users' potential behaviours and can help to make a business strategy about the positioning of EV charging stations. Refer to 10.1109/TITS.2020.3038938
Dec 2020
Moved to Samsung, Back to S Korea
Joined as a Robotics Research Scientist/Engineer for Samsung!
Sep 2020
Secondment to Japan
Best Poster Award Finalist in TAROS 2019
"Intuitive Bare-Hand Teleoperation of a Robotic Manipulator using Virtual Reality and Leap Motion"
https://link.springer.com/chapter/10.1007/978-3-030-25332-5_25
July 2019
Science highlighted my work as Latest News!
Omnipotent Virtual Giant for Remote Human-Swarm Interaction
You can be supernatural in virtual reality! That allows you to efficiently supervise and control multiple robots at the same time. (https://arxiv.org/abs/1903.10064)
Highlighted by Science (doi:10.1126/science.aax5187)
Mar 2019
Bare-hand Teleoperation of a Robotic Manipulator
rainhub.org.uk/ai-assisted-teleoperation-of-dual-arms/
Jan 2019
Best Poster Award Finalist in TAROS 2019
Decentralised Decision-making of Self-interested Multiple Agents/Robots: A Game-theoretical Approach
Each figure shows how multiple robots (n_a = 320) can make decisions for task allocation (n_t = 5) in a decentralised manner in the proposed framework. Here, the circles and the squares indicate the positions of the robots and the tasks, respectively. The lines between the circles represent the communication networks of the robots. The colored robots are assigned to the same colored task; for example, yellow robots belong to the team for executing the yellow task. The size of a square indicates the reward of the corresponding task. The cost for a robot with regard to a task is considered as a function of the distance from the robot to the task.
I.Jang, H.Shin, and A.Tsourdos, “Anonymous Hedonic Game for Task Allocation in a Large-Scale Multiple Agent System”, IEEE Transactions on Robotics (T-RO), 34(6), pp 1534-1548, 2018. DOI: 10.1109/TRO.2018.2858292.
Scalable Coordination Method for Swarm Robots
More than thousands robots (theoretically infinite robots as well) can be coordinated in a closed-loop manner even only in use of local information-based feedback.
Multi-Robot Task Allocation and Path Planning
50 Robots address (1) task allocation (amongst 3 tasks) with consideration of task demands/distances/remaining work resources, (2) position allocation (i.e. where to work), and (3) path planning with collision avoidance.
Selected Publications
J Hu, P Bhowmick, I Jang, F Arvin, A Lanzon; “A Decentralized Cluster Formation Containment Framework for Multirobot Systems”, IEEE Transactions on Robotics (T-RO), 2021. DOI: 10.1109/TRO.2021.3071615
S. Bae, I.Jang, S Gros, B. Kulcsar, and J Hellgren; “A Game Approach for Charging Station Placement Based on User Preferences and Crowdedness”, IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2020. DOI: 10.1109/TITS.2020.3038938
I.Jang, H.Shin, A.Tsourdos, J.Jeong, S.Kim, and J.Suk; “An integrated decision-making framework of a heterogeneous aerial robotic swarm for cooperative tasks with minimum requirements”, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 233(6), pp 2101-2118, 2019. DOI: 10.1177/0954410018772622
I.Jang, H.Shin, and A.Tsourdos; “Anonymous Hedonic Game for Task Allocation in a Large-Scale Multiple Agent System”, IEEE Transactions on Robotics (T-RO), 34(6), pp 1534-1548, 2018. DOI: 10.1109/TRO.2018.2858292.
I.Jang, H.Shin, and A.Tsourdos; “Local Information-Based Control for Probabilistic Swarm Distribution Guidance”, Swarm Intelligence, 12(4), pp 327-359, 2018. DOI: 10.1007/s11721-018-0160-2.