Papers
11
Total Citations
276
H-Index
8
About
Inmo Jang is a leading researcher in multirobot systems, specializing in cooperative control, task allocation, and human-swarm interaction. His most impactful work, "A Decentralized Cluster Formation Containment Framework for Multirobot Systems" (2021, 153 citations), addresses the challenge of coordinating robot teams for complex missions, offering a flexible and reconfigurable solution. Jang has also pioneered intuitive teleoperation techniques, such as bare-hand control of robotic manipulators via virtual reality and Leap Motion (2019, 32 citations), and advanced distributed neural network training for robotic manipulation using consensus algorithms (2022, 21 citations). His research extends to heterogeneous aerial swarms, where he developed integrated decision-making frameworks for cooperative tasks with minimum requirements (2018, 15 citations), and hedonic coalition formation for multi-robot task allocation (2021, 12 citations). Jang’s innovative "Omnipotent Virtual Giant" framework (2021, 9 citations) enables remote human-swarm interaction, likening operators to super-powered beings in virtual reality. With over 260 citations across his top works, Jang’s contributions are shaping the future of autonomous robotics, from industrial automation to search-and-rescue operations.
Research Focus
Key Achievements
Top Papers
- 1A Decentralized Cluster Formation Containment Framework for Multirobot Systems153 citations · 2021
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- 5Distributed Hedonic Coalition Formation for Multi-Robot Task Allocation12 citations · 2021
- 6Virtual Kinesthetic Teaching for Bimanual Telemanipulation12 citations · 2021
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- 8Omnipotent Virtual Giant for Remote Human–Swarm Interaction9 citations · 2021
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