Papers
19
Total Citations
263
H-Index
8
About
Chayan Sarkar is a robotics and AI researcher whose work spans multi-robot systems, human-robot interaction, and embodied intelligence. He has made significant contributions to the challenge of coordinating robot teams in industrial environments, most notably through scalable and energy-efficient task allocation algorithms — his 2018 paper on scalable multi-robot task allocation has garnered 58 citations, while a 2022 consensus-based approach follows closely with 49. His practical impact extends to Industry 4.0 applications, including Jampacker, an acclaimed robotic bin packing system (31 citations) that demonstrates his ability to bridge algorithmic innovation with real-world deployment. Sarkar has also carved a distinctive niche in natural language understanding for robots, developing systems that resolve ambiguity in human instructions — an often-overlooked yet critical challenge for coworker robots. His DoRO framework (19 citations) and related dialogue-based disambiguation work reflect a commitment to making robots genuinely usable by non-expert humans. Beyond explicit interaction, he has explored implicit human-robot communication, including fatigue detection and social group perception. Collectively, his research portfolio of over 220 citations positions him as a versatile contributor bridging intelligent coordination, perception, and human-centered robotics.
Research Focus
Key Achievements
Top Papers
- 1A Scalable Multi-Robot Task Allocation Algorithm58 citations · 2018
- 2Consensus-based fast and energy-efficient multi-robot task allocation49 citations · 2022
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- 4DoRO: Disambiguation of Referred Object for Embodied Agents19 citations · 2022
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- 6Enabling Human-Like Task Identification From Natural Conversation15 citations · 2019
- 7Your instruction may be crisp, but not clear to me!10 citations · 2019
- 8DeFatigue: Online Non-Intrusive Fatigue Detection by a Robot Co-Worker9 citations · 2018
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