Papers
11
Total Citations
91
H-Index
4
About
Upma Jain is a robotics researcher whose work centers on multi-robot systems, odor source localization, and autonomous exploration in unknown environments. Her most significant contributions lie in developing nature-inspired algorithms for odor source localization, where she has pioneered hybrid approaches combining Particle Swarm Optimization (PSO) with Grey Wolf Optimizer and Gravitational Search Algorithm. Her 2019 paper on multiple odor source localization using diverse-PSO has garnered 23 citations, while her 2018 work on concatenating PSO and Grey Wolf Optimizer has received 19 citations. Jain has also made notable advances in multi-robot area exploration, introducing a circle partitioning method for workload sharing that has been cited 16 times. Her comprehensive survey of frontier-based exploration methods (14 citations) has become a valuable resource for researchers in the field. More recently, she has expanded into three-dimensional navigation systems for multiple UAVs and underwater image enhancement using hybrid deep learning models. Her work consistently demonstrates a talent for fusing multiple optimization algorithms to solve complex robotic navigation challenges, making her a respected voice in swarm robotics and autonomous exploration.
Research Focus
Key Achievements
Top Papers
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- 3Multi Robot Area Exploration Using Circle Partitioning Method16 citations · 2012
- 4Comparative study of frontier based exploration methods14 citations · 2017
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- 7Advancing Underwater Image Enhancement Using Hybrid Deep Learning Models3 citations · 2025
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