Papers
12
Total Citations
187
H-Index
8
About
Vaibhav Srivastava’s research lies at the intersection of human supervisory control, multi-robot systems, and soft robotics, with a focus on designing intelligent autonomous agents that can collaborate effectively with human operators. His major contributions include developing optimization frameworks for adaptive attention allocation in human-robot teams—determining where and how an operator should focus their attention—and pioneering trust-aware assistance-seeking policies that help robots maintain human trust while autonomously deciding when to request help. His work on multi-armed bandits for surveillance in abruptly changing environments has advanced path planning under uncertainty, while his recent efforts in soft robotics have produced novel designs for planar soft robots and data-enabled predictive control, as well as simultaneous shape reconstruction and force estimation using distributed sensors. With over 180 citations across his most-cited works, Srivastava’s impact is evident in both theoretical foundations and practical applications. Notably, his 2015 article on human supervisory control of robotic teams has garnered 63 citations, serving as a key reference for integrating cognitive modeling with engineering design. His ongoing work on trust dynamics and secondary task engagement continues to shape the future of human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1
- 2Surveillance in an abruptly changing world via multiarmed bandits36 citations · 2014
- 3Adaptive attention allocation in human-robot systems21 citations · 2012
- 4
- 5Efficient Path Planning of Soft Robotic Arms in the Presence of Obstacles11 citations · 2021
- 6
- 7On Trust-aware Assistance-seeking in Human-Supervised Autonomy9 citations · 2023
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- 10