Shiva Sander-Tavallaey
Papers
6
Total Citations
184
H-Index
5
About
Shiva Sander-Tavallaey is a leading researcher in robotics and industrial automation, whose work bridges the gap between fundamental physics and practical machine intelligence. Her primary research areas encompass friction modeling, system diagnostics, and autonomous decision-making for industrial manipulators. Sander-Tavallaey’s most influential contribution is her extended friction model for robot joints, which captures complex load and temperature effects at the nanoscale—a paper that has earned 74 citations and remains a cornerstone for precision robotics. She has also pioneered data-driven approaches for monitoring repetitive processes, with her 2014 work on gearbox diagnostics (41 citations) and her 2012 method for wear monitoring in robot joints (24 citations) enabling predictive maintenance in manufacturing. Her earlier identification of flexibility parameters in 6-axis manipulators (33 citations) provided critical insights for modeling robot dynamics, while her SVD-based optimization method for drive trains (9 citations) advanced design efficiency. Most recently, Sander-Tavallaey has explored behavior trees for autonomous systems, demonstrating their modular advantages over finite state machines in a 2024 case study on underground explosive charging. Her work is essential reading for engineers seeking to enhance robot reliability, performance, and autonomy.
Research Focus
Key Achievements
Top Papers
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- 5Cycle-Based Robot Drive Train Optimization Utilizing SVD Analysis9 citations · 2007
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