V. Zanotto
Papers
19
Total Citations
1,357
H-Index
11
About
V. Zanotto is a robotics researcher whose work has made significant contributions to two interconnected fields: robot trajectory planning and medical robotics. He is perhaps best known for his pioneering work in smooth and optimal trajectory planning for industrial robot manipulators, developing algorithms that elegantly balance execution speed with motion quality by minimizing jerk — the rate of change of acceleration — a critical factor in reducing mechanical wear and improving precision. His 2006 paper introducing a new method for smooth trajectory planning has accumulated over 430 citations, while his subsequent time-jerk optimization technique from 2007 has garnered more than 320, reflecting the lasting influence of these foundational contributions. Zanotto further strengthened the field through rigorous experimental validation studies, demonstrating real-world applicability of his theoretical methods on industrial robots. Beyond trajectory planning, he has explored model predictive control for flexible-link mechanisms and ventured into medical robotics, contributing to haptic telerobotic systems for minimally invasive neurosurgery and dexterity-optimized surgical robot design. With a cumulative citation count exceeding 1,300, Zanotto's body of work remains an important reference for researchers and engineers advancing intelligent, precise, and efficient robotic systems.
Research Focus
Key Achievements
Top Papers
- 1A new method for smooth trajectory planning of robot manipulators431 citations · 2006
- 2A technique for time-jerk optimal planning of robot trajectories320 citations · 2007
- 3Optimal trajectory planning for industrial robots201 citations · 2009
- 4
- 5
- 6Model Predictive Control of a Flexible Links Mechanism64 citations · 2009
- 7
- 8A telerobotic haptic system for minimally invasive stereotactic neurosurgery27 citations · 2005
- 9
- 10Toward an optimal performance index for neurosurgical robot's design11 citations · 2009