Marco Andreetto
Papers
11
Total Citations
131
H-Index
7
About
Marco Andreetto is a leading researcher in assistive robotics, specializing in the development of safe, low-cost navigation systems for robotic walking assistants designed to support older adults. His core contributions lie in path following and obstacle avoidance, where he has pioneered innovative control strategies that prioritize user safety and autonomy. Andreetto’s major work includes the creation of “passive” guidance mechanisms that simulate natural, human-like behavior by using electromechanical brakes and authority-sharing between the robot and the user, ensuring the walker never overpowers the individual. His most cited paper (30 citations) introduces a socially-aware reactive obstacle avoidance strategy that combines potential field methods with limit cycles to navigate dynamic, crowded environments. Across his top-cited works, which collectively have garnered over 130 citations, he has advanced low-cost actuation and haptic feedback systems, such as combining bang-bang braking with vibrotactile cues for intuitive guidance. Notably, his research on harnessing steering singularities and constrained Kalman filters for minidrone flight demonstrates a versatile engineering approach. Andreetto’s work is distinguished by its practical focus on real-world deployment, making robotic walkers both affordable and reliable for enhancing senior mobility.
Research Focus
Key Achievements
Top Papers
- 1Socially-Aware Reactive Obstacle Avoidance Strategy Based on Limit Cycle30 citations · 2020
- 2Simulating Passivity for Robotic Walkers via Authority-Sharing18 citations · 2018
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- 5Passive robotic walker path following with bang-bang hybrid control paradigm14 citations · 2016
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- 8Constrained Kalman Filter for Adaptive Prediction in Minidrone Flight7 citations · 2019
- 9
- 10Path following for robotic rollators via simulated passivity5 citations · 2017