Egidio Falotico

TL;DR: This review article attempts to provide an insight into various controllers developed for continuum/soft robots as a guideline for future applications in the soft robotics field.

TL;DR: This paper presents a model-based policy learning algorithm for closed-loop predictive control of a soft robotic manipulator that can accommodate variable frequency control and unmodeled external loads.

TL;DR: This work presents the architecture of the first release of the Neurorobotics Platform, a new web-based environment offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in silico experimentation.

TL;DR: This paper provides a machine learning-based approach for the development of dynamic models for a soft robotic manipulator and a trajectory optimization method for predictive control of the manipulator in task space and indicates that such an approach is promising for developing fast and accurate dynamic model for soft robotic Manipulators while being applicable on a wide range of soft manipulators.

TL;DR: The central concept of this letter is to develop an assistive manipulator that can automate the bathing task for elderly citizens by exploiting principles of soft robotic technologies to design and control a compliant system to ensure safe human–robot interaction.