14 accepted papers
Modular continuum soft arms represent an emerging class of robotic systems characterized by flexible, highly deformable structures. Designing shape controllers for these arms poses significant challenges due to their modeling complexity and hyper-redundant nature. Our goal is to develop a scalable c…
Soft robot perception integrates information from distributed, multi-modal sensors, broadening their application to active interaction. Our work introduces recurrent learning models for tactile-based object recognition, demonstrating comparable performance in virtual and real-world scenarios. The wo…
Modular continuum soft arms represent an emerging class of robotic systems characterized by flexible, highly deformable structures. Designing shape controllers for these arms poses significant challenges due to their modeling complexity and hyper-redundant nature. Our goal is to develop a scalable c
Soft robots are promising in biomedical applications thanks to their inherent structural compliance and distributed large deformations. However, integrating a sensory system that maintains the robot's dexterity while offering accurate state estimation remains an open challenge for their widespread a
Soft robot perception integrates information from distributed, multi-modal sensors, broadening their application to active interaction. Our work introduces recurrent learning models for tactile-based object recognition, demonstrating comparable performance in virtual and real-world scenarios. The wo
In this letter, we present SoftSling, a soft robot control strategy designed for accurately throwing objects following circular run-ups. SoftSling draws inspiration from ancient slingers, who rotated a sling loaded with a projectile at high speeds to fight and hunt, releasing the object by letting g
This paper proposes an adaptive method for robot-to-human handovers under different scenarios. The method combines Dynamic Movement Primitives (DMP) with Preference Learning (PL) to generate online trajectories that are reactive to human motion, modulating the speed of the robot. The PL allows for t
In this paper, we propose a novel dynamic gait controller for the repetitive behavior of soft robot manipulators performing routine tasks. Compliance with soft robots is advantageous when the robot interacts with living organisms and other fragile objects. However, predicting and controlling repetit…
The focus of the research community in the soft robotic field has been on developing innovative materials, but the design of control strategies applicable to these robotic platforms is still an open challenge. This is due to their highly nonlinear dynamics which is difficult to model and the degree
Learning-based modeling and control of soft robots is advantageous due to neural network’s ability to capture complex dynamical effects with low computational cost. Continual Learning techniques add further value to these methods by allowing networks to learn from continuously available data without
Humanoid robots are often supposed to operate in non-deterministic human environments, and as a consequence, the robust and gentle rejection of the external perturbations is extremely crucial. In this scenario, stable and accurate behavior is mostly solved through adaptive control mechanisms that le
The central concept of this letter is to develop an assistive manipulator that can automate the bathing task for elderly citizens. We propose to exploit principles of soft robotic technologies to design and control a compliant system to ensure safe human-robot interaction, a primary requirement for
Dynamic control of soft robotic manipulators is a challenging field still in its nascent stages. Modeling is still a major hurdle due to its high dimensional nonlinear dynamic properties. Even if accurate models of these high dimensional nonlinear systems are available, the computational burden of t
In this letter, a fundamental model for underwater legged locomotion, called U-SLIP, is presented and implemented on a robotic platform. Unlike traditional locomotion models, U-SLIP addresses specific hydrodynamic contributions, such as drag, buoyancy, and added mass. By taking as a reference the US