386 citations · 465 across the 21 of their papers we have counts for
23 papers
Manipulation with Stability Guarantees: Linear Deformable Objects with Non-negligible Physical Response Grasped at Multiple Location
Daniel Feliu-Talegon, Cosimo Della Santina
Most research on the manipulation of deformable objects focuses on lightweight systems with negligible mechanical response, effectively restricting attention to quasi-static regime…
Learning to infer and manipulate through distributed whole-arm interaction in a soft robot
Chuhan Zhang, Ebrahim Shahabi, Kseniia Khomenko +2
In animals such as elephants and octopuses, acquiring non-visual information about an object and physically engaging with it are inseparable processes mediated by rich, large-area…
Set-Supervised Diffusion Policy: Learning Action-Chunking Diffusion through Corrections
Zhaoting Li, Gang Chen, Javier Alonso-Mora +2
Diffusion policies have recently emerged as a powerful framework for robotic manipulation. However, like other behavior cloning methods, they remain vulnerable to distributional sh…
Soft Swing-up: Benchmarking Model-Based Optimal Control for Rigid-Soft Underactuated Systems
Daniele Caradonna, Nikhil Nair, Anup Teejo Mathew +5
Continuum soft robots are inherently underactuated and subject to intrinsic input constraints, making dynamic control particularly challenging, especially in hybrid rigid-soft robo…
Symmetric Lyapunov Subcenter Manifolds for Periodic Regulation of Mechanical Systems
Yannik P. Wotte, Arne Sachtler, Alin Albu-Schäffer +2
Multi-body mechanical systems have rich internal dynamics, whose solutions can be exploited as energy-efficient control targets. Yet, solutions non-trivially depend on system param…
Exponentially Stable Projector-based Control of Lagrangian Systems with Gaussian Processes
Giulio Evangelisti, Cosimo Della Santina, Sandra Hirche
Designing accurate yet robust tracking controllers with tight performance guarantees for Lagrangian systems is challenging due to nonlinear modeling uncertainties and conservative…
Swing-Up of a Weakly Actuated Double Pendulum via Nonlinear Normal Modes
Arne Sachtler, Davide Calzolari, Maximilian Raff +5
We identify the nonlinear normal modes spawning from the stable equilibrium of a double pendulum under gravity, and we establish their connection to homoclinic orbits through the u…
Generalizable Motion Policies through Keypoint Parameterization and Transportation Maps
Giovanni Franzese, Ravi Prakash, Cosimo Della Santina +1
Learning from Interactive Demonstrations has revolutionized the way non-expert humans teach robots. It is enough to kinesthetically move the robot around to teach pick-and-place, d…
Berry Twist: a Twisting-Tube Soft Robotic Gripper for Blackberry Harvesting
Johannes F. Elfferich, Ebrahim Shahabi, Cosimo Della Santina +1
As global demand for fruits and vegetables continues to rise, the agricultural industry faces challenges in securing adequate labor. Robotic harvesting devices offer a promising so…
Controlling Deformable Objects with Non-negligible Dynamics: a Shape-Regulation Approach to End-Point Positioning
Sebastien Tiburzio, Tomás Coleman, Daniel Feliu-Talegon +1
Model-based manipulation of deformable objects has traditionally dealt with objects while neglecting their dynamics, thus mostly focusing on very lightweight objects at steady stat…
Model Predictive Wave Disturbance Rejection for Underwater Soft Robotic Manipulators
Kyle L. Walker, Cosimo Della Santina, Francesco Giorgio-Serchi
Inspired by the octopus and other animals living in water, soft robots should naturally lend themselves to underwater operations, as supported by encouraging validations in deep wa…
Curriculum-Based Reinforcement Learning for Quadrupedal Jumping: A Reference-free Design
Vassil Atanassov, Jiatao Ding, Jens Kober +2
Deep reinforcement learning (DRL) has emerged as a promising solution to mastering explosive and versatile quadrupedal jumping skills. However, current DRL-based frameworks usually…
Analytical Model and Experimental Testing of the SoftFoot: an Adaptive Robot Foot for Walking over Obstacles and Irregular Terrains
Cristina Piazza, Cosimo Della Santina, Giorgio Grioli +2
Robot feet are crucial for maintaining dynamic stability and propelling the body during walking, especially on uneven terrains. Traditionally, robot feet were mostly designed as fl…
Neural Autoencoder-Based Structure-Preserving Model Order Reduction and Control Design for High-Dimensional Physical Systems
Marco Lepri, Davide Bacciu, Cosimo Della Santina
This work concerns control-oriented and structure-preserving learning of low-dimensional approximations of high-dimensional physical systems, with a focus on mechanical systems. We…
NiSNN-A: Non-iterative Spiking Neural Networks with Attention with Application to Motor Imagery EEG Classification
Chuhan Zhang, Wei Pan, Cosimo Della Santina
Motor imagery, an important category in electroencephalogram (EEG) research, often intersects with scenarios demanding low energy consumption, such as portable medical devices and…
Modeling and Control of Intrinsically Elasticity Coupled Soft-Rigid Robots
Zach J. Patterson, Cosimo Della Santina, Daniela Rus
While much work has been done recently in the realm of model-based control of soft robots and soft-rigid hybrids, most works examine robots that have an inherently serial structure…
Physics-informed Neural Networks to Model and Control Robots: a Theoretical and Experimental Investigation
Jingyue Liu, Pablo Borja, Cosimo Della Santina
This work concerns the application of physics-informed neural networks to the modeling and control of complex robotic systems. Achieving this goal required extending Physics Inform…
Can Large Language Models design a Robot?
Francesco Stella, Cosimo Della Santina, Josie Hughes
Large Language Models can lead researchers in the design of robots.
Model Based Control of Soft Robots: A Survey of the State of the Art and Open Challenges
Cosimo Della Santina, Christian Duriez, Daniela Rus
Continuum soft robots are mechanical systems entirely made of continuously deformable elements. This design solution aims to bring robots closer to invertebrate animals and soft ap…
Estimating the State of Epidemics Spreading with Graph Neural Networks
Abhishek Tomy, Matteo Razzanelli, Francesco Di Lauro +2
When an epidemic spreads into a population, it is often unpractical or impossible to have a continuous monitoring of all subjects involved. As an alternative, algorithmic solutions…
Covid-19 and Flattening the Curve: a Feedback Control Perspective
Francesco Di Lauro, István Z. Kiss, Daniela Rus +1
Many of the control policies that were put into place during the Covid-19 pandemic had a common goal: to flatten the curve of the number of infected people so that its peak remains…
Using Nonlinear Normal Modes for Execution of Efficient Cyclic Motions in Articulated Soft Robots
Cosimo Della Santina, Dominic Lakatos, Antonio Bicchi +1
Inspired by the vertebrate branch of the animal kingdom, articulated soft robots are robotic systems embedding elastic elements into a classic rigid (skeleton-like) structure. Leve…
Cerebellar-Inspired Learning Rule for Gain Adaptation of Feedback Controllers
Ivan Herreros, Xerxes D. Arsiwalla, Cosimo Della Santina +3
How does our nervous system successfully acquire feedback control strategies in spite of a wide spectrum of response dynamics from different musculo-skeletal systems? The cerebellu…