44 accepted papers
Soft robots,compared to rigid robots,possess inherent advantages,including higher degrees of freedom, compliance,and enhanced safety,which have contributed to their increasing application across various fields. Among these benefits, adaptability is particularly noteworthy. In this paper, adaptabilit…
Robots operating alongside people, particularly in sensitive scenarios such as aiding the elderly with daily tasks or collaborating with workers in manufacturing, must guarantee safety and cultivate user trust. Continuum soft manipulators promise safety through material compliance, but as designs ev…
Model-based manipulation of deformable objects has traditionally dealt with objects while neglecting their dynamics, thus mostly focusing on very lightweight objects at steady state. At the same time, soft robotic research has made considerable strides toward general modeling and control, despite so…
Learning from demonstration is a promising way to teach robots new skills. However, a central challenge in executing acquired skills is the ability to recognize faults and prevent failures. This is essential since the demonstrations usually cover only a limited number of mostly successful cases. Dur…
Industrial robotics demands significant energy to operate, making energy-reduction methodologies increasingly important. Strategies for planning minimum-energy trajectories typically involve solving nonlinear optimal control problems (OCPs), which rarely cope with real-time requirements. In this pap…
Diffusion policies have recently emerged as a powerful framework for robotic manipulation. However, like other behavior cloning methods, they remain vulnerable to distributional shift, often requiring human-in-the-loop interventions to correct failures during deployment. These interactions naturally…
Asglobal demand for fruits and vegetables continues to rise, the agricultural industry faces significant challenges in securing adequate labor. Robotic harvesting devices offer a promising solution to address this issue. Harvesting delicate fruits, such as blackberries, presents unique open challeng
Robots operating alongside people, particularly in sensitive scenarios such as aiding the elderly with daily tasks or collaborating with workers in manufacturing, must guarantee safety and cultivate user trust. Continuum soft manipulators promise safety through material compliance, but as designs ev
Achieving controlled jumping behaviour for a quadruped robot is a challenging task, especially when introducing passive compliance in mechanical design. This study addresses this challenge via imitation-based deep reinforcement learning with a progressive training process. To start, we learn the jum
Soft continuum manipulators are celebrated for their versatility and physical robustness to external forces and perturbations. However, this feature comes at a cost. The many degrees of freedom and compliance pose challenges for accurate pose reconstruction, both in terms of distributed sensing and…
Even though a variety of methods have been proposed in the literature, efficient and effective latent-space control (i.e., control in a learned low-dimensional space) of physical systems remains an open challenge. We argue that a promising avenue is to leverage powerful and well-understood closed-fo…
A central challenge in Learning from Demonstration is to generate representations that are adaptable and can generalize to unseen situations. This work proposes to learn such a representation without using task-specific heuristics within the context of multi-reference frame skill learning by superim…
Soft robots enable safe and robust operations in unstructured environments. However, the nonlinearities of their continuum structure complicate the accomplishment of classic robotic tasks, such as pick and place. In this work, we propose the R-Soft Inverted Pendulum, a Soft Inverted Pendulum (SIP) a
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. While these systems have been prevalent in the literature, there is an increasing trend toward designing soft-rigid hy…
We introduce the Random Oscillators Network (RON), a physically-inspired recurrent model derived from a network of heterogeneous oscillators. Unlike traditional recurrent neural networks, RON keeps the connections between oscillators untrained by leveraging on smart random initialisations, leading t…
Quadrupeds deployed in real-world scenarios need to be robust to unmodelled dynamic effects. In this work, we aim to increase the robustness of quadrupedal periodic forward jumping (i.e., pronking) by unifying cutting-edge model-based trajectory optimization and iterative learning control. Using a r
The control possibilities for soft robots have long been hindered by the need for reliable methods to estimate their configuration. Inertial measurement units (IMUs) can solve this challenge, but they are affected by well-known drift issues. This letter proposes a method to eliminate this limitation
Controlled execution of dynamic motions in quadrupedal robots, especially those with articulated soft bodies, presents a unique set of challenges that traditional methods struggle to address efficiently. In this study, we tackle these issues by relying on a simple yet effective two-stage learning fr…
Fully exploiting soft robots' capabilities requires devising strategies that can accurately control their movements with the limited amount of control sources available. This task is challenging for reasons including the hard-to-model dynamics, the system's underactuation, and the need of using a pr
Animals rely on the elasticity of their tendons and muscles to execute robust and efficient locomotion patterns for a vast and continuous range of velocities. Replicating such capabilities in artificial systems is a long-lasting challenge in robotics. By taking advantage of a pitch dynamics decoupli
Performing precise, repetitive motions is essential in many robotic and automation systems. Iterative learning control (ILC) allows determining the necessary control command by using a very rough system model to speed up the process. Functional iterative learning control is a novel technique that pr…
Soft robots are intrinsically underactuated mechanical systems that operate under uncertainties and disturbances. In these conditions, this letter proposes two versions of PID-like control laws with a saturated integral action for the particularly challenging shape regulation task. The closed-loop s
The control possibilities for soft robots have long been hindered by the lack of accurate yet computationally treatable dynamic models of soft structures. Polynomial curvature models propose a solution to this quest for continuum slender structures. Nevertheless, the results produced with this class
Adding elastic elements to the mechanical structure should enable robots to perform efficient oscillatory tasks. Still, even characterizing natural oscillations in nonlinear systems is a challenge in itself, which nonlinear modal theory promises to solve. Therein eigenmanifolds generalize eigenspace
The intrinsically underactuated and nonlinear nature of continuum soft robots makes the derivation of provably stable feedback control laws a challenging task. Most of the works so far circumvented the issue either by looking at coarse fully-actuated approximations of the dynamics or by imposing qua
Embedding elastic elements into legged robots through mechanical design enables highly efficient oscillating patterns that resemble natural gaits. However, current trajectory planning techniques miss the opportunity of taking advantage of these natural motions. This work proposes a locomotion planni…
Eigenmanifolds are two-dimensional submanifolds of the state space, which generalize linear eigenspaces to nonlinear mechanical systems. Initializing a robot on an Eigenmanifold (or driving it there by control) yields hyper-efficient and regular oscillatory behaviors, called modal oscillations. This
Introducing elasticity in the mechanical design can endow robots with the ability of performing efficient and effective periodic motions. Yet, devising controllers that can take advantage of such elasticity is still an open challenge. This letter tackles an instance of this general problem, by propo
Robotic legs often lag behind the performance of their biological counterparts. The inherent passive dynamics of natural legs largely influences the locomotion and can be abstracted through the spring-loaded inverted pendulum (SLIP) model. This model is often approximated in physical robotic legs us…
In recent years, the spread of data-driven approaches for robotic grasp synthesis has come with the increasing need for reliable datasets, which can be built e.g. through video labelling. To this goal, it is important to define suitable rules to characterize the main human grasp types, for easily id
The need for users' safety and technology accept-ability has incredibly increased with the deployment of co-bots physically interacting with humans in industrial settings, and for people assistance. A well-studied approach to meet these requirements is to ensure human-like robot motions. Classic sol…
The complex nature of soft robot dynamics calls for the development of models specifically tailored on the control application. In this letter, we take a first step in this direction by proposing a dynamic model for slender soft robots, taking into account the fully infinite-dimensional dynamical st
Unlike traditional robots, soft robots can intrinsically interact with their environment in a continuous, robust, and safe manner. These abilities - and the new opportunities they open - motivate the development of algorithms that provide reliable information on the nature of environmental interacti
Creating soft robots with sophisticated, autonomous capabilities requires these systems to possess reliable, on-line proprioception of 3D configuration through integrated soft sensors. We present a framework for predicting a soft robot's 3D configuration via deep learning using feedback from a soft,
The large majority of legged robots currently employ ball-feet or flat-feet. More recently soft feet have been introduced, to improve walking performance on uneven grounds. Nevertheless, their novel adaptability requires sensor systems beyond traditional Force/Torque sensors to estimate the distribu
Piecewise constant curvature models have proven to be an useful tool for describing kinematics and dynamics of soft robots. However, in their three dimensional formulation they suffer from many issues limiting their range of applicability - as discontinuities and singularities - mainly concerning th
This letter proposes a framework which is able to generate a sequence of three-dimensional human dance poses for a given music. The proposed framework consists of three components: a music feature encoder, a pose generator, and a music genre classifier. We focus on integrating these components for g
The development of effective reduced order models for soft robots is paving the way toward the development of a new generation of model based techniques, which leverage classic rigid robot control. However, several soft robot features differentiate the soft-bodied case from the rigid-bodied one. Fir…
Since the spread of robotic systems embedding in their mechanics purposefully designed elastic elements, the interest in characterizing and exploiting non-linear oscillatory behaviors has progressively grown. However, few works so far looked at the problem from the point of view of modal analysis. T…
Recently, the development of soft robots is imposing a change of prospective in several aspects of design and control, moving the robotic field closer to the natural world. Soft robots, like many animals, are often built of continuously deformable elements, and are consequently characterized by a hi
Soft hands are robotic systems that embed compliant elements in their mechanical design. This enables an effective adaptation with the items and the environment, and ultimately, an increase in their grasping performance. These hands come with clear advantages in terms of ease-to-use and robustness i
An effective robotic wrist represents a key enabling element in robotic manipulation, especially in prosthetics. In this paper, we propose an under-actuated wrist system, which is also adaptable and allows to implement different under-actuation schemes. Our approach leverages upon the idea of soft s…
Sensing contact forces can be a key enabler for higher order dexterous manipulation in robotic hands. To sense the full range of contact pressure distribution would provide the best solution, but it is in practice unfeasible when considering very deformable and adaptable hands. This paper proposes a…
State of the art of hand prosthetics is divided between simple and reliable gripper-like systems and sophisticate hi-tech poly-articular hands which tend to be complex both in their design and for the patient to operate. In this paper, we introduce the idea of decoding different movement intentions