Model and Control of R-Soft Inverted Pendulum

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) actuated only by a revolute joint at the base...

A Provably Stable Iterative Learning Controller for Continuum Soft Robots

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 prominent feedforward control action to...

Planning Natural Locomotion for Articulated Soft Quadrupeds

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 planning method that aims to unify traditional...

Understanding Human Manipulation with the Environment: A Novel Taxonomy for Video Labelling

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 identifying them in video streams. In this...

PI^σ - PI^σ Continuous Iterative Learning Control for Nonlinear Systems with Arbitrary Relative Degree

Online-Offline Iterative Learning Control provides an effective and robust solution to learn precise trajectory tracking when dealing with repetitive tasks. Yet, these algorithms were developed under the assumption that the relative degree between input and output is one. This prevents applications in many practically meaningful situations - e.g...

Iterative learning control as a framework for human-inspired control with bio-mimetic actuators

The synergy between musculoskeletal and central nervous systems empowers humans to achieve a high level of motor performance, which is still unmatched in bio-inspired robotic systems. Literature already presents a wide range of robots that mimic the human body. However, under a control point of view, substantial advancements are still needed...

Exciting Nonlinear Modes of Conservative Mechanical Systems by Operating a Master Variable Decoupling

Eigenmanifolds extend eigenspaces to nonlinear mechanical systems with possibly non-Euclidean metrics. Recent work has shown that simple controllers can excite hyper-efficient oscillations by simultaneously stabilizing an Eigenmanifold and regulate the total energy. Yet, existing techniques require imposing assumptions on the system dynamics...

Using Nonlinear Normal Modes for Execution of Efficient Cyclic Motions in Articulated Soft Robots

Thanks to their body elasticity, articulated soft robots promise to produce effective and robust oscillations with low energy consumption. This in turn is an important feature which can be exploited in the execution of many tasks, as for example locomotion. Yet, an established theory and general techniques allowing to excite and sustain these...

Modeling Human Motor Skills to Enhance Robots’ Physical Interaction

The need for users’ safety and technology acceptability 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 and interactions. In this manuscript, we present a...

Editorial: Soft Robotic Modeling and Control: Bringing Together Articulated Soft Robots and Soft-Bodied Robots

Control Architecture for Human-Like Motion With Applications to Articulated Soft Robots

Human beings can achieve a high level of motor performance that is still unmatched in robotic systems. These capabilities can be ascribed to two main enabling factors: (i) the physical proprieties of human musculoskeletal system, and (ii) the effectiveness of the control operated by the central nervous system. Regarding point (i), the...