The new and promising field of soft robotics has many open areas of research such as the development of an exhaustive theoretical and methodological approach to dynamic modeling. To help contribute to this area of research, this paper develops a dynamic model of a continuum soft robot arm driven by cables and based upon a rigorous geometrically exact approach. The model fully investigates both dynamic interaction with a dense medium and the coupled tendon condition. The model was experimentally validated with satisfactory results, using a soft robot arm working prototype inspired by the octopus arm and capable of multibending. Experimental validation was performed for the octopus most characteristic movements: bending, reaching, and fetching. The present model can be used in the design phase as a dynamic simulation platform and to design the control strategy of a continuum robot arm moving in a dense medium.

Soft robotics is a challenging and promising branch of robotics. It can drive significant improvements across various fields of traditional robotics, and contribute solutions to basic problems such as locomotion and manipulation in unstructured environments. A challenging task for soft robotics is to build and control soft robots able to exert effective forces. In recent years, biology has inspired several solutions to such complex problems. This study aims at investigating the smart solution that the Octopus vulgaris adopts to perform a crawling movement, with the same limbs used for grasping and manipulation. An ad hoc robot was designed and built taking as a reference a biological hypothesis on crawling. A silicone arm with cables embedded to replicate the functionality of the arm muscles of the octopus was built. This novel arm is capable of pushing-based locomotion and object grasping, mimicking the movements that octopuses adopt when crawling. The results support the biological observations and clearly show a suitable way to build a more complex soft robot that, with minimum control, can perform diverse tasks.

Soft robotics and its related technologies enable robot abilities in several robotics domains including, but not exclusively related to, manipulation, manufacturing, human–robot interaction and locomotion. Although field applications have emerged for soft manipulation and human–robot interaction, mobile soft robots appear to remain in the research stage, involving the somehow conflictual goals of having a deformable body and exerting forces on the environment to achieve locomotion. This paper aims to provide a reference guide for researchers approaching mobile soft robotics, to describe the underlying principles of soft robot locomotion with its pros and cons, and to envisage applications and further developments for mobile soft robotics.

The octopus is an interesting model for the development of soft robotics, due to its high deformability, dexterity and rich behavioural repertoire. To investigate the principles of octopus dexterity, we designed an eight-arm soft robot and evaluated its performance with focused experiments. The OCTOPUS robot presented here is a completely soft robot, which integrates eight arms extending in radial direction and a central body which contains the main processing units. The front arms are mainly used for elongation and grasping, while the others are mainly used for locomotion. The robotic octopus works in water and its buoyancy is close to neutral. The experimental results show that the octopus-inspired robot can walk in water using the same strategy as the animal model, with good performance over different surfaces, including walking through physical constraints. It can grasp objects of different sizes and shapes, thanks to its soft arm materials and conical shape.

The solution of the inverse kinematics problem of soft manipulators is essential to generate paths in the task space. The inverse kinematics problem of constant curvature or piecewise constant curvature manipulators has already been solved by using different methods, which include closed-form analytical approaches and iterative methods based on the Jacobian method. On the other hand, the inverse kinematics problem of nonconstant curvature manipulators remains unsolved. This study represents one of the first attempts in this direction. It presents both a model-based method and a supervised learning method to solve the inverse statics of nonconstant curvature soft manipulators. In particular, a Jacobian-based method and a feedforward neural network are chosen and tested experimentally. A comparative analysis has been conducted in terms of accuracy and computational time.

An underwater legged robot, inspired by benthic animals, opens new perspectives for seabed exploration.