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.

This paper reports on the development of a new kind of unmanned underwater vehicle which draws inspiration from cephalopods both in terms of morphology and swimming routine. The robot developed here is the first in its kind, being a soft aquatic robot which travels in water by pulsed-jet propulsion. The general design principles of this innovative kind of underwater robot are illustrated and a first prototype is built and tested. The experiments demonstrate an inverse correlation between the frequency of pulsation and the speed of the robot. A mathematical model which associates the kinematics of the pulsating routine to the dynamics of the swimming is devised and compared with the experiments in order to better investigate the interplay of the various design parameters.

This paper describes the design and development of a robot with six soft limbs, with the dual capability of pushing-based locomotion and grasping by wrapping around objects. Specifically, a central platform lodges six silicone limbs, radially distributed, with cables embedded. A new mechanism-specific gait, invariant regarding the number of limbs, has been implemented. Functionally, some limbs provide stability while others push and pull the robot to locomote in the desired direction. Once the robot is close to a target, one limb is elected to wrap around the object and, thanks to the particular limb structure and the soft material, a friction-based grasping is achieved. The robot is inspired by the octopus and implements the key principles of locomotion in this animal, without coping the full body structure. For this reason it works in water, but it is not restricted to this environment. The experiments show the effectiveness of the original solution in locomotion and grasping.

Control of soft robots remains nowadays a big challenge, as it does in the larger category of continuum robots. In this paper a direct and inverse kinetics models are described for a non-constant curvature structure. A major effort has been put recently in modelling and controlling constant curvature structures, such as cylindrical shaped manipulators. Manipulators with non-constant curvature, on the other hand, have been treated with a piecewise constant curvature approximation. In this work a non-constant curvature manipulator with a conical shape is built, taking inspiration from the anatomy of the octopus arm. The choice of a conical shape manipulator made of soft material is justified by its enhanced capability in grasping objects of different sizes. A different approach from the piecewise constant curvature approximation is employed for direct and inverse kinematics model. A continuum geometrically exact approach for direct kinetics model and a Jacobian method for inverse case are proposed. They are validated experimentally with a prototype soft robot arm moving in water. Results show a desired tip position in the task-space can be achieved automatically with a satisfactory degree of accuracy.