Soft robotic grippers are intrinsically delicate while grasping objects, and can rely on mechanical deformation to adapt to different shapes without explicit control. These characteristics are particularly appealing for agriculture, where items of produce from the same crop can vary significantly in shape and size, and delicate harvesting is among the first concerns for fruit quality. Various soft robotic grippers have been proposed for harvesting different produce types, however their employment in field testing has been extremely limited. In this paper we developed the first closed structure soft gripper for the harvest of blackberries. We adapted an existing gripper concept, initially testing it on a sensorised raspberry physical twin. Then, followed grower-guided protocols to pick blackberries in farm polytunnels, and to evaluate the shelf life in comparison with berries picked by professional human pickers. Our results with ten experimental varieties showed a picking success rate of 95.4% demonstrating the capability of a closed structure gripper to adapt mechanically to fruit-shape variability. Moreover, a shelf life assessment on seven measured traits reported greatly improved shelf life of between 30 and 150%, across all traits for gripper harvested blackberries. Our study demonstrates the potential of soft grippers for delicate fruit harvesting, and indicates how to increase the impact of robotics in agriculture.

Efficiently performing intervention tasks underwater is crucial in various commercial and scientific sectors; however, propeller-driven vehicles face limitations due to their floating nature. In Remotely Operated Vehicles (ROVs) operations, this can be compensated by the ability of the operator, but they come with high operational costs. Instead, Autonomous Underwater Vehicles (AUVs) have shown promise, but demonstrated intervention tasks are limited to controlled environments or docked. To address these limitations, we focused on the use of Underwater Legged Robots (ULRs), which offer greater stability and agile seabed mobility thanks to their legged propulsion system. This paper presents the field demonstration of teleoperated pick-and-place tasks using the ULR SILVER2 for which a novel stance control, Graphic User Interface (GUI), and tendon-driven gripper have been developed based on the lessons learned through several hours of field use. The methodology is validated through four field trials, including missions in both shallow water and open sea environments. The trials involve picking and placing various objects, such as plastic bottles, bags, and cans. The results demonstrate successful teleoperated object grasping and manipulation in real-world conditions, with collection times ranging from a few minutes to around ten minutes. Overall, this research contributes to advancing the capabilities of ULRs and lays the foundation for future underwater intervention missions in various scientific and industrial applications, aligning with the goals of the Decade of Ocean Science for Sustainable Development.

Prokaryotic flagellum is considered as the only known example of a biological “wheel,” a system capable of converting the action of rotatory actuator into a continuous propulsive force. For this reason, flagella are an interesting case study in soft robotics and they represent an appealing source of inspiration for the design of underwater robots. A great number of flagellum-inspired devices exists, but these are all characterized by a size ranging in the micrometer scale and mostly realized with rigid materials. Here, we present the design and development of a novel generation of macroscale underwater propellers that draw their inspiration from flagellated organisms. Through a simple rotatory actuation and exploiting the capability of the soft material to store energy when interacting with the surrounding fluid, the propellers attain different helical shapes that generate a propulsive thrust. A theoretical model is presented, accurately describing and predicting the kinematic and the propulsive capabilities of the proposed solution. Different experimental trials are presented to validate the accuracy of the model and to investigate the performance of the proposed design. Finally, an underwater robot prototype propelled by four flagellar modules is presented.

Drawing inspiration from the locomotion modalities of animals, legged robots demonstrated the potential to traverse irregular and unstructured environments. Successful approaches exploited single-leg templates, like the spring-loaded inverted pendulum (SLIP), as a reference for the control of multilegged machines. Nevertheless, the anchoring between the low-order model and the actual multilegged structure is still an open challenge. This article proposes a novel strategy to derive actuation inputs for a multilegged robot by expressing the control requirements in terms of jump height and forward speed (derived from the limit cycle). We found that these requirements could be associated with a specific maximum force, successively split on an arbitrary number of legs and their relative actuation sets. The proposed approach has been validated in multibody simulation and real-world experiments by employing the underwater hexapod robot SILVER2. Results show that locomotion performances of the low-order model are reflected by the simulated and actual robot, showing that the articulated-USLIP (a-USLIP) model can faithfully explain the multilegged behavior under the imposed control inputs once hydrodynamic parameters have been tuned. More importantly, the proposed controller can be translated to the terrestrial case with minimal modifications and extended with additional layers to obtain more complex behaviors.

Recently, a new category of bio-inspired legged robots moving directly on the seabed have been proposed to complement the abilities of traditional underwater vehicles and to enhance manipulation and sampling tasks. So far, only tele-operated use of underwater legged robots has been reported and in this paper we attempt to fill such gap by presenting the first step towards autonomous area inspection. First, we present a 3 dimensional single-legged model for underwater hopping locomotion and derive a path following control strategy. Later, we adapt such control strategy to an underwater hexapod robot SILVER2 on the robotic simulator Webots. Finally, we simulate a full autonomous mission consisting in the inspection of an area over a pre-defined path, target recognition, transition to a safer gait and target approach. Our results show the feasibility of the approach and encourage the implementation of the presented control strategy on the robot SILVER2.

Flagellated micro-organism are regarded as excellent swimmers within their size scales. This, along with the simplicity of their actuation and the richness of their dynamics makes them a valuable source of inspiration to design continuum, self-propelled underwater robots. Here we introduce a soft, flagellum-inspired system which exploits the compliance of its own body to passively attain a range of geometrical configurations from the interaction with the surrounding fluid. The spontaneous formation of stable helical waves along the length of the flagellum is responsible for the generation of positive net thrust. We investigate the relationship between actuation frequency and material elasticity in determining the steady-state configuration of the system and its thrust output. This is ultimately used to perform a parameter identification procedure of an elastodynamic model aimed at investigating the scaling laws in the propulsion of flagellated robots.

Recent developments in robotics demonstrated that bioinspiration and embodiement are powerful tools to achieve robust behavior in presence of little control. In this context morphological design is usually performed by humans, following a set of heuristic principles: in general this can be limiting, both from an engineering and an artificial life perspectives. In this work we thus suggest a different approach, leveraging evolutionary techniques. The case study is the one of improving the locomotion capabilities of an existing bioinspired robot. First, we explore the behavior space of the robot to discover a number of qualitatively different morphology-enabled behaviors, from whose analysis design indications are gained. The suitability of novelty search -- a recent open-ended evolutionary algorithm -- for this intended purpose is demonstrated. Second, we show how it is possible to condense such behaviors into a reconfigurable robot capable of online morphological adaptation (morphosis, morphing). Examples of successful morphing are demonstrated, in which changing just one morphological parameter entails a dramatic change in the behavior: this is promising for a future robot design. The approach here adopted represents a novel computed-aided, bioinspired, design paradigm, merging human and artificial creativity. This may result in interesting implications also for artificial life, having the potential to contribute in exploring underwater locomotion "as-it-could-be".

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.

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.

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.