Marcello Calisti

An octopus-bioinspired solution to movement and manipulation for soft robots

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.

Dynamic Model of a Multibending Soft Robot Arm Driven by Cables

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.

Bioinspired locomotion and grasping in water: the soft eight-arm OCTOPUS robot

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.

Design and development of a soft robot with crawling and grasping capabilities

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.

Neural Network and Jacobian Method for Solving the Inverse Statics of a Cable-Driven Soft Arm With Nonconstant Curvature

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.

Study and fabrication of bioinspired Octopus arm mockups tested on a multipurpose platform

This paper illustrates a robotic approach to the study of the Octopus vulgaris arm. On the base of the embodied intelligence theory, a study on the interaction among materials, mechanisms and actuation systems has been conducted. Starting from the observation of the performances of the octopus and drawing inspiration by its functional anatomy, several mock-ups, made by different materials and actuated by different cable arrangements have been tested. For this purpose a versatile platform has been designed and built, where the various solutions have been mounted and compared. The final aim of the work is to replicate the main complex movements of the octopus in a robotic platform. In particular the reaching movement, which best represents the stereotyped motion pattern of the octopus arm, has been reproduced.

A two dimensional inverse kinetics model of a cable driven manipulator inspired by the octopus arm

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.

Dynamics of underwater legged locomotion: modeling and experiments on an octopus-inspired robot

This paper studies underwater legged locomotion (ULL) by means of a robotic octopus-inspired prototype and its associated model. Two different types of propulsive actions are embedded into the robot model: reaction forces due to leg contact with the ground and hydrodynamic forces such as the drag arising from the sculling motion of the legs. Dynamic parameters of the model are estimated by means of evolutionary techniques and subsequently the model is exploited to highlight some distinctive features of ULL. Specifically, the separation between the center of buoyancy (CoB)/center of mass and density affect the stability and speed of the robot, whereas the sculling movements contribute to propelling the robot even when its legs are detached from the ground. The relevance of these effects is demonstrated through robotic experiments and model simulations; moreover, by slightly changing the position of the CoB in the presence of the same feed-forward activation, a number of different behaviors (i.e. forward and backward locomotion at different speeds) are achieved.

Octopus-inspired sensorimotor control of a multi-arm soft robot

Soft robots have significant advantages over traditional rigid robots because of their morphological flexibility. However, the use of conventional engineering approaches to control soft robots is difficult, especially to achieve autonomous behaviors. With its completely soft body, the octopus has a rich behavioral repertoire, so it is frequently used as a model in building and controlling soft robots. However, the sensorimotor control strategies in some interesting behaviors of the octopus, such as octopus crawling, remain largely unknown. In this study, we review related biological studies on octopus crawling behavior and propose its sensorimotor control strategy. The proposed strategy is implemented with an echo state network on an octopus-inspired, multi-arm crawling robot. We also demonstrate the control strategy in the robot for autonomous direction and speed control. Finally, the implications of this study are discussed.

Evolutionary discovery of self-stabilized dynamic gaits for a soft underwater legged robot

In recent years a number of robotic platforms have been developed, that are capable of robust locomotion in presence of a simple open loop control. Relying on the self-stabilizing properties of their mechanical structure, morphology assumes a crucial role in the design process, that is, however, usually guided by a set of heuristic principles falling under what is commonly known as embodied intelligence. Despite many impressive demonstrations, the result of such a methodology may be sub-optimal, given the dimension of the design space and the complex intertwining of involved dynamical effects. Encouraged by the growing consensus that embodied solutions can indeed be produced by bio-inspired computational techniques in a more automated manner, this work proposes a computer-aided methodology to explore in simulation the design space of an existing robot, by harnessing computational techniques inspired by natural evolution. Although many works exist on the application of evolutionary algorithms in robotics, few of them embrace this design perspective. The idea is to have an evolutionary process suggesting to the human designer a number of interesting robot configurations and embodied behaviors, from whose analysis design hints can be gained to improve the platform. The focus will be on enhancing the locomotion capabilities of a multi-legged, soft, underwater robot. We investigate for the first time the suitability of a recently introduced open-ended evolutionary algorithm (novelty search) for the intended study, and demonstrate its benefits in the comparison with a more conventional genetic algorithm. Results confirm that evolutionary algorithms are indeed capable of producing new, elaborate dynamic gaits, with evolved designs exhibiting several regularities. Possible future directions are also pointed out, in which the passive exploitation of robots morphological features could bring additional advantages in achieving diverse, robust behaviors.