Embodiment design of soft continuum robots

This article presents the results of a multidisciplinary project where mechatronic engineers worked alongside biologists to develop a soft robotic arm that captures key features of octopus anatomy and neurophysiology. The concept of embodiment (the dynamic coupling between sensory-motor control, anatomy, materials and environment that allows for the animal to achieve adaptive behaviours) is used as a starting point for the design process but tempered by current engineering technologies and approaches. In this article, the embodied design requirements are first discussed from a robotic viewpoint by taking into account real-life engineering limitations; then, the motor control schemes inspired by octopus nervous system are investigated. Finally, the mechanical and control design of a prototype is presented that appropriately blends bio-inspiration and engineering limitations. Simulated and experimental results show that the developed continuum robotic arm is able to reproduce octopus-like motions for bending, reaching and grasping

Software Abstractions for Simulation and Control of a Continuum Robot

Nordmann A, Rolf M, Wrede S. Software Abstractions for Simulation and Control of a Continuum Robot. In: SIMPAR2012 - SIMULATION, MODELING, and PROGRAMMING for AUTONOMOUS ROBOTS. 2012

Controlling a CyberOctopus Soft Arm with Muscle-like Actuation

This paper presents an application of the energy shaping methodology to control a flexible, elastic Cosserat rod model of a single octopus arm. The novel contributions of this work are two-fold: (i) a control-oriented modeling of the anatomically realistic internal muscular architecture of an octopus arm; and (ii) the integration of these muscle models into the energy shaping control methodology. The control-oriented modeling takes inspiration in equal parts from theories of nonlinear elasticity and energy shaping control. By introducing a stored energy function for muscles, the difficulties associated with explicitly solving the matching conditions of the energy shaping methodology are avoided. The overall control design problem is posed as a bilevel optimization problem. Its solution is obtained through iterative algorithms. The methodology is numerically implemented and demonstrated in a full-scale dynamic simulation environment Elastica. Two bio-inspired numerical experiments involving the control of octopus arms are reported

Lessons for Robotics From the Control Architecture of the Octopus

Biological and artificial agents are faced with many of the same computational and mechanical problems, thus strategies evolved in the biological realm can serve as inspiration for robotic development. The octopus in particular represents an attractive model for biologically-inspired robotic design, as has been recognized for the emerging field of soft robotics. Conventional global planning-based approaches to controlling the large number of degrees of freedom in an octopus arm would be computationally intractable. Instead, the octopus appears to exploit a distributed control architecture that enables effective and computationally efficient arm control. Here we will describe the neuroanatomical organization of the octopus peripheral nervous system and discuss how this distributed neural network is specialized for effectively mediating decisions made by the central brain and the continuous actuation of limbs possessing an extremely large number of degrees of freedom. We propose top-down and bottom-up control strategies that we hypothesize the octopus employs in the control of its soft body. We suggest that these strategies can serve as useful elements in the design and development of soft-bodied robotics

Neural Control and Biomechanics of the Octopus Arm Muscular Hydrostat

openOctopus vulgaris is a cephalopod mollusk with outstanding motor capabilities, built upon the action of eight soft and exceptionally flexible appendages. In the absence of any rigid skeletal-like support, the octopus arm works as a “muscular hydrostat” and movement is generated from the antagonistic action of two main muscle groups (longitudinal, L, and transverse, T, muscles) under an isovolumetric constrain. This peculiar anatomical organization evolved along with novel morphological arrangements, biomechanical properties, and motor control strategies aimed at reducing the computational burden of controlling unconstrained appendages endowed with virtually infinite degrees of freedom of motion. Hence, the octopus offers the unique opportunity to study a motor system, different from those of skeletal animals, and capable of controlling complex and precise motor tasks of eight arms with theoretically infinite degrees of freedom. Here, we investigated the octopus arm motor system employing a bottom-up approach. We began by identifying the motor neuron population and characterizing their organization in the arm nervous system. We next performed an extensive biomechanical characterization of the arm muscles focusing on the morphofunctional properties that are likely to facilitate the dynamic deformations occurring during arm movement. We show that motor neurons cluster in specific regions of the arm ganglia following a topographical organization. In addition, T muscles exhibit biomechanical properties resembling those of vertebrate slow muscles whereas L muscles are closer to those of vertebrate fast muscles. This difference is enhanced by the hydrostatic pressure inherently present in the arm, which causes the two muscles to operate under different conditions. Interestingly, these features underlie the different use of arm muscles during specific tasks Thus, the octopus evolved several arm-embedded adaptations to reduce the motor control complexity and increase the energetic efficiency of arm motion. This study find relevance also in the blooming field of soft-robotics. Indeed, an increasing number of researchers are currently aiming to design and construct bio-inspired soft-robotic manipulators, more flexible and versatile than their “hard” counterparts and more suited to perform gentle tasks and to interact with biological tissues. In this context, the octopus emerged as a pivotal source of inspiration for motor control principles underlying motion in soft-bodied limbs.openXXXIV CICLO - NEUROSCIENZE - Neuroscienze e neurotecnologieDI CLEMENTE, Alessi

Design of flexible actuators using electro-active polymers and CPG-based control strategies

Biomimetic design based on inspiration from nature for solutions for engineering problems has been practiced throughout human history. Invertebrate animals without a skeletal struc-ture have exible, robust and agile movements. For example, the octopus arm which is able to grip objects by exerting large forces, moves with a wide range of velocities, and manip-ulates delicate objects, without any rigid skeletal elements. Two key applications of such biomimetic systems are compliant and lightweight robotic arms for tightly constrained spaces and energy-e cient muscle actuators for biomimetic locomotion. Inspired by octopus arm, in this thesis we investiagte di erent design concepts and require-ments for using dielectric electroactive polymers (EAP) for designing of exible actuators and manipulators. A model-guided approach to design a bio-inspired exible actuator mod-ule is presented analyzed. Further, mathematical modelling for Central Pattern Generators (CPGs) is presented. The condition for phase synchronization of coupled single chain oscil-lators is derived and various techniques for pattern generation using oscillator network are studied. Finally, octopus based control using Central Pattern Generators (CPGs) is brie y discussed

Soft-Material Robotics

There has been a boost of research activities in robotics using soft materials in the past ten years. It is expected that the use and control of soft materials can help realize robotic systems that are safer, cheaper, and more adaptable than the level that the conventional rigid-material robots can achieve. Contrary to a number of existing review and position papers on soft-material robotics, which mostly present case studies and/or discuss trends and challenges, the review focuses on the fundamentals of the research field. First, it gives a definition of softmaterial robotics and introduces its history, which dates back to the late 1970s. Second, it provides characterization of soft-materials, actuators and sensing elements. Third, it presents two general approaches to mathematical modelling of kinematics of soft-material robots; that is, piecewise constant curvature approximation and variable curvature approach, as well as their related statics and dynamics. Fourth, it summarizes control methods that have been used for soft-material robots and other continuum robots in both model-based fashion and model-free fashion. Lastly, applications or potential usage of soft-material robots are described related to wearable robots, medical robots, grasping and manipulation

The Current State of Cephalopod Science and Perspectives on the Most Critical Challenges Ahead From Three Early-Career Researchers

International audienceHere, three researchers who have recently embarked on careers in cephalopod biology discuss the current state of the field and offer their hopes for the future. Seven major topics are explored genetics, aquaculture, climate change, welfare, behavior, cognition, and neurobiology. Recent developments in each of these fields are reviewed and the potential of emerging technologies to address specific gaps in knowledge about cephalopods are discussed. Throughout, the authors highlight specific challenges that merit particular focus in the near-term. This review and prospectus is also intended to suggest some concrete near-term goals to cephalopod researchers and inspire those working outside the field to consider the revelatory potential of these remarkable creatures

Spatio-Temporal Optimization for Control of Infinite Dimensional Systems in Robotics, Fluid Mechanics, and Quantum Mechanics

The majority of systems in nature have a spatio-temporal dependence and can be described by Partial Differential Equations (PDEs). They are ubiquitous in science and engineering, and are of rising interest among the control, robotics, and machine learning communities. Related methods usually treat these infinite dimensional problems in finite dimensions with reduced order models. This leads to committing to specific approximation schemes and the subsequent control laws cannot generalize outside of the approximation schemes. Additionally, related work does not consider spatio-temporal descriptions of noise that realistically represent the stochastic nature of physical systems. This thesis develops a variety of approaches for control optimization and co-design optimization for PDE and stochastic PDE (SPDE) systems from a unified perspective that can be applied to macroscopic systems in robotics and fluid dynamics, as well as microscopic systems in quantum mechanics. These approaches are each developed completely in the infinite dimensional Hilbert spaces where the systems are mathematically described, enabling the frameworks to be agnostic to the discretization scheme used to implement them. The first three developed approaches are applied in simulation to classical systems in fluid dynamics such as the Heat and Burgers equation. The fourth approach is developed for second-order SPDEs that arise in robotic systems, and is applied in simulation to systems in soft-robotics such as the Euler-Bernoulli equation and a biological model of a soft-robotic limb. Finally, several approaches are developed in the context of quantum feedback control of open quantum systems with non-demolition measurement, and one such approach is applied in simulation to perform explicit feedback control of the two qubit open quantum system.Ph.D

Health, Agency, and the Evolution of Consciousness

This goal of this thesis in the philosophy of nature is to move us closer towards a true biological science of consciousness in which the evolutionary origin, function, and phylogenetic diversity of consciousness are moved from the field's periphery of investigations to its very centre. Rather than applying theories of consciousness built top-down on the human case to other animals, I argue that we require an evolutionary bottom-up approach that begins with the very origins of subjective experience in order to make sense of the place of mind in nature. To achieve this goal, I introduce and defend the pathological complexity thesis as both a framework for the scientific investigation of consciousness and as a life-mind continuity thesis about the origins and function of consciousness