Morphological Computation in Plant Seeds for a New Generation of Self-Burial and Flying Soft Robots

Plants have evolved different mechanisms to disperse from parent plants and improve germination to sustain their survival. The study of seed dispersal mechanisms, with the related structural and functional characteristics, is an active research topic for ecology, plant diversity, climate change, as well as for its relevance for material science and engineering. The natural mechanisms of seed dispersal show a rich source of robust, highly adaptive, mass and energy efficient mechanisms for optimized passive flying, landing, crawling and drilling. The secret of seeds mobility is embodied in the structural features and anatomical characteristics of their tissues, which are designed to be selectively responsive to changes in the environmental conditions, and which make seeds one of the most fascinating examples of morphological computation in Nature. Particularly clever for their spatial mobility performance, are those seeds that use their morphology and structural characteristics to be carried by the wind and dispersed over great distances (i.e. “winged” and “parachute” seeds), and seeds able to move and penetrate in soil with a self-burial mechanism driven by their hygromorphic properties and morphological features. By looking at their motion mechanisms, new design principles can be extracted and used as inspiration for smart artificial systems endowed with embodied intelligence. This mini-review systematically collects, for the first time together, the morphological, structural, biomechanical and aerodynamic information from selected plant seeds relevant to take inspiration for engineering design of soft robots, and discusses potential future developments in the field across material science, plant biology, robotics and embodied intelligence.

Embodied Intelligence in Soft Robotics Through Hardware Multifunctionality

The soft robotics community is currently wondering what the future of soft robotics is. Therefore, it is very important to identify the directions in which the community should focus its efforts to consolidate its impact. The identification of convincing applications is a priority, especially to demonstrate that some achievements already represent an attractive alternative to current technological approaches in specific scenarios. However, most of the added value of soft robotics has been only theoretically grasped. Embodied Intelligence, being of these theoretical principles, represents an interesting approach to fully exploit soft robotic’s potential, but a pragmatic application of this theory still remains difficult and very limited. A different design approach could be beneficial, i.e., the integration of a certain degree of continuous adaptability in the hardware functionalities of the robot, namely, a “flexible” design enabled by hardware components able to fulfill multiple functionalities. In this paper this concept of flexible design is introduced along with its main technological and theoretical basic elements. The potential of the approach is demonstrated through a biological comparison and the feasibility is supported by practical examples with state-of-the-art technologies.

Body of Intelligence: A Response to Jennifer Herdt

This response to Jennifer Herdt’s paper, ‘Partisan Epistemology and Post-Truth Power’, looks to embodied intelligence for help in discerning integrity and truthfulness.

Embodied intelligence via learning and evolution

The intertwined processes of learning and evolution in complex environmental niches have resulted in a remarkable diversity of morphological forms. Moreover, many aspects of animal intelligence are deeply embodied in these evolved morphologies. However, the principles governing relations between environmental complexity, evolved morphology, and the learnability of intelligent control, remain elusive, because performing large-scale in silico experiments on evolution and learning is challenging. Here, we introduce Deep Evolutionary Reinforcement Learning (DERL): a computational framework which can evolve diverse agent morphologies to learn challenging locomotion and manipulation tasks in complex environments. Leveraging DERL we demonstrate several relations between environmental complexity, morphological intelligence and the learnability of control. First, environmental complexity fosters the evolution of morphological intelligence as quantified by the ability of a morphology to facilitate the learning of novel tasks. Second, we demonstrate a morphological Baldwin effect i.e., in our simulations evolution rapidly selects morphologies that learn faster, thereby enabling behaviors learned late in the lifetime of early ancestors to be expressed early in the descendants lifetime. Third, we suggest a mechanistic basis for the above relationships through the evolution of morphologies that are more physically stable and energy efficient, and can therefore facilitate learning and control.

On the Mathematical Modeling of Slender Biomedical Continuum Robots

The passive, mechanical adaptation of slender, deformable robots to their environment, whether the robot be made of hard materials or soft ones, makes them desirable as tools for medical procedures. Their reduced physical compliance can provide a form of embodied intelligence that allows the natural dynamics of interaction between the robot and its environment to guide the evolution of the combined robot-environment system. To design these systems, the problems of analysis, design optimization, control, and motion planning remain of great importance because, in general, the advantages afforded by increased mechanical compliance must be balanced against penalties such as slower dynamics, increased difficulty in the design of control systems, and greater kinematic uncertainty. The models that form the basis of these problems should be reasonably accurate yet not prohibitively expensive to formulate and solve. In this article, the state-of-the-art modeling techniques for continuum robots are reviewed and cast in a common language. Classical theories of mechanics are used to outline formal guidelines for the selection of appropriate degrees of freedom in models of continuum robots, both in terms of number and of quality, for geometrically nonlinear models built from the general family of one-dimensional rod models of continuum mechanics. Consideration is also given to the variety of actuators found in existing designs, the types of interaction that occur between continuum robots and their biomedical environments, the imposition of constraints on degrees of freedom, and to the numerical solution of the family of models under study. Finally, some open problems of modeling are discussed and future challenges are identified.

Stretchable origami robotic arm with omnidirectional bending and twisting

Inspired by the embodied intelligence observed in octopus arms, we introduce magnetically controlled origami robotic arms based on Kresling patterns for multimodal deformations, including stretching, folding, omnidirectional bending, and twisting. The highly integrated motion of the robotic arms is attributed to inherent features of the reconfigurable Kresling unit, whose controllable bistable deploying/folding and omnidirectional bending are achieved through precise magnetic actuation. We investigate single- and multiple-unit robotic systems, the latter exhibiting higher biomimetic resemblance to octopus’ arms. We start from the single Kresling unit to delineate the working mechanism of the magnetic actuation for deploying/folding and bending. The two-unit Kresling assembly demonstrates the basic integrated motion that combines omnidirectional bending with deploying. The four-unit Kresling assembly constitutes a robotic arm with a larger omnidirectional bending angle and stretchability. With the foundation of the basic integrated motion, scalability of Kresling assemblies is demonstrated through distributed magnetic actuation of double-digit number of units, which enables robotic arms with sophisticated motions, such as continuous stretching and contracting, reconfigurable bending, and multiaxis twisting. Such complex motions allow for functions mimicking octopus arms that grasp and manipulate objects. The Kresling robotic arm with noncontact actuation provides a distinctive mechanism for applications that require synergistic robotic motions for navigation, sensing, and interaction with objects in environments with limited or constrained access. Based on small-scale Kresling robotic arms, miniaturized medical devices, such as tubes and catheters, can be developed in conjunction with endoscopy, intubation, and catheterization procedures using functionalities of object manipulation and motion under remote control.

Thinking like a State - Embodied intelligence in the deep history of our collective minds

This article aims to show how the deep history of early State societies entails the development of a collective form of cognitive agency. It relates classical works in the anthropology of States (in particular Scott’s Seeing like a State) with the enactive account of biological and cognitive organisation, thanks to the unified ontology for self-organisation dynamics across scales offered by the Active Inference framework. Active Inference conceives of cognition as synchronisation across individuated sensorimotor states. It entails that biological or sociocultural constraints display a minimal form of cognition by shaping the behaviour of faster dynamics in a certain way. When such constraints collectively define a basic life form (an integrated, operationally closed system), they can therefore be said to embody adaptive knowledge properly speaking.The (en)Active Inference account I articulate here strongly motivates and methodologically grounds a holist approach in the social sciences. Indeed, it grounds the study of human societies in the role of structural constraints, whose “meaning” depends both on the broader system’s activity and in the historical context of their emergence. The present account of the dynamics of early urbanisation and State genesis aims to illustrate this approach.

A Pattern Language for Social Field Shifts

The complex systemic issues of today, including climate change, racism, social inequality, mental health crisis, call for new ways of engaging the heart (feeling), mind (thinking), and will (doing) to actually change deep-rooted behaviors. To develop these new ways of engaging, one must learn how to cultivate first, one’s interior condition (the inner place from which we operate) and second, one's capacities to co-create with others the exterior conditions for healthy social relationships. In this paper, we claim that by living in a body we are embodied and that wisdom lives in a holistic knowing that includes embodied intelligence. We argue that to address the complex challenges of our times, we must cultivate embodied and perceptual capacities and a language for our embodied experience(s). Over three years of workshops with advanced practitioners of an embodied practice called Social Presencing Theater (SPT), we used embodied activities and design prompts (drawing, photo, video) to surface and make visible social patterns. This has led us to develop a language in the context of social systems change, in particular of social field shifts (i.e., transformations in the relational and felt qualities of our social systems). Through this paper we aim to contribute to social field research by proposing an embodied, visual, and verbal language for social groups to describe and reflect on social field shifts, made up of two parts: first, an aesthetic language to describe social field qualities; and second, three families of social field archetypes to describe social fields.