A broad diversity of biological organisms and systems interact with soil in ways that facilitate their growth and survival. These interactions are made possible by strategies that enable organisms to accomplish functions that can be analogous to those required in geotechnical engineering systems. Examples include anchorage in soft and weak ground, penetration into hard and stiff subsurface materials and movement in loose sand. Since the biological strategies have been ‘vetted’ by the process of natural selection, and the functions they accomplish are governed by the same physical laws in both the natural and engineered environments, they represent a unique source of principles and design ideas for addressing geotechnical challenges. Prior to implementation as engineering solutions, however, the differences in spatial and temporal scales and material properties between the biological environment and engineered system must be addressed. Current bio-inspired geotechnics research is addressing topics such as soil excavation and penetration, soil–structure interface shearing, load transfer between foundation and anchorage elements and soils, and mass and thermal transport, having gained inspiration from organisms such as worms, clams, ants, termites, fish, snakes and plant roots. This work highlights the potential benefits to both geotechnical engineering through new or improved solutions and biology through understanding of mechanisms as a result of cross-disciplinary interactions and collaborations.

Octopuses have impressive manipulation capabilities empowered by the intrinsic adaptation of their soft arms combined with distributed suckers. Drawing inspiration from the arm morphology and abilities of the octopus, the integrated design of a conical soft robotic arm endowed with suction cups is presented herein. The proposed arm exploits soft robotic technologies as in materials (combining stiff and soft silicones) and actuation (tendons to drive motion and fluidic channels for suction cup actuation) for retrieving objects in confined spaces of unknown shapes and sizes. The soft arm is able to grasp varied and complex‐shaped objects, to move in air, water, and oil, and to retrieve items immersed in a 70 mm diameter pipe, under pressure (up to 18 bar). Suction cups enable the arm to retrieve objects that would be impossible to grasp without them and help in improving the grasping force up to ≈1.4 times in air, ≈2.4 times in water, and ≈12.5 times in oil. The enhanced holding force (up to 3.3 N, ≈3.9 times arm weight) and a wide spectrum of objects negotiable by the arm make it a universal tool for object retrieval in confined spaces and wet conditions.

Soft robotics aims at creating systems with improved performance of movement and adaptability in unknown, challenging, environments and with higher level of safety during interactions with humans. This Roadmap on Soft Robotics covers selected aspects for the design of soft robots significantly linked to the area of multifunctional materials, as these are considered a fundamental component in the design of soft robots for an improvement of their peculiar abilities, such as morphing, adaptivity and growth. The roadmap includes different approaches for components and systems design, bioinspired materials, methodologies for building soft robots, strategies for the implementation and control of their functionalities and behavior, and examples of soft-bodied systems showing abilities across different environments. For each covered topic, the author(s) describe the current status and research directions, current and future challenges, and perspective advances in science and technology to meet the challenges.

Self-growing robots are an emerging solution in soft robotics for navigating, exploring, and colonizing unstructured environments. However, their ability to grow and move in heterogeneous three-dimensional (3D) spaces, comparable with real-world conditions, is still developing. We present an autonomous growing robot that draws inspiration from the behavioral adaptive strategies of climbing plants to navigate unstructured environments. The robot mimics climbing plants’ apical shoot to sense and coordinate additive adaptive growth via an embedded additive manufacturing mechanism and a sensorized tip. Growth orientation, comparable with tropisms in real plants, is dictated by external stimuli, including gravity, light, and shade. These are incorporated within a vector field method to implement the preferred adaptive behavior for a given environment and task, such as growth toward light and/or against gravity. We demonstrate the robot’s ability to navigate through growth in relation to voids, potential supports, and thoroughfares in otherwise complex habitats. Adaptive twining around vertical supports can provide an escape from mechanical stress due to self-support, reduce energy expenditure for construction costs, and develop an anchorage point to support further growth and crossing gaps. The robot adapts its material printing parameters to develop a light body and fast growth to twine on supports or a tougher body to enable self-support and cross gaps. These features, typical of climbing plants, highlight a potential for adaptive robots and their on-demand manufacturing. They are especially promising for applications in exploring, monitoring, and interacting with unstructured environments or in the autonomous construction of complex infrastructures.

We present the design and development of a plant-inspired robot, named Plantoid, with sensorized robotic roots. Natural roots have a multi-sensing capability and show a soft bending behaviour to follow or escape from various environmental parameters (i.e., tropisms). Analogously, we implement soft bending capabilities in our robotic roots by designing and integrating soft spring-based actuation (SSBA) systems using helical springs to transmit the motor power in a compliant manner. Each robotic tip integrates four different sensors, including customised flexible touch and innovative humidity sensors together with commercial gravity and temperature sensors. We show how the embedded sensing capabilities together with a root-inspired control algorithm lead to the implementation of tropic behaviours. Future applications for such plant-inspired technologies include soil monitoring and exploration, useful for agriculture and environmental fields.

This paper provides the very first definition of “growing robots”: a category of robots that imitates biological growth by the incremental addition of material. Although this nomenclature is quite new, the concept of morphological evolution, which is behind growth, has been extensively addressed in engineering and robotics. In fact, the idea of reproducing processes that belong to living systems has always attracted scientists and engineers. The creation of systems that adapt reliably and effectively to the environment with their morphology and control would be beneficial for many different applications, including terrestrial and space exploration or the monitoring of disasters or dangerous environments. Different approaches have been proposed over the years for solving the morphological adaptation of artificial systems, e.g., self-assembly, self-reconfigurability, evolution of virtual creatures, plant inspiration. This work reviews the main milestones in relation to growing robots, starting from the original concept of a self-replicating automaton to the achievements obtained by plant inspiration, which provided an alternative solution to the challenges of creating robots with self-building capabilities. A selection of robots representative of growth functioning is also discussed, grouped by the natural element used as model: molecule, cell, or organism growth-inspired robots. Finally, the historical evolution of growing robots is outlined together with a discussion of the future challenges toward solutions that more faithfully can represent biological growth.