Revealing bending and force in a soft body through a plant root inspired approach

A Soft Inductive Bimodal Sensor for Proprioception and Tactile Sensing of Soft Machines

The somatosensory system is crucial for living beings to survive and thrive in complex environments and to interact with their surroundings. Similarly, rapidly developed soft robots need to be aware of their own posture and detect external stimuli. Bending and force sensing are key for soft machines to achieve embodied intelligence. Here, we present a soft inductive bimodal sensor (SIBS) that uses the strain modulation of magnetic permeability and the eddy-current effect for simultaneous bidirectional bending and force sensing with only two wires. The SIBS is made of a flexible planar coil, a porous ferrite film, and a soft conductive film. By measuring the inductance at two different frequencies, the bending angle and force can be obtained and decoupled. Rigorous experiments revealed that the SIBS can achieve high resolution (0.44° bending and 1.09 mN force), rapid response, excellent repeatability, and high durability. A soft crawling robot embedded with one SIBS can sense its own shape and interact with and respond to external stimuli. Moreover, the SIBS is demonstrated as a wearable human-machine interaction to control a crawling robot via wrist bending and touching. This highlights that the SIBS can be readily implemented in diverse applications for reliable bimodal sensing.

A mechanical theory of competition between plant root growth and soil pressure reveals a potential mechanism of root penetration

Root penetration into the soil is essential for plants to access water and nutrients, as well as to mechanically support aboveground structures. This requires a combination of healthy plant growth, adequate soil mechanical properties, and compatible plant-soil interactions. Despite the current knowledge of the static rheology driving the interactions at the root-soil interface, few theoretical approaches have attempted to describe root penetration with dynamic rheology. In this work, we experimentally showed that radish roots in contact with soil of specific density during a specific growth stage fail to penetrate the soil. To explore the mechanism of root penetration into the soil, we constructed a theoretical model to explore the relevant conditions amenable to root entry into the soil. The theory indicates that dimensionless parameters such as root growth anisotropy, static root-soil competition, and dynamic root-soil competition are important for root penetration. The consequent theoretical expectations were supported by finite element analysis, and a potential mechanism of root penetration into the soil is discussed.

A perspective on plant robotics: from bioinspiration to hybrid systems

As miscellaneous as the Plant Kingdom is, correspondingly diverse are the opportunities for taking inspiration from plants for innovations in science and engineering. Especially in robotics, properties like growth, adaptation to environments, ingenious materials, sustainability, and energy-effectiveness of plants provide an extremely rich source of inspiration to develop new technologies-and many of them are still in the beginning of being discovered. In the last decade, researchers have begun to reproduce complex plant functions leading to functionality that goes far beyond conventional robotics and this includes sustainability, resource saving, and eco-friendliness. This perspective drawn by specialists in different related disciplines provides a snapshot from the last decade of research in the field and draws conclusions on the current challenges, unanswered questions on plant functions, plant-inspired robots, bioinspired materials, and plant-hybrid systems looking ahead to the future of these research fields.

Wireless Miniature Magnetic Phase-Change Soft Actuators

Wireless miniature soft actuators are promising for various potential high-impact applications in medical, robotic grippers, and artificial muscles. However, these miniature soft actuators are currently constrained by a small output force and low work capacity. To address such challenges, a miniature magnetic phase-change soft composite actuator is reported. This soft actuator exhibits an expanding deformation and enables up to a 70 N output force and 175.2 J g-1 work capacity under remote magnetic radio frequency heating, which are 106 -107 times that of traditional magnetic soft actuators. To demonstrate its capabilities, a wireless soft robotic device is first designed that can withstand 0.24 m s-1 fluid flows in an artery phantom. By integrating it with a thermally-responsive shape-memory polymer and bistable metamaterial sleeve, a wireless reversible bistable stent is designed toward future potential angioplasty applications. Moreover, it can additionally locomote inside and jump out of granular media. At last, the phase-change actuator can realize programmable bending deformations when a specifically designed magnetization profile is encoded, enhancing its shape-programming capability. Such a miniature soft actuator provides an approach to enhance the mechanical output and versatility of magnetic soft robots and devices, extending their medical and other potential applications.

Root Cap to Soil Interface: A Driving Force Toward Plant Adaptation and Development

Land plants have developed robust roots to grow in diverse soil ecosystems. The distal end of the root tip has a specialized organ called the 'root cap'. The root cap assists the roots in penetrating the ground, absorbing water and minerals, avoiding heavy metals and regulating the rhizosphere microbiota. Furthermore, root-cap-derived auxin governs the lateral root patterning and directs root growth under varying soil conditions. The root cap formation is hypothesized as one of the key innovations during root evolution. Morphologically diversified root caps in early land plant lineage and later in angiosperms aid in improving the adaptation of roots and, thereby, plants in diverse soil environments. This review article presents a retrospective view of the root cap's important morphological and physiological characteristics for the root-soil interaction and their response toward various abiotic and biotic stimuli. Recent single-cell RNAseq data shed light on root cap cell-type-enriched genes. We compiled root cap cell-type-enriched genes from Arabidopsis, rice, maize and tomato and analyzed their transcription factor (TF) binding site enrichment. Further, the putative gene regulatory networks derived from root-cap-enriched genes and their TF regulators highlight the species-specific biological functions of root cap genes across the four plant species.

From a Deployable Soft Mechanism Inspired by a Nemertea Proboscis to a Robotic Blood Vessel Mechanism

In this project, we aim to establish a design theory as well as implementation methods for deformable robot mechanisms that can branch and change in shape, structure, and stiffness. As the first step in our research on this project, we present an initial prototype of a branched torus mechanism that uses an inflatable structure inspired by a nemertea proboscis. We develop a basic mechanical model of this proboscis structure, and we confirm the basic performance and effective functionality of the configuration experimentally using a real prototype, specifically, a deployable torus mechanism and a retractable torus mechanism with an incompressible fluid. In addition, as an expanded concept from the branched torus mechanism, robotic blood vessels that can have an active self-healing function are prototyped, and the basic performance of the actual prototype is confirmed through experiments.

Extra-Soft Tactile Sensor for Sensitive Force/Displacement Measurement with High Linearity Based on a Uniform Strength Beam

The soft sensing system has drawn huge enthusiasm for the application of soft robots and healthcare recently. Most of them possess thin-film structures that are beneficial to monitoring strain and pressure, but are unfavorable for measuring normal displacement with high linearity. Here we propose soft tactile sensors based on uniform-strength cantilever beams that can be utilized to measure the normal displacement and force of soft objects simultaneously. First, the theoretical model of the sensors is constructed, on the basis of which, the sensors are fabricated for testing their sensing characteristics. Next, the test results validate the constructed model, and demonstrate that the sensors can measure the force as well as the displacement. Besides, the self-fabricated sensor can have such prominent superiorities as follows—it is ultra-soft, and its equivalent stiffness is only 0.31 N·m⁻¹ (approximately 0.4% of fat); it has prominent sensing performance with excellent linearity (R² = 0.999), high sensitivity of 0.533 pF·mm⁻¹ and 1.66 pF·mN⁻¹ for measuring displacement and force; its detection limit is as low as 70 μm and 20 μN that is only one-tenth of the touch of a female fingertip. The presented sensor highlights a new idea for measuring the force and displacement of the soft objects with broad application prospects in mechanical and medical fields.

Heterogeneous sensing in a multifunctional soft sensor for human-robot interfaces

Soft sensors have been playing a crucial role in detecting different types of physical stimuli to part or the entire body of a robot, analogous to mechanoreceptors or proprioceptors in biology. Most of the currently available soft sensors with compact form factors can detect only a single deformation mode at a time due to the limitation in combining multiple sensing mechanisms in a limited space. However, realizing multiple modalities in a soft sensor without increasing its original form factor is beneficial, because even a single input stimulus to a robot may induce a combination of multiple modes of deformation. Here, we report a multifunctional soft sensor capable of decoupling combined deformation modes of stretching, bending, and compression, as well as detecting individual deformation modes, in a compact form factor. The key enabling design feature of the proposed sensor is a combination of heterogeneous sensing mechanisms: optical, microfluidic, and piezoresistive sensing. We characterize the performance on both detection and decoupling of deformation modes, by implementing both a simple algorithm of threshold evaluation and a machine learning technique based on an artificial neural network. The proposed soft sensor is able to estimate eight different deformation modes with accuracies higher than 95%. We lastly demonstrate the potential of the proposed sensor as a method of human-robot interfaces with several application examples highlighting its multifunctionality.

The Bio-Engineering Approach for Plant Investigations and Growing Robots. A Mini-Review

It has been 10 years since the publication of the first article looking at plants as a biomechatronic system and as model for robotics. Now, roboticists have started to look at plants differently and consider them as a model in the field of bioinspired robotics. Despite plants have been seen traditionally as passive entities, in reality they are able to grow, move, sense, and communicate. These features make plants an exceptional example of morphological computation - with probably the highest level of adaptability among all living beings. They are a unique model to design robots that can act in- and adapt to- unstructured, extreme, and dynamically changing environments exposed to sudden or long-term events. Although plant-inspired robotics is still a relatively new field, it has triggered the concept of growing robotics: an emerging area in which systems are designed to create their own body, adapt their morphology, and explore different environments. There is a reciprocal interest between biology and robotics: plants represent an excellent source of inspiration for achieving new robotic abilities, and engineering tools can be used to reveal new biological information. This way, a bidirectional biology-robotics strategy provides mutual benefits for both disciplines. This mini-review offers a brief overview of the fundamental aspects related to a bioengineering approach in plant-inspired robotics. It analyses the works in which both biological and engineering aspects have been investigated, and highlights the key elements of plants that have been milestones in the pioneering field of growing robots.

Plant Bioinspired Ecological Robotics

Plants are movers, but the nature of their movement differs dramatically from that of creatures that move their whole body from point A to point B. Plants grow to where they are going. Bio-inspired robotics sometimes emulates plants' growth-based movement; but growing is part of a broader system of movement guidance and control. We argue that ecological psychology's conception of "information" and "control" can simultaneously make sense of what it means for a plant to navigate its environment and provide a control scheme for the design of ecological plant-inspired robotics. In this effort, we will outline several control laws and give special consideration to the class of control laws identified by tau theory, such as time to contact.

Development of a New Multi-cavity Pneumatic-driven Earthworm-like Soft Robot

This paper presents a soft robot which can imitate the crawling locomotion of an earthworm. Locomotion of the robot can be achieved by expanding and contracting the body that is made of flexible material. A link of the earthworm-like robot is combined with three modules, and a multi-cavity earthworm-like soft robot is combined with multiple links. The multiple links of the earthworm-like soft robot are fabricated by silicone in the three-dimensional printed customized molds. Experiments on a single module, two-links, and three-links show that the soft robot can move and bend on condition of modules extension and contraction in a specified gait. The development of the earthworm-like soft robot shows a great prospect in many complicated environments such as pipeline detection.

Fabrication and Dynamic Modeling of Bidirectional Bending Soft Actuator Integrated with Optical Waveguide Curvature Sensor

Soft robots exhibit many exciting properties due to their softness and body compliance. However, to interact with the environment safely and to perform a task effectively, a soft robot faces a series of challenges such as dexterous motion, proprioceptive sensing, and robust control of its deformable bodies. To address these issues, this article presents a method for fabrication and dynamic modeling of a novel bidirectional bending soft pneumatic actuator that embeds a curvature proprioceptive sensor. The bidirectional bending deformation was generated by two similar chambers with a sinusoidal shape for reducing the internal dampness during bending deformation. An optical waveguide made from flexible poly (methyl methacrylate) material that is immune to the inlet pressure was embedded into the actuator body to measure its bending angle. A dynamic modeling framework based on step response and parameter fitting was proposed to establish a simple differential equation that can describe the nonlinear behavior of the soft actuator. Hence, a sliding mode controller is designed based on this differential equation and the Taylor expansion. The proposed dynamical model and the sliding mode controller were validated by trajectory tracking experiments. The performance of the bidirectional bending soft actuator, such as the linear output of the curvature sensor in different inflating patterns, the proprioceptive sensitiveness to the external environment, the output force, and large bending range under relatively small pressure, was evaluated by relevant experimental paradigms. Prototypes from the novel design and fabrication process demonstrated the soft actuator's potential applications in industrial grasping and hand rehabilitation.

Toward Perceptive Soft Robots: Progress and Challenges

In the past few years, soft robotics has rapidly become an emerging research topic, opening new possibilities for addressing real-world tasks. Perception can enable robots to effectively explore the unknown world, and interact safely with humans and the environment. Among all extero- and proprioception modalities, the detection of mechanical cues is vital, as with living beings. A variety of soft sensing technologies are available today, but there is still a gap to effectively utilize them in soft robots for practical applications. Here, the developments in soft robots with mechanical sensing are summarized to provide a comprehensive understanding of the state of the art in this field. Promising sensing technologies for mechanically perceptive soft robots are described, categorized, and their pros and cons are discussed. Strategies for designing soft sensors and criteria to evaluate their performance are outlined from the perspective of soft robotic applications. Challenges and trends in developing multimodal sensors, stretchable conductive materials and electronic interfaces, modeling techniques, and data interpretation for soft robotic sensing are highlighted. The knowledge gap and promising solutions toward perceptive soft robots are discussed and analyzed to provide a perspective in this field.

Toward Growing Robots: A Historical Evolution from Cellular to Plant-Inspired Robotics

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.

Soft Smart Garments for Lower Limb Joint Position Analysis

Revealing human movement requires lightweight, flexible systems capable of detecting mechanical parameters (like strain and pressure) while being worn comfortably by the user, and not interfering with his/her activity. In this work we address such multifaceted challenge with the development of smart garments for lower limb motion detection, like a textile kneepad and anklet in which soft sensors and readout electronics are embedded for retrieving movement of the specific joint. Stretchable capacitive sensors with a three-electrode configuration are built combining conductive textiles and elastomeric layers, and distributed around knee and ankle. Results show an excellent behavior in the ~30% strain range, hence the correlation between sensors' responses and the optically tracked Euler angles is allowed for basic lower limb movements. Bending during knee flexion/extension is detected, and it is discriminated from any external contact by implementing in real time a low computational algorithm. The smart anklet is designed to address joint motion detection in and off the sagittal plane. Ankle dorsi/plantar flexion, adduction/abduction, and rotation are retrieved. Both knee and ankle smart garments show a high accuracy in movement detection, with a RMSE less than 4° in the worst case.

Integrated Simultaneous Detection of Tactile and Bending Cues for Soft Robotics

Soft robots should move in an unstructured environment and explore it and, to do so, they should be able to measure and distinguish proprioceptive and exteroceptive stimuli. This can be done by embedding mechanosensing systems in the body of the robot. Here, we present a polydimethylsiloxane block sensorized with an electro-optical system and a resistive strain gauge made with the supersonic cluster beam implantation (SCBI) technique. We show how to integrate these sensing elements during the whole fabrication process of the soft body and we demonstrate that their presence does not change the mechanical properties of the bulk material. Exploiting the position of both sensing systems and a proper combination of the output signals, we present a strategy to measure simultaneously external pressure and positive/negative bending of the body. In particular, the optical system can reveal any mechanical stimulation (external from the soft block or due to its own deformation), while the resistive strain gauge is insensitive to the external pressure, but sensitive to the bending of the body. This solution, here applied to a simple block of soft material, could be extended to the whole body of a soft robot. This approach provides detection and discrimination of the two stimuli (pressure and bending), with low computational effort and without significant mechanical constraint.

Can a Soft Robotic Probe Use Stiffness Control Like a Human Finger to Improve Efficacy of Haptic Perception?

When humans are asked to palpate a soft tissue to locate a hard nodule, they regulate the stiffness, speed, and force of the finger during examination. If we understand the relationship between these behavioral variables and haptic information gain (transfer entropy) during manual probing, we can improve the efficacy of soft robotic probes for soft tissue palpation, such as in tumor localization in minimally invasive surgery. Here, we recorded the muscle co-contraction activity of the finger using EMG sensors to address the question as to whether joint stiffness control during manual palpation plays an important role in the haptic information gain. To address this question, we used a soft robotic probe with a controllable stiffness joint and a force sensor mounted at the base to represent the function of the tendon in a biological finger. Then, we trained a Markov chain using muscle co-contraction patterns of human subjects, and used it to control the stiffness of the soft robotic probe in the same soft tissue palpation task. The soft robotic experiments showed that haptic information gain about the depth of the hard nodule can be maximized by varying the internal stiffness of the soft probe.

A plant-inspired robot with soft differential bending capabilities

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.

Adaptation of sensor morphology: an integrative view of perception from biologically inspired robotics perspective

Sensor morphology, the morphology of a sensing mechanism which plays a role of shaping the desired response from physical stimuli from surroundings to generate signals usable as sensory information, is one of the key common aspects of sensing processes. This paper presents a structured review of researches on bioinspired sensor morphology implemented in robotic systems, and discusses the fundamental design principles. Based on literature review, we propose two key arguments: first, owing to its synthetic nature, biologically inspired robotics approach is a unique and powerful methodology to understand the role of sensor morphology and how it can evolve and adapt to its task and environment. Second, a consideration of an integrative view of perception by looking into multidisciplinary and overarching mechanisms of sensor morphology adaptation across biology and engineering enables us to extract relevant design principles that are important to extend our understanding of the unfinished concepts in sensing and perception.

Root hairs aid soil penetration by anchoring the root surface to pore walls

The physical role of root hairs in anchoring the root tip during soil penetration was examined. Experiments using a hairless maize mutant (Zea mays: rth3-3) and its wild-type counterpart measured the anchorage force between the primary root of maize and the soil to determine whether root hairs enabled seedling roots in artificial biopores to penetrate sandy loam soil (dry bulk density 1.0-1.5g cm(-3)). Time-lapse imaging was used to analyse root and seedling displacements in soil adjacent to a transparent Perspex interface. Peak anchorage forces were up to five times greater (2.5N cf. 0.5N) for wild-type roots than for hairless mutants in 1.2g cm(-3) soil. Root hair anchorage enabled better soil penetration for 1.0 or 1.2g cm(-3) soil, but there was no significant advantage of root hairs in the densest soil (1.5g cm(-3)). The anchorage force was insufficient to allow root penetration of the denser soil, probably because of less root hair penetration into pore walls and, consequently, poorer adhesion between the root hairs and the pore walls. Hairless seedlings took 33h to anchor themselves compared with 16h for wild-type roots in 1.2g cm(-3) soil. Caryopses were often pushed several millimetres out of the soil before the roots became anchored and hairless roots often never became anchored securely.The physical role of root hairs in anchoring the root tip may be important in loose seed beds above more compact soil layers and may also assist root tips to emerge from biopores and penetrate the bulk soil.