Body-environment Interactions Research Articles

Towards the optimization of passive undulatory locomotion on land: mathematical and physical models.

The current study investigates the body-environment interaction and exploits the passive viscoelastic properties of the body to perform undulatory locomotion. The investigations are carried out using a mathematical model based on a dry frictional environment, and the results are compared with the performance obtained using a physical model. The physical robot is a wheel-based modular system with flexible joints moving on different substrates. The influence of the spatial distribution of body stiffness on speed performance is also investigated. Our results suggest that the environment affects the performance of undulatory locomotion based on the distribution of body stiffness. While stiffness may vary with the environment, we have established a qualitative constitutive law that holds across environments. Specifically, we expect the stiffness distribution to exhibit either an ascending-descending or an ascending-plateau pattern along the length of the object, from head to tail. Furthermore, undulatory locomotion showed sensitivity to contact mechanics: solid-solid or solid-viscoelastic contact produced different locomotion kinematics. Our results elucidate how terrestrial limbless animals achieve undulatory locomotion performance by exploiting the passive properties of the environment and the body. Application of the results obtained may lead to better performing long-segmented robots that exploit the suitability of passive body dynamics and the properties of the environment in which they need to move.

Body Stiffness Control for Using Body-Environment Interaction with a Closed-Link Deformable Mobile Robot

It is necessary for the robot to use interactions from the environment through the body in order to adaptively move through various environments. When the robot is faced with a narrow path or a space with many pillars, it should be able to use its interaction with the environment to thin its own shape, i.e., it should have a flexible body. In contrast, in the case where we want the robot to move forward powerfully on a slope or uneven terrain (small steps), it is preferable for the robot to rigidify its own body and exert a strong propulsive force in response to interactions from the environment. In this paper, we present an idea of a mobile robot that can adjust its body flexibility (stiffness) to realize such adaptive behavior, and furthermore, we demonstrate its validity through experiments. Specifically, we propose a closed-link deformable mobile robot whose stiffness can be adjusted by indirectly driving joints. We design a function that increases the stiffness of the body by controlling the joints to follow the target angle quickly, and a function that decreases the stiffness of the body by controlling the joints to follow the angle slowly. The effectiveness of a robot that can adjust its stiffness is demonstrated through experiments of traversing narrow paths and steps. We also discuss propulsion control that takes advantage of the deformable mobile robot and its applicability to uneven slopes due to the flexibility of the links.

On special issue “Passive Locomotion from Body-Environment Interactions”

On special issue “Passive Locomotion from Body-Environment Interactions”

Body and peripersonal space representations in chronic stroke patients with upper limb motor deficits.

The continuous stream of multisensory information between the brain and the body during body–environment interactions is crucial to maintain the updated representation of the perceived dimensions of body parts (metric body representation) and the space around the body (the peripersonal space). Such flow of multisensory signals is often limited by upper limb sensorimotor deficits after stroke. This would suggest the presence of systematic distortions of metric body representation and peripersonal space in chronic patients with persistent sensorimotor deficits. We assessed metric body representation and peripersonal space representation in 60 chronic stroke patients with unilateral upper limb motor deficits, in comparison with age-matched healthy controls. We also administered a questionnaire capturing explicit feelings towards the affected limb. These novel measures were analysed with respect to patients’ clinical profiles and brain lesions to investigate the neural and functional origin of putative deficits. Stroke patients showed distortions in metric body representation of the affected limb, characterized by an underestimation of the arm length and an alteration of the arm global shape. A descriptive lesion analysis (subtraction analysis) suggests that these distortions may be more frequently associated with lesions involving the superior corona radiata and the superior frontal gyrus. Peripersonal space representation was also altered, with reduced multisensory facilitation for stimuli presented around the affected limb. These deficits were more common in patients reporting pain during motion. Explorative lesion analyses (subtraction analysis, disconnection maps) suggest that the peripersonal space distortions would be more frequently associated with lesions involving the parietal operculum and white matter frontoparietal connections. Moreover, patients reported altered feelings towards the affected limb, which were associated with right brain damage, proprioceptive deficits and a lower cognitive profile. These results reveal implicit and explicit distortions involving metric body representation, peripersonal space representation and the perception of the affected limb in chronic stroke patients. These findings might have important clinical implications for the longitudinal monitoring and the treatments of often-neglected deficits in body perception and representation.

Coordinating tiny limbs and long bodies: Geometric mechanics of lizard terrestrial swimming

Although typically possessing four limbs and short bodies, lizards have evolved diverse morphologies, including elongate trunks with tiny limbs. Such forms are hypothesized to aid locomotion in cluttered/fossorial environments but propulsion mechanisms (e.g., the use of body and/or limbs to interact with substrates) and potential body/limb coordination remain unstudied. Here, we use biological experiments, a geometric theory of locomotion, and robophysical models to investigate body-limb coordination in diverse lizards. Locomotor field studies in short-limbed, elongate lizards (Brachymeles and Lerista) and laboratory studies of fully limbed lizards (Uma scoparia and Sceloporus olivaceus) and a snake (Chionactis occipitalis) reveal that body-wave dynamics can be described by a combination of standing and traveling waves; the ratio of the amplitudes of these components is inversely related to the degree of limb reduction and body elongation. The geometric theory (which replaces laborious calculation with diagrams) helps explain our observations, predicting that the advantage of traveling-wave body undulations (compared with a standing wave) emerges when the dominant thrust-generation mechanism arises from the body rather than the limbs and reveals that such soil-dwelling lizards propel via "terrestrial swimming" like sand-swimming lizards and snakes. We test our hypothesis by inducing the use of traveling waves in stereotyped lizards via modulating the ground-penetration resistance. Study of a limbed/undulatory robophysical model demonstrates that a traveling wave is beneficial when propulsion is generated by body-environment interaction. Our models could be valuable in understanding functional constraints on the evolutionary processes of elongation and limb reduction as well as advancing robot designs.

The evolution and development of consciousness: the subject-object emergence hypothesis

A strategy for investigating consciousness that has proven very productive has focused on comparing brain processes that are accompanied by consciousness with processes that are not. But comparatively little attention has been given to a related strategy that promises to be even more fertile. This strategy exploits the fact that as individuals develop, new classes of brain processes can transition from operating ‘in the dark’ to becoming conscious. It has been suggested that these transitions occur when a new class of brain processes becomes object to a new, emergent, higher-level subject. Similar transitions are likely to have occurred during evolution. An evolutionary/developmental research strategy sets out to identify the nature of the transitions in brain processes that shift them from operating in the dark to ‘lighting up’. The paper begins the application of this strategy by extrapolating the sequence of transitions back towards its origin. The goal is to reconstruct a minimally-complex, subject-object subsystem that would be capable of giving rise to consciousness and providing adaptive benefits. By focusing on reconstructing a subsystem that is simple and understandable, this approach avoids the homunculus fallacy. The reconstruction suggests that the emergence of such a minimally-complex subsystem was driven by its capacity to coordinate body-environment interactions in real time e.g. hand-eye coordination. Conscious processing emerged initially because of its central role in organising real-time sensorimotor coordination. The paper goes on to identify and examine a number of subsequent major transitions in consciousness, including the emergence of capacities for conscious mental modelling. Each transition is driven by its potential to solve adaptive challenges that cannot be overcome at lower levels. The paper argues that mental modelling arose out of a pre-existing capacity to use simulations of motor actions to anticipate the consequences of the actions. As the capacity developed, elements of the simulations could be changed, and the consequences of these changes could be ‘thought through’ consciously. This enabled alternative motor responses to be evaluated. The paper goes on to predict significant new major transitions in consciousness.

Review of Electronics-Free Robotics: Toward a Highly Decentralized Control Architecture

In recent years, conventional model-based motion control has become more challenging owing to the continuously increasing complexity of areas in which robots must operate and navigate. A promising approach for solving this issue is by employing interaction-based robotics, which includes behavior-based robotics, morphological computations, and soft robotics that generate control and computation functions based on interactions between the robot body and environment. These control strategies, which incorporate the diverse dynamics of the environment to generate control and computation functions, may alleviate the limitations imposed by the finite physical and computational resources of conventional robots. However, current interaction-based robots can only perform a limited number of actions compared with conventional robots. To increase the diversity of behaviors generated from body–environment interactions, a robotic body design methodology that can generate appropriate behaviors depending on the various situations and environmental stimuli that arise from them is necessitated. Electronics-free robotics is reviewed herein as a paradigm for designing robots with control and computing functions in each part of the body. In electronics-free robotics, instead of using electrical sensors or computers, a control system is constructed based on only mechanical or chemical reactions. Robotic bodies fabricated using this approach do not require bulky electrical wiring or peripheral circuits and can perform control and computational functions by obtaining energy from a central source. Therefore, by distributing these electronics-free controllers throughout the body, we hope to design autonomous and highly decentralized robotic bodies than can generate various behaviors in response to environmental stimuli. This new paradigm of designing and controlling robot bodies can enable realization of completely electronics-free robots as well as expand the range of conventional electronics-based robot designs.

Behavioral Diversity Generated From Body–Environment Interactions in a Simulated Tensegrity Robot

Behavioral Diversity Generated From Body–Environment Interactions in a Simulated Tensegrity Robot

Illusory tactile movement crosses arms and legs and is coded in external space

Humans often misjudge where on the body a touch occurred. Theoretical accounts have ascribed such misperceptions to local interactions in peripheral and primary somatosensory neurons, positing that spatial-perceptual mechanisms adhere to limb boundaries and skin layout. Yet, perception often reflects integration of sensory signals with prior experience. On their trajectories, objects often touch multiple limbs; therefore, body–environment interactions should manifest in perceptual mechanisms that reflect external space.Here, we demonstrate that humans perceived the cutaneous rabbit illusion – the percept of multiple identical stimuli as hopping across the skin – along the Euclidian trajectory between stimuli on two body parts and regularly mislocalized stimuli from one limb to the other. A Bayesian model based on Euclidian, as opposed to anatomical, distance faithfully reproduced key aspects of participants' localization behavior.Our results suggest that prior experience of touch in space critically shapes tactile spatial perception and illusions beyond anatomical organization.

Preceding Postural Control in Forelimb Reaching Movements in Cats.

Postural control precedes the goal-directed movement to maintain body equilibrium during the action. Because the environment continuously changes due to one’s activity, postural control requires a higher-order brain function that predicts the interaction between the body and the environment. Here, we tried to elucidate to what extent such a preceding postural control (PPC) predictively offered a posture that ensured the entire process of the goal-directed movement before starting the action. For this purpose, we employed three cats, which we trained to maintain a four-leg standing posture on force transducers to reach the target by either forelimb. Each cat performed the task under nine target locations in front with different directions and distances. As an index of posture, we employed the center of pressure (CVP) and examined CVP positions when the cat started postural alteration, began to lift its paw, and reached the target. After gazing at the target, each cat started PPC where postural alteration was accompanied by a 20–35 mm CVP shift to the opposite side of the forelimb to be lifted. Then, the cat lifted its paw at the predicted CVP position and reached the forelimb to the target with a CVP shift of only several mm. Moreover, each cat had an optimal target location where the relationship between the cat and target minimized the difference in the CVP positions between the predicted and the final. In this condition, more than 80% of the predicted CVP positions matched the final CVP positions, and the time requiring the reaching movement was the shortest. By contrast, the forelimb reaching movement required a greater CVP shift and longer time when the target was far from the cat. In addition, the time during forelimb reaching showed a negative correlation with the speed of the CVP shift during the PPC. These results suggest that the visuospatial information, such as the body-environment interaction, contributes to the motor programming of the PPC. We conclude that the PPC ensures postural stability throughout the action to optimize the subsequent goal-directed movements. Impairments in these processes may disturb postural stability during movements, resulting in falling.

Frontal and parietal background connectivity and their dynamic changes account for individual differences in the multisensory representation of peripersonal space

Functional connectivity (FC) of brain networks dynamically fluctuates during both rest and task execution. Individual differences in dynamic FC have been associated with several cognitive and behavioral traits. However, whether dynamic FC also contributes to sensorimotor representations guiding body-environment interactions, such as the representation of peripersonal space (PPS), is currently unknown. PPS is the space immediately surrounding the body and acts as a multisensory interface between the individual and the environment. We used an audio-tactile task with approaching sounds to map the individual PPS extension, and fMRI to estimate the background FC. Specifically, we analyzed FC values for each stimulus type (near and far space) and its across-trial variability. FC was evaluated between task-relevant nodes of two fronto-parietal networks (the Dorsal Attention Network, DAN, and the Fronto-Parietal Network, FPN) and a key PPS region in the premotor cortex (PM). PM was significantly connected to specific task-relevant nodes of the DAN and the FPN during the audio-tactile task, and FC was stronger while processing near space, as compared to far space. At the individual level, less PPS extension was associated with stronger premotor-parietal FC during processing of near space, while the across-trial variability of premotor-parietal and premotor-frontal FC was higher during the processing of far space. Notably, only across-trial FC variability captured the near-far modulation of space processing. Our findings indicate that PM connectivity with task-relevant frontal and parietal regions and its dynamic changes participate in the mechanisms that enable PPS representation, in agreement with the idea that neural variability plays a crucial role in plastic and dynamic sensorimotor representations.

L’eSoi : de l’hypotrophie de la représentation du corps à l’hypertrophie de l’image du soi

Screens bring a new element to the environment of the child and even more to that of the adolescent. As a new partner in their development, screens are increasingly retaining the child's attention, and have multiple effects. They alter the relationship to space, time and attention and introduce a new dimension in the construction of the sexuality of young people. They are challenging–for the moment–educational practices. But the impact of screens on young people also depends a lot on the context of use and the environment in which they live. Alongside the child, there are parents, with their educational practices and their own use of screens, and there is society, with its values, the benchmarks it offers to its members, its culture and its models. Screens have become ubiquitous and invite humans to interact through their accessibility, the amusing simplicity of their job and their possibilities of interactivity. This tool will promote and even stimulate the child's empowerment vis-à-vis parents in his discovery and exploration of the world. Access to a screen connected to the Internet explodes the possibilities of interactions and exploration of a virtual space that is almost infinite. More and more, there is a striking contrast between the increasing spatial framing of the child confined in socially dedicated places, the room, the parental apartment, then the school, spaces set up for his protection… and his freedom to explore and interact with the virtual environment made possible by the connected screens that parents offer him. For safety reasons, children, especially younger ones, are no longer being opened to the streets, and they spend less and less time in parks or natural spaces (forests, fields, rivers, etc.). Children are increasingly reclusive in the interior spaces of homes and in playgrounds designed for their safety, which sanitizes the encounter with the natural environment. In contrast to this physical framing, the child's framing in the discovery and exploration of the virtual world increasingly escapes parents, despite the “parental control” devices. In this article, we try to identify some of the effects of the significant use of screens by children and adolescents on the construction of space and on the relationship to their bodies illustrating it in clinical vignettes. Indeed, the body-environment interaction is at the basis of the construction of the representation of one's own body, as well as that of space, essential for the building of identity.

Continuous body 3-D reconstruction of limbless animals.

Limbless animals such as snakes, limbless lizards, worms, eels and lampreys move their slender, long bodies in three dimensions to traverse diverse environments. Accurately quantifying their continuous body's 3-D shape and motion is important for understanding body-environment interactions in complex terrain, but this is difficult to achieve (especially for local orientation and rotation). Here, we describe an interpolation method to quantify continuous body 3-D position and orientation. We simplify the body as an elastic rod and apply a backbone optimization method to interpolate continuous body shape between end constraints imposed by tracked markers. Despite over-simplifying the biomechanics, our method achieves a higher interpolation accuracy (∼50% error) in both 3-D position and orientation compared with the widely used cubic B-spline interpolation method. Beyond snakes traversing large obstacles as demonstrated, our method applies to other long, slender, limbless animals and continuum robots. We provide codes and demo files for easy application of our method.

General Distributed Neural Control and Sensory Adaptation for Self-Organized Locomotion and Fast Adaptation to Damage of Walking Robots.

Walking animals such as invertebrates can effectively perform self-organized and robust locomotion. They can also quickly adapt their gait to deal with injury or damage. Such a complex achievement is mainly performed via coordination between the legs, commonly known as interlimb coordination. Several components underlying the interlimb coordination process (like distributed neural control circuits, local sensory feedback, and body-environment interactions during movement) have been recently identified and applied to the control systems of walking robots. However, while the sensory pathways of biological systems are plastic and can be continuously readjusted (referred to as sensory adaptation), those implemented on robots are typically static. They first need to be manually adjusted or optimized offline to obtain stable locomotion. In this study, we introduce a fast learning mechanism for online sensory adaptation. It can continuously adjust the strength of sensory pathways, thereby introducing flexible plasticity into the connections between sensory feedback and neural control circuits. We combine the sensory adaptation mechanism with distributed neural control circuits to acquire the adaptive and robust interlimb coordination of walking robots. This novel approach is also general and flexible. It can automatically adapt to different walking robots and allow them to perform stable self-organized locomotion as well as quickly deal with damage within a few walking steps. The adaptation of plasticity after damage or injury is considered here as lesion-induced plasticity. We validated our adaptive interlimb coordination approach with continuous online sensory adaptation on simulated 4-, 6-, 8-, and 20-legged robots. This study not only proposes an adaptive neural control system for artificial walking systems but also offers a possibility of invertebrate nervous systems with flexible plasticity for locomotion and adaptation to injury.

The Circularity of the Embodied Mind

From an embodied and enactive point of view, the mind–body problem has been reformulated as the relation between the lived or subject body on the one hand and the physiological or object body on the other (“body–body problem”). The aim of the paper is to explore the concept of circularity as a means of explaining the relation between the phenomenology of lived experience and the dynamics of organism–environment interactions. This concept of circularity also seems suitable for connecting enactive accounts with ecological psychology. It will be developed in a threefold way:(1) As the circular structure of embodiment, which manifests itself (a) in the homeostatic cycles between the brain and body and (b) in the sensorimotor cycles between the brain, body, and environment. This includes the interdependence of an organism’s dispositions of sense-making and the affordances of the environment.(2) As the circular causality, which characterizes the relation between parts and whole within the living organism as well as within the organism–environment system.(3) As the circularity of process and structure in development and learning. Here, it will be argued that subjective experience constitutes a process of sense-making that implies (neuro-)physiological processes so as to form modified neuronal structures, which in turn enable altered future interactions.On this basis, embodied experience may ultimately be conceived as the integration of brain–body and body–environment interactions, which has a top-down, formative, or ordering effect on physiological processes. This will serve as an approach to a solution of the body–body problem.

Passive Morphological Adaptation for Obstacle Avoidance in a Self-Growing Robot Produced by Additive Manufacturing.

This article presents strategies for the passive path and morphological adaptation of a plant-inspired growing robot that can build its own body by an additive manufacturing process. By exploiting the soft state of the thermoplastic material used by the robot to build its structure, we analyzed the ability of the robot to change its direction of growth without the need for specific cognition and control processes. Obstacle avoidance is computed by the mechanics from the body–environment interaction. The robot can passively adapt its body to flat obstacles with an inclination of up to 50° with resulting reaction forces of up to ∼10 N. The robot also successfully performs penetration and body adaptation (with 30° obstacle inclination) in artificial soil and in a rough unstructured environment. This approach is founded on observing plant roots and how they move and passively adapt to obstacles in soil before they actively respond followed by cell division-based growth.

Exploring Behaviors of Caterpillar-Like Soft Robots with a Central Pattern Generator-Based Controller and Reinforcement Learning.

Due to their flexibility, soft-bodied robots can potentially achieve rich and various behaviors within a single body. However, to date, no methodology has effectively harnessed these robots to achieve such diverse desired functionalities. Controllers that accomplish only a limited range of behaviors in such robots have been handcrafted. Moreover, the behaviors of these robots should be determined through body–environment interactions because an appropriate behavior may not always be manifested even if the body dynamics are given. Therefore, we have proposed SenseCPG-PGPE, a method for automatically designing behaviors for caterpillar-like soft-bodied robots. This method optimizes mechanosensory feedback to a central pattern generator (CPG)-based controller, which controls actuators in a robot, using policy gradients with parameter-based exploration (PGPE). In this article, we deeply investigated this method. We found that PGPE can optimize a CPG-based controller for soft-bodied robots that exhibit viscoelasticity and large deformation, whereas other popular policy gradient methods, such as trust region policy optimization and proximal policy optimization, cannot. Scalability of the method was confirmed using simulation as well. Although SenseCPG-PGPE uses a CPG-based controller, it can achieve nonsteady motion such as climbing a step in a simulated robot. The approach also resulted in distinctive behaviors depending on different body–environment conditions. These results demonstrate that the proposed method enables soft robots to explore a variety of behaviors automatically.

State estimation in posterior parietal cortex: Distinct poles of environmental and bodily states

Posterior parietal cortex (PPC) has been implicated in sensory and motor processing, but its underlying organization is still debated. Sensory-based accounts suggest that PPC is mainly involved in attentional selection and multisensory integration, serving novelty detection and information seeking. Motor-specific accounts suggest a parietal subdivision into lower-dimensional, effector-specific subspaces for planning motor action. More recently, function-based interpretations have been put forward based on coordinated responses across multiple effectors evoked by circumscribed PPC regions. In this review, we posit that an overarching interpretation of PPC’s functional organization must integrate, rather than contrast, these various accounts of PPC. We propose that PPC’s main role is that of a state estimator that extends into two poles: a rostral, body-related pole that projects the environment onto the body and a caudal, environment-related pole that projects the body into an environment landscape. The combined topology interweaves perceptual, motor, and function-specific principles, and suggests that actions are specified by top-down guided optimization of body-environment interactions.

A Biomimetic Control Method Increases the Adaptability of a Humanoid Robot Acting in a Dynamic Environment.

One of the big challenges in robotics is to endow agents with autonomous and adaptive capabilities. With this purpose, we embedded a cerebellum-based control system into a humanoid robot that becomes capable of handling dynamical external and internal complexity. The cerebellum is the area of the brain that coordinates and predicts the body movements throughout the body-environment interactions. Different biologically plausible cerebellar models are available in literature and have been employed for motor learning and control of simplified objects. We built the canonical cerebellar microcircuit by combining machine learning and computational neuroscience techniques. The control system is composed of the adaptive cerebellar module and a classic control method; their combination allows a fast adaptive learning and robust control of the robotic movements when external disturbances appear. The control structure is built offline, but the dynamic parameters are learned during an online-phase training. The aforementioned adaptive control system has been tested in the Neuro-robotics Platform with the virtual humanoid robot iCub. In the experiment, the robot iCub has to balance with the hand a table with a ball running on it. In contrast with previous attempts of solving this task, the proposed neural controller resulted able to quickly adapt when the internal and external conditions change. Our bio-inspired and flexible control architecture can be applied to different robotic configurations without an excessive tuning of the parameters or customization. The cerebellum-based control system is indeed able to deal with changing dynamics and interactions with the environment. Important insights regarding the relationship between the bio-inspired control system functioning and the complexity of the task to be performed are obtained.

Simulating Soft-Bodied Swimmers with Particle-Based Physics.

In swimming virtual creatures, there is often a disparity between the level of detail in simulating a swimmer's body and that of the fluid it moves in. To address this disparity, we have developed a new approach to modeling swimming virtual creatures using pseudo-soft bodies and particle-based fluids, which has sufficient realism to investigate a larger range of body-environment interactions than are usually included. As this comes with increased computational costs, which may be severe, we have also developed a means of reducing the volume of fluid that must be simulated.