Climbing favours the tripod gait over alternative faster insect gaits

Interleg coordination in free-walking bug Erthesina fullo (Hemiptera: Pentatomidae)

Insects can adapt their walking patterns to complex and varied environments and retain the ability to walk even after significant changes in their physical attributes, such as amputation. Although the interleg coordination of intact insects has been widely described in previous studies, the adaptive walking patterns in free-walking insects with amputation of 1 or more legs are still unclear. The pentatomid bug Erthesina fullo exhibits a tripod gait, when walking freely on horizontal substrates, like many other insects. In this study, amputations were performed on this species to investigate changes in interleg coordination. The walking parameters were analyzed, such as the locations of touchdown and liftoff, cycle period, walking speed, and head displacement of intact and amputated insects. The results show that E. fullo displays adaptive interleg coordination in response to amputations. With 1 amputated leg, bugs changed to a 3-unit gait, whereas with 2 amputated legs they employed a wave gait. These data are helpful in exploring the motion mode control in walking insects and provide the theoretical basis for the gait control strategy of robots, when leg failure occurs.

Sensorimotor delays constrain robust locomotion in a 3D kinematic model of fly walking

Walking animals must maintain stability in the presence of external perturbations, despite significant temporal delays in neural signaling and muscle actuation. Here, we develop a 3D kinematic model with a layered control architecture to investigate how sensorimotor delays constrain robustness of walking behavior in the fruit fly, Drosophila. Motivated by the anatomical architecture of insect locomotor control circuits, our model consists of three component layers: a neural network that generates realistic 3D joint kinematics for each leg, an optimal controller that executes the joint kinematics while accounting for delays, and an inter-leg coordinator. The model generates realistic simulated walking that matches real fly walking kinematics and sustains walking even when subjected to unexpected perturbations, generalizing beyond its training data. However, we found that the model's robustness to perturbations deteriorates when sensorimotor delay parameters exceed the physiological range. These results suggest that fly sensorimotor control circuits operate close to the temporal limit at which they can detect and respond to external perturbations. More broadly, we show how a modular, layered model architecture can be used to investigate physiological constraints on animal behavior.

Experimental study and geometrical method to design bio-inspired robotic kinematic chains of inching-locomotion caterpillars

Inching-locomotion caterpillars (ILAR) show impressive environmental adaptation, having high dexterity and flexibility. To design robots that mimic these abilities, a novel bioinspired robotic design (BIROD) method is presented. The method is composed by an algorithm for geometrical kinematic analysis (GEKINS) to standardize the proportional dimensions according to the insect's anatomy and obtain the kinematic chains. The approach is experimentally applied to analyze the locomotion and kinematic chain of these specimens:Geometridae-two pair of prolegs (represents 35 000 species) andPlusiinae-three pair of prolegs (represents 400 species). The obtained data indicate that the application of the proposed method permits to locate the attachment mechanisms, joints, links, and to calculate angular displacement, angular average velocity, number of degrees of freedom, and thus the kinematic chain.Geometridaein contrast toPlusiinae, shows a longer walk-stride length, a lower number of single-rotational joints in 2D (3 DOF versus 4 DOF), and a lower number of dual-rotational joints in 3D (6 DOF versus 8 DOF). The application of BIROD and GEKINS provides the forward kinematics for 35 400 ILAR species and are expected to be useful as a preliminary phase for the design of bio-inspired arthropod robots.

The Characteristics, Distribution, Function, and Origin of Alternative Lateral Horse Gaits

This article traces the characteristics, origin, distribution, and function of alternative lateral horse gaits, i.e., intermediate speed lateral-sequence gaits. Such alternative lateral gaits (running walk, rack, broken pace, hard pace, and broken trot) are prized by equestrians today for their comfort and have been found in select horse breeds for hundreds of years and even exhibited in fossil equid trackways. After exploring the evolution and development of alternative lateral gaits via fossil equid trackways, human art, and historical writings, the functional and genetic factors that led to the genesis of these gaits are discussed. Such gaited breeds were particularly favored and spread by the Scythians, Celts, Turks, and Spaniards. Fast and low-swinging hard pacing gaits are common in several horse breeds of mountainous areas of East and North Asia; high-stepping rack and running walk gaits are often displayed in European and North and South American breeds; the broken pace is found in breeds of Central Asia, Southeast Asia, West Asia, Western North America, and Brazil in South America; and the broken trot occurs in breeds of North Asia, South Asia, the Southern United States, and Brazil in South America, inhabiting desert or marshy areas.

The neuromechanics of animal locomotion: From biology to robotics and back

Robotics and neuroscience are sister disciplines that both aim to understand how agile, efficient, and robust locomotion can be achieved in autonomous agents. Robotics has already benefitted from neuromechanical principles discovered by investigating animals. These include the use of high-level commands to control low-level central pattern generator-like controllers, which, in turn, are informed by sensory feedback. Reciprocally, neuroscience has benefited from tools and intuitions in robotics to reveal how embodiment, physical interactions with the environment, and sensory feedback help sculpt animal behavior. We illustrate and discuss exemplar studies of this dialog between robotics and neuroscience. We also reveal how the increasing biorealism of simulations and robots is driving these two disciplines together, forging an integrative science of autonomous behavioral control with many exciting future opportunities.

Flexible locomotion in complex environments: the influence of species, speed and sensory feedback on panarthropod inter-leg coordination

Panarthropods (a clade containing arthropods, tardigrades and onychophorans) can adeptly move across a wide range of challenging terrains and their ability to do so given their relatively simple nervous systems makes them compelling study organisms. Studies of forward walking on flat terrain excitingly point to key features in inter-leg coordination patterns that seem to be 'universally' shared across panarthropods. However, when movement through more complex, naturalistic terrain is considered, variability in coordination patterns - from the intra-individual to inter-species level - becomes more apparent. This variability is likely to be due to the interplay between sensory feedback and local pattern-generating activity, and depends crucially on species, walking speed and behavioral goal. Here, I gather data from the literature of panarthropod walking coordination on both flat ground and across more complex terrain. This Review aims to emphasize the value of: (1) designing experiments with an eye towards studying organisms in natural environments; (2) thoughtfully integrating results from various experimental techniques, such as neurophysiological and biomechanical studies; and (3) ensuring that data is collected and made available from a wider range of species for future comparative analyses.

How the conception of control influences our understanding of actions

Wilful movement requires neural control. Commonly, neural computations are thought to generate motor commands that bring the musculoskeletal system - that is, the plant - from its current physical state into a desired physical state. The current state can be estimated from past motor commands and from sensory information. Modelling movement on the basis of this concept of plant control strives to explain behaviour by identifying the computational principles for control signals that can reproduce the observed features of movements. From an alternative perspective, movements emerge in a dynamically coupled agent-environment system from the pursuit of subjective perceptual goals. Modelling movement on the basis of this concept of perceptual control aims to identify the controlled percepts and their coupling rules that can give rise to the observed characteristics of behaviour. In this Perspective, we discuss a broad spectrum of approaches to modelling human motor control and their notions of control signals, internal models, handling of sensory feedback delays and learning. We focus on the influence that the plant control and the perceptual control perspective may have on decisions when modelling empirical data, which may in turn shape our understanding of actions.

Control and study of bio-inspired quadrupedal gaits on an underactuated miniature robot

This paper presents a linear quadratic Gaussian (LQG) controller for controlling the gait of a miniature, foldable quadruped robot with individually actuated and controlled legs (MinIAQ-III). The controller is implemented on a palm-size robot made by folding an acetate sheet. MinIAQ-III has four DC motors for actuation and four rotary sensors for feedback. It is one of the few untethered robots on a miniature scale capable of working with different gaits with the help of its individually-actuated legs and the developed controller. The presented LQG controller controls each leg's positions and rotational speeds by measuring the positions and estimating the rotational speeds, respectively. With the precise gait control on the robot, we demonstrate different gaits inspired by quadrupeds in nature and compare the simulation and experiment results for some of the gaits. An extensive simulation environment developed for robot dynamics helps us to predict the locomotion behavior of the robot in various environments. The match between the simulation and the experiment results shows that the proposed LQG controller can successfully control the miniature robot's gaits. We also conduct a case study that shows the potential to use the simulation to achieve different robot behavior. In a case study, we present our robot performing a prancing similar to horses. We use the simulation environment to find the required motor configuration phases and physical parameters, which can make our robot prance. After finding the parameters in simulation, we replicate the configuration in our robot and observe the robot making the same moves as the simulation.

Microscopic robots with onboard digital control

Autonomous robots-systems where mechanical actuators are guided through a series of states by information processing units to perform a predesigned function-are expected to revolutionize everything from health care to transportation. Microscopic robots are poised for a similar revolution in fields from medicine to environmental remediation. A key hurdle to developing these microscopic robots is the integration of information systems, particularly electronics fabricated at commercial foundries, with microactuators. Here, we develop such an integration process and build microscopic robots controlled by onboard complementary metal oxide semiconductor electronics. The resulting autonomous, untethered robots are 100 to 250 micrometers in size, are powered by light, and walk at speeds greater than 10 micrometers per second. In addition, we demonstrate a microscopic robot that can respond to an optical command. This work paves the way for ubiquitous autonomous microscopic robots that perform complex functions, respond to their environments, and communicate with the outside world.

Design, Analysis and Experiments of Hexapod Robot with Six-Link Legs for High Dynamic Locomotion

An important feature of a legged robot is its dynamic motion performance. Traditional methods often improve the dynamic motion performance by reducing the moment of inertia of robot legs or by adopting quasi-direct drive actuators. This paper proposes a method to enhance the dynamic performance of a legged robot by transmission mechanism. Specifically, we present a unique six-link leg mechanism that can implement a large output motion using a small drive motion. This unique feature can enhance the robots' dynamic motion capability. Experiments with a hexapod robot verified the effectiveness of the mechanism. The experimental results showed that, when the steering gear of the robot rotates 1°, the toe can lift 7 mm (5% of body height), and the maximum running speed of the robot can reach 390 mm/s (130% of the moveable body length per second).

Motor dysfunction in Drosophila melanogaster as a biomarker for developmental neurotoxicity

Adequate alternatives to conventional animal testing are needed to study developmental neurotoxicity (DNT). Here, we used kinematic analysis to assess DNT of known (toluene (TOL) and chlorpyrifos (CPS)) and putative (β-N-methylamino-L-alanine (BMAA)) neurotoxic compounds. Drosophila melanogaster was exposed to these compounds during development and evaluated for survival and adult kinematic parameters using the FlyWalker system, a kinematics evaluation method. At concentrations that do not induce general toxicity, the solvent DMSO had a significant effect on kinematic parameters. Moreover, while TOL did not significantly induce lethality or kinematic dysfunction, CPS not only induced developmental lethality but also significantly impaired coordination in comparison to DMSO. Interestingly, BMAA, which was not lethal during development, induced motor decay in young adult animals, phenotypically resembling aged flies, an effect later attenuated upon aging. Furthermore, BMAA induced abnormal development of leg motor neuron projections. Our results suggest that our kinematic approach can assess potential DNT of chemical compounds.

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Alternatives to mammalian testing are needed to detect developmental neurotoxicity

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The pesticide chlorpyrifos causes partial lethality and motor dysfunction

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Non-lethal levels of BMAA induce motor dysfunction in a dose-dependent manner

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Kinematic profiling of adult Drosophila can identify developmental neurotoxicity

Insect-inspired AI for autonomous robots

Autonomous robots are expected to perform a wide range of sophisticated tasks in complex, unknown environments. However, available onboard computing capabilities and algorithms represent a considerable obstacle to reaching higher levels of autonomy, especially as robots get smaller and the end of Moore's law approaches. Here, we argue that inspiration from insect intelligence is a promising alternative to classic methods in robotics for the artificial intelligence (AI) needed for the autonomy of small, mobile robots. The advantage of insect intelligence stems from its resource efficiency (or parsimony) especially in terms of power and mass. First, we discuss the main aspects of insect intelligence underlying this parsimony: embodiment, sensory-motor coordination, and swarming. Then, we take stock of where insect-inspired AI stands as an alternative to other approaches to important robotic tasks such as navigation and identify open challenges on the road to its more widespread adoption. Last, we reflect on the types of processors that are suitable for implementing insect-inspired AI, from more traditional ones such as microcontrollers and field-programmable gate arrays to unconventional neuromorphic processors. We argue that even for neuromorphic processors, one should not simply apply existing AI algorithms but exploit insights from natural insect intelligence to get maximally efficient AI for robot autonomy.

Sideways crab-walking is faster and more efficient than forward walking for a hexapod robot

Articulated legs enable the selection of robot gaits, including walking in different directions such as forward or sideways. For longer distances, the best gaits might maximize velocity or minimize the cost of transport (COT). While animals often have morphology suited to walking either forward (like insects) or sideways (like crabs), hexapod robots often default to forward walking. In this paper, we compare forward walking with crab-like sideways walking. To do this, a simple gait design method is introduced for determining forward and sideways gaits with equivalent body heights and step heights. Specifically, the frequency and stride lengths are tuned within reasonable constraints to find gaits that represent a robot's performance potential in terms of speed and energy cost. Experiments are performed in both dynamic simulation in Webots and a laboratory environment with our 18 degree-of-freedom hexapod robot, Sebastian. With the common three joint leg design, the results show that sideways walking is overall better (75% greater walking speed and 40% lower COT). The performance of sideways walking was better on both hard floors and granular media (dry play sand). This supports development of future crab-like walking robots for future applications. In future work, this approach may be used to develop nominal gaits without extensive optimization, and to explore whether the advantages of sideways walking persist for other hexapod designs.

NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster

Animal behavior emerges from an interaction between neural network dynamics, musculoskeletal properties and the physical environment. Accessing and understanding the interplay between these elements requires the development of integrative and morphologically realistic neuromechanical simulations. Here we present NeuroMechFly, a data-driven model of the widely studied organism, Drosophila melanogaster. NeuroMechFly combines four independent computational modules: a physics-based simulation environment, a biomechanical exoskeleton, muscle models and neural network controllers. To enable use cases, we first define the minimum degrees of freedom of the leg from real three-dimensional kinematic measurements during walking and grooming. Then, we show how, by replaying these behaviors in the simulator, one can predict otherwise unmeasured torques and contact forces. Finally, we leverage NeuroMechFly's full neuromechanical capacity to discover neural networks and muscle parameters that drive locomotor gaits optimized for speed and stability. Thus, NeuroMechFly can increase our understanding of how behaviors emerge from interactions between complex neuromechanical systems and their physical surroundings.

Kinematic Modeling at the Ant Scale: Propagation of Model Parameter Uncertainties

Quadrupeds and hexapods are known by their ability to adapt their locomotive patterns to their functions in the environment. Computational modeling of animal movement can help to better understand the emergence of locomotive patterns and their body dynamics. Although considerable progress has been made in this subject in recent years, the strengths and limitations of kinematic simulations at the scale of small moving animals are not well understood. In response to this, this work evaluated the effects of modeling uncertainties on kinematic simulations at small scale. In order to do so, a multibody model of a Messor barbarus ant was developed. The model was built from 3D scans coming from X-ray micro-computed tomography. Joint geometrical parameters were estimated from the articular surfaces of the exoskeleton. Kinematic data of a free walking ant was acquired using high-speed synchronized video cameras. Spatial coordinates of 49 virtual markers were used to run inverse kinematics simulations using the OpenSim software. The sensitivity of the model’s predictions to joint geometrical parameters and marker position uncertainties was evaluated by means of two Monte Carlo simulations. The developed model was four times more sensitive to perturbations on marker position than those of the joint geometrical parameters. These results are of interest for locomotion studies of small quadrupeds, octopods, and other multi-legged animals.

Motorized Treadmill and Optical Recording System for Gait Analysis of Grasshoppers

(1) Background: Insects, which serve as model systems for many disciplines with their unique advantages, have not been extensively studied in gait research because of the lack of appropriate tools and insect models to properly study the insect gaits. (2) Methods: In this study, we present a gait analysis of grasshoppers with a closed-loop custom-designed motorized insect treadmill with an optical recording system for quantitative gait analysis. We used the eastern lubber grasshopper, a flightless and large-bodied species, as our insect model. Gait kinematics were recorded and analyzed by making three grasshoppers walk on the treadmill with various speeds from 0.1 to 1.5 m/s. (3) Results: Stance duty factor was measured as 70–95% and decreased as walking speed increased. As the walking speed increased, the number of contact legs decreased, and diagonal arrangement of contact was observed at walking speed of 1.1 cm/s. (4) Conclusions: This pilot study of gait analysis of grasshoppers using the custom-designed motorized insect treadmill with the optical recording system demonstrates the feasibility of quantitative, repeatable, and real-time insect gait analysis.

Comparative analysis of a geometric and an adhesive righting strategy against toppling in inclined hexapedal locomotion

Animals are known to exhibit different walking behaviors in hilly habitats. For instance, cats, rats, squirrels, tree frogs, desert iguana, stick insects and desert ants were observed to lower their body height when traversing slopes, whereas mound-dwelling iguanas and wood ants tend to maintain constant walking kinematics regardless of the slope. This paper aims to understand and classify these distinct behaviors into two different strategies against toppling for climbing animals by looking into two factors: (i) the torque of the center of gravity (CoG) with respect to the critical tipping axis, and (ii) the torque of the legs, which has the potential to counterbalance the CoG torque. Our comparative locomotion analysis on level locomotion and inclined locomotion exhibited that primarily only one of the proposed two strategies was chosen for each of our sample species, despite the fact that a combined strategy could have reduced the animal's risk of toppling over even more. We found that Cataglyphis desert ants (species Cataglyphis fortis) maintained their upright posture primarily through the adjustment of their CoG torque (geometric strategy), and Formica wood ants (species Formica rufa), controlled their posture primarily by exerting leg torques (adhesive strategy). We further provide hints that the geometric strategy employed by Cataglyphis could increase the risk of slipping on slopes as the leg-impulse substrate angle of Cataglyphis hindlegs was lower than that of Formica hindlegs. In contrast, the adhesion strategy employed by Formica front legs not only decreased the risk of toppling but also explained the steeper leg-impulse substrate angle of Formica hindlegs which should relate to more bending of the tarsal structures and therefore to more microscopic contact points, potentially reducing the risk of hindleg slipping.

Descending and Ascending Signals That Maintain Rhythmic Walking Pattern in Crickets

The cricket is one of the model animals used to investigate the neuronal mechanisms underlying adaptive locomotion. An intact cricket walks mostly with a tripod gait, similar to other insects. The motor control center of the leg movements is located in the thoracic ganglia. In this study, we investigated the walking gait patterns of the crickets whose ventral nerve cords were surgically cut to gain an understanding of how the descending signals from the head ganglia and ascending signals from the abdominal nervous system into the thoracic ganglia mediate the initiation and coordination of the walking gait pattern. Crickets whose paired connectives between the brain and subesophageal ganglion (SEG) (circumesophageal connectives) were cut exhibited a tripod gait pattern. However, when one side of the circumesophageal connectives was cut, the crickets continued to turn in the opposite direction to the connective cut. Crickets whose paired connectives between the SEG and prothoracic ganglion were cut did not walk, whereas the crickets exhibited an ordinal tripod gait pattern when one side of the connectives was intact. Crickets whose paired connectives between the metathoracic ganglion and abdominal ganglia were cut initiated walking, although the gait was not a coordinated tripod pattern, whereas the crickets exhibited a tripod gait when one side of the connectives was intact. These results suggest that the brain plays an inhibitory role in initiating leg movements and that both the descending signals from the head ganglia and the ascending signals from the abdominal nervous system are important in initiating and coordinating insect walking gait patterns.

Adaptive Locomotion Control of a Hexapod Robot via Bio-Inspired Learning

In this paper, an adaptive locomotion control approach for a hexapod robot is proposed. Inspired from biological neuro control systems, a 3D two-layer artificial center pattern generator (CPG) network is adopted to generate the locomotion of the robot. The first layer of the CPG is responsible for generating several basic locomotion patterns and the functional configuration of this layer is determined through kinematics analysis. The second layer of the CPG controls the limb behavior of the robot to adapt to environment change in a specific locomotion pattern. To enable the adaptability of the limb behavior controller, a reinforcement learning (RL)-based approach is employed to tune the CPG parameters. Owing to symmetrical structure of the robot, only two parameters need to be learned iteratively. Thus, the proposed approach can be used in practice. Finally, both simulations and experiments are conducted to verify the effectiveness of the proposed control approach.

Form, Structure, and Function: How Plants vs. Animals Solve Physical Problems

Plants and animals have evolved solutions for a wide range of mechanical problems, such as adhesion and dispersal. Several of these solutions have been sources for bio-inspiration, like the Lotus Effect for self-cleaning surfaces or Velcro for adhesion. This symposium brought together plant and animal biomechanics researchers who tackle similar problems in different systems under the unifying theme of structure-function relations with relevance to bio-inspiration. For both communities it holds true that the structural systems, which have evolved in the respective organisms to address the mechanical challenges mentioned above, are often highly complex. This requires interdisciplinary research involving "classical" experimental biology approaches in combination with advanced imaging methods and computational modeling. The transfer of such systems into biomimetic technical materials and structures comes with even more challenges, like scalability issues and applicability. Having brought all these topics under one umbrella, this symposium presented the forefront of biophysical basic and application-oriented international research with the goal of facilitation knowledge transfer across systems and disciplines.

Tuning movement for sensing in an uncertain world

While animals track or search for targets, sensory organs make small unexplained movements on top of the primary task-related motions. While multiple theories for these movements exist-in that they support infotaxis, gain adaptation, spectral whitening, and high-pass filtering-predicted trajectories show poor fit to measured trajectories. We propose a new theory for these movements called energy-constrained proportional betting, where the probability of moving to a location is proportional to an expectation of how informative it will be balanced against the movement's predicted energetic cost. Trajectories generated in this way show good agreement with measured trajectories of fish tracking an object using electrosense, a mammal and an insect localizing an odor source, and a moth tracking a flower using vision. Our theory unifies the metabolic cost of motion with information theory. It predicts sense organ movements in animals and can prescribe sensor motion for robots to enhance performance.

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.

Behavioral and environmental contributions to drosophilid social networks

Animals interact with each other in species-specific reproducible patterns. These patterns of organization are captured by social network analysis, and social interaction networks (SINs) have been described for a wide variety of species including fish, insects, birds, and mammals. The aim of this study is to understand the evolution of social organization in Drosophila Using a comparative ecological, phylogenetic, and behavioral approach, the different properties of SINs formed by 20 drosophilids were compared. We investigate whether drosophilid network structures arise from common ancestry, a response to the species' past climate, other social behaviors, or a combination of these factors. This study shows that differences in past climate predicted the species' current SIN properties. The drosophilid phylogeny offered no value to predicting species' differences in SINs through phylogenetic signal tests. This suggests that group-level social behaviors in drosophilid species are shaped by divergent climates. However, we find that the social distance at which flies interact correlated with the drosophilid phylogeny, indicating that behavioral elements of SINs have remained largely unchanged in their evolutionary history. We find a significant correlation of leg length to social distance, outlining the interdependence of anatomy and complex social structures. Although SINs display a complex evolutionary relationship across drosophilids, this study suggests that the ecology, and not common ancestry, contributes to diversity in social structure in Drosophila.

Resource-efficient bio-inspired visual processing on the hexapod walking robot HECTOR

Emulating the highly resource-efficient processing of visual motion information in the brain of flying insects, a bio-inspired controller for collision avoidance and navigation was implemented on a novel, integrated System-on-Chip-based hardware module. The hardware module is used to control visually-guided navigation behavior of the stick insect-like hexapod robot HECTOR. By leveraging highly parallelized bio-inspired algorithms to extract nearness information from visual motion in dynamically reconfigurable logic, HECTOR is able to navigate to predefined goal positions without colliding with obstacles. The system drastically outperforms CPU- and graphics card-based implementations in terms of speed and resource efficiency, making it suitable to be also placed on fast moving robots, such as flying drones.

Walking kinematics in the polymorphic seed harvester ant Messor barbarus: influence of body size and load carriage

Ants are famous in the animal kingdom for their amazing load-carrying performance. Yet, the mechanisms that allow these insects to maintain their stability when carrying heavy loads have been poorly investigated. Here, we present a study of the kinematics of unloaded and loaded locomotion in the polymorphic seed-harvesting ant Messor barbarus In this species, large ants have larger heads relative to their size than small ants. Hence, their center of mass is shifted forward, and even more so when they are carrying a load in their mandibles. We tested the hypothesis that this could lead to large ants being less statically stable than small ants, thus explaining their lower load-carrying ability. We found that large ants were indeed less statically stable than small ants when walking unloaded, but they were nonetheless able to adjust their stepping pattern to partly compensate for this instability. When ants were walking loaded on the other hand, there was no evidence of different locomotor behaviors in individuals of different sizes. Loaded ants, whatever their size, move too slowly to maintain their balance through dynamic stability. Rather, they seem to do so by clinging to the ground with their hind legs during part of a stride. We show through a straightforward model that allometric relationships have a minor role in explaining the differences in load-carrying ability between large ants and small ants, and that a simple scale effect is sufficient to explain these differences.

Three-Legged Locomotion and the Constraints on Limb Number: Why Tripeds Don't Have a Leg to Stand On

Three-legged animals do not exist today and such an animal is not found in the fossil record. Which constraints operate to result in the lack of a triped phenotype? Consideration of animal locomotion and robotic studies suggests that physical constraints would not prevent a triped from being functional or advantageous. As is reviewed here, the strongest constraint on the evolution of a triped is phylogenetic: namely, the early genetic adoption of a bilaterally symmetrical body plan occurring before the advent of limbs. Presumably, this would greatly constrain any three-legged animal from ever evolving. Tripedalism is employed only by a few animals, but many use a tripod stance while engaged in a variety of activities. Because terms are often used interchangeably in the literature, a standardization of locomotion terminology is proposed. Understanding the constraints behind "forbidden" phenotypes forces us to confront gaps in our evolutionary understanding of which we may be unaware.

Robotic investigation on effect of stretch reflex and crossed inhibitory response on bipedal hopping

To maintain balance during dynamic locomotion, the effects of proprioceptive sensory feedback control (e.g. reflexive control) should not be ignored because of its simple sensation and fast reaction time. Scientists have identified the pathways of reflexes; however, it is difficult to investigate their effects during locomotion because locomotion is controlled by a complex neural system and current technology does not allow us to change the control pathways in living humans. To understand these effects, we construct a musculoskeletal bipedal robot, which has similar body structure and dynamics to those of a human. By conducting experiments on this robot, we investigate the effects of reflexes (stretch reflex and crossed inhibitory response) on posture during hopping, a simple and representative bouncing gait with complex dynamics. Through over 300 hopping trials, we confirm that both the stretch reflex and crossed response can contribute to reducing the lateral inclination during hopping. These reflexive pathways do not use any prior knowledge of the dynamic information of the body such as its inclination. Beyond improving the understanding of the human neural system, this study provides roboticists with biomimetic ideas for robot locomotion control.

Inverted and vertical climbing of a quadrupedal microrobot using electroadhesion

The ability to climb greatly increases the reachable workspace of terrestrial robots, improving their utility for inspection and exploration tasks. This is particularly desirable for small (millimeter-scale) legged robots operating in confined environments. This paper presents a 1.48-gram and 4.5-centimeter-long tethered quadrupedal microrobot, the Harvard Ambulatory MicroRobot with Electroadhesion (HAMR-E). The design of HAMR-E enables precise leg motions and voltage-controlled electroadhesion for repeatable and reliable climbing of inverted and vertical surfaces. The innovations that enable this behavior are an integrated leg structure with electroadhesive pads and passive alignment ankles and a parametric tripedal crawling gait. At a relatively low adhesion voltage of 250 volts, HAMR-E achieves speeds up to 1.2 (4.6) millimeters per second and can ambulate for a maximum of 215 (162) steps during vertical (inverted) locomotion. Furthermore, HAMR-E still retains the ability for high-speed locomotion at 140 millimeters per second on horizontal surfaces. As a demonstration of its potential for industrial applications, such as in situ inspection of high-value assets, we show that HAMR-E is capable of achieving open-loop, inverted locomotion inside a curved portion of a commercial jet engine.

Static stability predicts the continuum of interleg coordination patterns in Drosophila

During walking, insects must coordinate the movements of their six legs for efficient locomotion. This interleg coordination is speed dependent: fast walking in insects is associated with tripod coordination patterns, whereas slow walking is associated with more variable, tetrapod-like patterns. To date, however, there has been no comprehensive explanation as to why these speed-dependent shifts in interleg coordination should occur in insects. Tripod coordination would be sufficient at low walking speeds. The fact that insects use a different interleg coordination pattern at lower speeds suggests that it is more optimal or advantageous at these speeds. Furthermore, previous studies focused on discrete tripod and tetrapod coordination patterns. Experimental data, however, suggest that changes observed in interleg coordination are part of a speed-dependent spectrum. Here, we explore these issues in relation to static stability as an important aspect for interleg coordination in Drosophila We created a model that uses basic experimentally measured parameters in fruit flies to find the interleg phase relationships that maximize stability for a given walking speed. The model predicted a continuum of interleg coordination patterns spanning the complete range of walking speeds as well as an anteriorly directed swing phase progression. Furthermore, for low walking speeds, the model predicted tetrapod-like patterns to be most stable, whereas at high walking speeds, tripod coordination emerged as most optimal. Finally, we validated the basic assumption of a continuum of interleg coordination patterns in a large set of experimental data from walking fruit flies and compared these data with the model-based predictions.

Force dynamics and synergist muscle activation in stick insects: the effects of using joint torques as mechanical stimuli

Many sensory systems are tuned to specific parameters of behaviors and have effects that are task-specific. We have studied how force feedback contributes to activation of synergist muscles in serially homologous legs of stick insects. Forces were applied using conventional half-sine or ramp and hold functions. We also utilized waveforms of joint torques calculated from experiments in freely walking animals. In all legs, forces applied to either the tarsus (foot) or proximal leg segment (trochanter) activated synergist muscles that generate substrate grip and support, but coupling of the depressor muscle to tarsal forces was weak in the front legs. Activation of trochanteral receptors using ramp and hold functions generated positive feedback to the depressor muscle in all legs when animals were induced to seek substrate grip. However, discharges of the synergist flexor muscle showed adaptation at moderate force levels. In contrast, application of forces using torque waveforms, which do not have a static hold phase, produced sustained discharges in muscle synergies with little adaptation. Firing frequencies reflected the magnitude of ground reaction forces, were graded to changes in force amplitude, and could also be modulated by transient force perturbations added to the waveforms. Comparison of synergist activation by torques and ramp and hold functions revealed a strong influence of force dynamics (dF/d t). These studies support the idea that force receptors can act to tune muscle synergies synchronously to the range of force magnitudes and dynamics that occur in each leg according to their specific use in behavior. NEW & NOTEWORTHY The effects of force receptors (campaniform sensilla) on leg muscles and synergies were characterized in stick insects using both ramp and hold functions and waveforms of joint torques calculated by inverse dynamics. Motor responses were sustained and showed reduced adaptation to the more "natural" and nonlinear torque stimuli. Calculation of the first derivative (dF/d t) of the torque waveforms demonstrated that this difference was correlated with the dynamic sensitivities of the system.

Robotics-inspired biology

For centuries, designers and engineers have looked to biology for inspiration. Biologically inspired robots are just one example of the application of knowledge of the natural world to engineering problems. However, recent work by biologists and interdisciplinary teams have flipped this approach, using robots and physical models to set the course for experiments on biological systems and to generate new hypotheses for biological research. We call this approach robotics-inspired biology; it involves performing experiments on robotic systems aimed at the discovery of new biological phenomena or generation of new hypotheses about how organisms function that can then be tested on living organisms. This new and exciting direction has emerged from the extensive use of physical models by biologists and is already making significant advances in the areas of biomechanics, locomotion, neuromechanics and sensorimotor control. Here, we provide an introduction and overview of robotics-inspired biology, describe two case studies and suggest several directions for the future of this exciting new research area.

Honeybees Prefer to Steer on a Smooth Wall With Tetrapod Gaits

Insects are well equipped in walking on complex three-dimensional terrain, allowing them to overcome obstacles or catch prey. However, the gait transition for insects steering on a wall remains unexplored. Here, we find that honeybees adopted a tetrapod gait to change direction when climbing a wall. On the contrary to the common tripod gait, honeybees propel their body forward by synchronously stepping with both middle legs and then both front legs. This process ensures the angle of the central axis of the honeybee to be consistent with the crawling direction. Interestingly, when running in an alternating tripod gait, the central axis of honeybee sways around the center of mass under alternating tripod gait to maintain stability. Experimental results show that tripod, tetrapod, and random gaits result in the amazing consensus harmony on the climbing speed and gait stability, whether climbing on a smooth wall or walking on smooth ground.

Honeybees Prefer to Steer on a Smooth Wall With Tetrapod Gaits

Insects are well equipped in walking on complex three-dimensional terrain, allowing them to overcome obstacles or catch prey. However, the gait transition for insects steering on a wall remains unexplored. Here, we find that honeybees adopted a tetrapod gait to change direction when climbing a wall. On the contrary to the common tripod gait, honeybees propel their body forward by synchronously stepping with both middle legs and then both front legs. This process ensures the angle of the central axis of the honeybee to be consistent with the crawling direction. Interestingly, when running in an alternating tripod gait, the central axis of honeybee sways around the center of mass under alternating tripod gait to maintain stability. Experimental results show that tripod, tetrapod, and random gaits result in the amazing consensus harmony on the climbing speed and gait stability, whether climbing on a smooth wall or walking on smooth ground.

A Synthetic Nervous System Controls a Simulated Cockroach

The purpose of this work is to better understand how animals control locomotion. This knowledge can then be applied to neuromechanical design to produce more capable and adaptable robot locomotion. To test hypotheses about animal motor control, we model animals and their nervous systems with dynamical simulations, which we call synthetic nervous systems (SNS). However, one major challenge is picking parameter values that produce the intended dynamics. This paper presents a design process that solves this problem without the need for global optimization. We test this method by selecting parameter values for SimRoach2, a dynamical model of a cockroach. Each leg joint is actuated by an antagonistic pair of Hill muscles. A distributed SNS was designed based on pathways known to exist in insects, as well as hypothetical pathways that produced insect-like motion. Each joint’s controller was designed to function as a proportional-integral (PI) feedback loop and tuned with numerical optimization. Once tuned, SimRoach2 walks through a simulated environment, with several cockroach-like features. A model with such reliable low-level performance is necessary to investigate more sophisticated locomotion patterns in the future.

A Minimal Model Describing Hexapedal Interlimb Coordination: The Tegotae-Based Approach

Insects exhibit adaptive and versatile locomotion despite their minimal neural computing. Such locomotor patterns are generated via coordination between leg movements, i.e., an interlimb coordination, which is largely controlled in a distributed manner by neural circuits located in thoracic ganglia. However, the mechanism responsible for the interlimb coordination still remains elusive. Understanding this mechanism will help us to elucidate the fundamental control principle of animals' agile locomotion and to realize robots with legs that are truly adaptive and could not be developed solely by conventional control theories. This study aims at providing a “minimal" model of the interlimb coordination mechanism underlying hexapedal locomotion, in the hope that a single control principle could satisfactorily reproduce various aspects of insect locomotion. To this end, we introduce a novel concept we named “Tegotae,” a Japanese concept describing the extent to which a perceived reaction matches an expectation. By using the Tegotae-based approach, we show that a surprisingly systematic design of local sensory feedback mechanisms essential for the interlimb coordination can be realized. We also use a hexapod robot we developed to show that our mathematical model of the interlimb coordination mechanism satisfactorily reproduces various insects' gait patterns.