Adaptive load feedback robustly signals force dynamics in robotic model of Carausius morosus stepping

Animals utilize a number of neuronal systems to produce locomotion. One type of sensory organ that contributes in insects is the campaniform sensillum (CS) that measures the load on their legs. Groups of the receptors are found on high stress regions of the leg exoskeleton and they have significant effects in adapting walking behavior. Recording from these sensors in freely moving animals is limited by technical constraints. To better understand the load feedback signaled by CS to the nervous system, we have constructed a dynamically scaled robotic model of the Carausius morosus stick insect middle leg. The leg steps on a treadmill and supports weight during stance to simulate body weight. Strain gauges were mounted in the same positions and orientations as four key CS groups (Groups 3, 4, 6B, and 6A). Continuous data from the strain gauges were processed through a previously published dynamic computational model of CS discharge. Our experiments suggest that under different stepping conditions (e.g., changing “body” weight, phasic load stimuli, slipping foot), the CS sensory discharge robustly signals increases in force, such as at the beginning of stance, and decreases in force, such as at the end of stance or when the foot slips. Such signals would be crucial for an insect or robot to maintain intra- and inter-leg coordination while walking over extreme terrain

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

Evaluation of force feedback in walking using joint torques as naturalistic stimuli

Control of adaptive walking requires the integration of sensory signals of muscle force and load. We have studied how mechanoreceptors (tibial campaniform sensilla) encode naturalistic stimuli derived from joint torques of stick insects walking on a horizontal substrate. Previous studies showed that forces applied to the legs using the mean torque profiles of a proximal joint were highly effective in eliciting motor activities. However, substantial variations in torque direction and magnitude occurred at the more distal femorotibial joint, which can generate braking or propulsive forces and provide lateral stability. To determine how these forces are encoded, we used torque waveforms of individual steps that had maximum values in stance in the directions of flexion or extension. Analysis of kinematic data showed that the torques in different directions tended to occur in different ranges of joint angles. Variations within stance were not accompanied by comparable changes in joint angle but often reflected vertical ground reaction forces and leg support of body load. Application of torque waveforms elicited sensory discharges with variations in firing frequency similar to those seen in freely walking insects. All sensilla directionally encoded the dynamics of force increases and showed hysteresis to transient force decreases. Smaller receptors exhibited more tonic firing. Our findings suggest that dynamic sensitivity in force feedback can modulate ongoing muscle activities to stabilize distal joints when large forces are generated at proximal joints. Furthermore, use of naturalistic stimuli can reproduce characteristics seen in freely moving animals that are absent in conventional restrained preparations. NEW & NOTEWORTHY Sensory encoding of forces during walking by campaniform sensilla was characterized in stick insects using waveforms of joint torques calculated by inverse dynamics as mechanical stimuli. Tests using the mean joint torque and torques of individual steps showed the system is highly sensitive to force dynamics (dF/dt). Use of naturalistic stimuli can reproduce characteristics of sensory discharges seen in freely walking insects, such as load transfer among legs

A perspective on the neuromorphic control of legged locomotion in past, present, and future insect-like robots

This article is a historical perspective on how the study of the neuromechanics of insects and other arthropods has inspired the construction, and especially the control, of hexapod robots. Many hexapod robots’ control systems share common features, including: 1. Direction of motor output of each joint (i.e. to flex or extend) in the leg is gated by an oscillatory or bistable gating mechanism; 2. The relative phasing between each joint is influenced by proprioceptive feedback from the periphery (e.g. joint angles, leg load) or central connections between joint controllers; and 3. Behavior can be directed (e.g. transition from walking along a straight path to walking along a curve) via low-dimensional, broadly-acting descending inputs to the network. These distributed control schemes are inspired by, and in some robots, closely mimic the organization of the nervous systems of insects, the natural hexapods, as well as crustaceans. Nearly a century of research has revealed organizational principles such as central pattern generators, the role of proprioceptive feedback in control, and command neurons. These concepts have inspired the control systems of hexapod robots in the past, in which these structures were applied to robot controllers with neuromorphic (i.e. distributed) organization, but not neuromorphic computational units (i.e. neurons) or computational hardware (i.e. hardware-accelerated neurons). Presently, several hexapod robots are controlled with neuromorphic computational units with or without neuromorphic organization, almost always without neuromorphic hardware. In the near future, we expect to see hexapod robots whose controllers include neuromorphic organization, computational units, and hardware. Such robots may exhibit the full mobility of their insect counterparts thanks to a ‘biology-first’ approach to controller design. This perspective article is not a comprehensive review of the neuroscientific literature but is meant to give those with engineering backgrounds a gentle introduction into the neuroscientific principles that underlie models and inspire neuromorphic robot controllers. A historical summary of hexapod robots whose control systems and behaviors use neuromorphic elements is provided. Robots whose controllers closely model animals and may be used to generate concrete hypotheses for future animal experiments are of particular interest to the authors. The authors hope that by highlighting the decades of experimental research that has led to today’s accepted organization principles of arthropod nervous systems, engineers may better understand these systems and more fully apply biological details in their robots. To assist the interested reader, deeper reviews of particular topics from biology are suggested throughout

Raw Data for Correlation Between Ranges of Leg Walking Angles and Passive Rest Angles Among Leg Types in Stick Insects

Three types of data files were uploaded to the repository: 1) The raw data in the form of movie stills of walking animals and photos of denervated animals; 2) The measured walking ThF angles and the measured resting-state ThF angles extracted from the movie stills and photos in 1), in the form of .txt files; and 3) Instructions for accessing specific data (Instructions to repository data_Guschlbauer et al. 2022.pdf)

Correlation between ranges of leg walking angles and passive rest angles among leg types in stick insects

Because of scaling issues, passive muscle and joint forces become increasingly important as limb size decreases.(1-3) In some small limbs, passive forces can drive swing in locomotion,(4,5) and antagonist passive torques help control limb swing velocity.(6) In stance, minimizing antagonist muscle and joint passive forces could save energy. These considerations predict that, for small limbs, evolution would result in the angle range over which passive forces are too small to cause limb movement (called resting-state range in prior insect work(4) and area of neutral equilibrium in physics and engineering) correlating with the limb's typical working range, usually that in locomotion. We measured the most protracted and retracted thorax-femur (ThF) angles of the pro- (front), meso- (middle), and metathoracic (hind) leg during stick insect (Carausius morosus) walks. This ThF working range differed in the three leg types, being more posterior in more posterior legs. In other experiments, we manually protracted or retracted the denervated front, middle, and hind legs. Upon release, passive forces moved the leg in the opposite direction (retraction or protraction) until it reached the most protracted or most retracted edge of the ThF resting-state range. The ThF resting-state angle ranges correlated with the leg-type working range, being more posterior in more posterior legs. The most protracted ThF walking angles were more retracted than the post-protraction ThF angles, and the most retracted ThF walking angles were similar to the postretraction ThF angles. These correlations of ThF working- and resting-state ranges could simplify motor control and save energy. These data also provide an example of evolution altering behavior by changing passive muscle and joint properties.(7