Dynamic Locomotion Research Articles

Reinforcement learning for versatile, dynamic, and robust bipedal locomotion control

Reinforcement learning for versatile, dynamic, and robust bipedal locomotion control

Determining the optimum number of cycles for calculating joint coordination and its variability during running at different speeds: A timeseries analysis

Understanding the intricacies of human movement coordination and variability during running is crucial to unraveling the dynamics of locomotion, identifying potential injury mechanisms and understanding skill development. Identification of minimum number of cycles for calculation of reliable coordination and its variability could help with better test organization and efficient assessment time. By adopting a cross-sectional study design, this study investigated the minimum required cycles for calculating hip-knee, hip-ankle and knee-ankle coordination and their variability using a continuous relative phase (CRP) method. Twenty-nine healthy adults ran on a treadmill at speeds of 9, 12.5, and 16 km.h−1 while 3D kinematic data of their lower limbs were recorded using 6 optoelectronic cameras. Using Intraclass Correlation Coefficient (ICC) analysis, reliability between CRP and its variability (CRPv) in different gait cycles (3, 5, 10, 20, 30) was assessed for each speed. A minimum of 10 cycles was required for CRP calculation across all speeds, whereas CRPv necessitated a minimum of 30 cycles for moderate to good reliability. While increasing the number of cycles improved ICC values for inter-joint CRP, the same trend was not consistently observed for CRPv, emphasizing the importance of separately assessing CRP and its variability metrics.

Spatiotemporal dynamics of locomotor decisions in Drosophila melanogaster.

Decision-making in animals often involves choosing actions while navigating the environment, a process markedly different from static decision paradigms commonly studied in laboratory settings. Even in decision-making assays in which animals can freely locomote, decision outcomes are often interpreted as happening at single points in space and single moments in time, a simplification that potentially glosses over important spatiotemporal dynamics. We investigated locomotor decision-making in Drosophila melanogaster in Y-shaped mazes, measuring the extent to which their future choices could be predicted through space and time. We demonstrate that turn-decisions can be reliably predicted from flies' locomotor dynamics, with distinct predictability phases emerging as flies progress through maze regions. We show that these predictability dynamics are not merely the result of maze geometry or wall-following tendencies, but instead reflect the capacity of flies to move in ways that depend on sustained locomotor signatures, suggesting an active, working memory-like process. Additionally, we demonstrate that fly mutants known to have sensory and information-processing deficits exhibit altered spatial predictability patterns, highlighting the role of visual, mechanosensory, and dopaminergic signaling in locomotor decision-making. Finally, highlighting the broad applicability of our analyses, we generalize our findings to other species and tasks. We show that human participants in a virtual Y-maze exhibited similar decision predictability dynamics as flies. This study advances our understanding of decision-making processes, emphasizing the importance of spatial and temporal dynamics of locomotor behavior in the lead-up to discrete choice outcomes.

A New Tightly-Coupled Dual-VIO for a Mobile Manipulator With Dynamic Locomotion

A New Tightly-Coupled Dual-VIO for a Mobile Manipulator With Dynamic Locomotion

Learning to Walk with Adaptive Feet

In recent years, tasks regarding autonomous mobility favoredthe use of legged robots rather than wheeled ones thanks to their higher mobility on rough and uneven terrains. This comes at the cost of more complex motion planners and controllers to ensure robot stability and balance. However, in the case of quadrupedal robots, balancing is simpler than it is for bipeds thanks to their larger support polygons. Until a few years ago, most scientists and engineers addressed the quadrupedal locomotion problem with model-based approaches, which require a great deal of modeling expertise. A new trend is the use of data-driven methods, which seem to be quite promising and have shown great results. These methods do not require any modeling effort, but they suffer from computational limitations dictated by the hardware resources used. However, only the design phase of these algorithms requires large computing resources (controller training); their execution in the operational phase (deployment), takes place in real time on common processors. Moreover, adaptive feet capable of sensing terrain profile information have been designed and have shown great performance. Still, no dynamic locomotion control method has been specifically designed to leverage the advantages and supplementary information provided by this type of adaptive feet. In this work, we investigate the use and evaluate the performance of different end-to-end control policies trained via reinforcement learning algorithms specifically designed and trained to work on quadrupedal robots equipped with passive adaptive feet for their dynamic locomotion control over a diverse set of terrains. We examine how the addition of the haptic perception of the terrain affects the locomotion performance.

Picotaur: A 15 mg Hexapedal Robot with Electrostatically Driven, 3D‐Printed Legs

Dynamic and agile locomotion in legged robots enables them to overcome obstacles and navigate complex and unstructured terrain. However, the leg mechanisms and actuators needed for versatile locomotion are much more challenging to manufacture and integrate in sub‐gram scale robots. Herein, Picotaur, a 15.4 mg hexapedal robot with legs that enable various locomotion tasks such as turning, climbing 3D‐printed stairs, and pushing loads for the first time at these size scales, is presented. 3D printing with two‐photon polymerization enables the manufacture of electrostatically driven 2 degrees of freedom legs on a robot body made from a flexible printed circuit board. Based on simple control inputs, Picotaur can achieve alternating tripod gaits, reaching speeds up to 57 mm (7.2 body lengths) per second, as well as pronking gaits to tackle a wider variety of terrain. This approach to manufacturing and controlling legged robots at smaller scales provides a path forward toward robots that can be used for practical applications ranging from inspection to exploration and rival the performance of insects at similar size scales.

Risk of migration: not all gregarious locust nymphs reach appropriate refuges.

Sedentary animals choose appropriate refuges against predators, while migratory ones may not necessarily do so. In ectotherms, refuge selection is critical during low temperatures, because they cannot actively evade predators. To understand how migratory ectotherms alter their defensive behaviors depending on refuge quality in cold temperatures, we evaluated migratory gregarious desert locust nymphs (Schistocerca gregaria) in the Sahara Desert, where daily thermal constraints occur. We recorded how roosting plant type (bush/shrub) and its height influenced two alternative defense behaviors (dropping/stationary) during cold mornings, in response to an approaching simulated ground predator. Most locusts in bushes dropped within the bush and hid irrespective of their height, whereas those roosting > 2 m height in shrubs remained stationary. These defenses are effective and match with refuge plant types because dynamic locomotion is not required. When nymphs roosted on shrubs < 1.5-m height, which was an unsafe position, nearly half showed both defensive behaviors, indicating that escaping decisions become ambiguous when the refuges are inappropriate. These results suggest that locusts display flexible defensive behaviors when finding appropriate refuges and selecting refuge before daily thermal limitations occur could be critical for migratory ectotherms, which is a risk associated with migration.

Dynamics of centipede locomotion revealed by large-scale traction force microscopy.

We present a novel approach to traction force microscopy (TFM) for studying the locomotion of 10 cm long walking centipedes on soft substrates. Leveraging the remarkable elasticity and ductility of kudzu starch gels, we use them as a deformable gel substrate, providing resilience against the centipedes' sharp leg tips. By optimizing fiducial marker size and density and fine-tuning imaging conditions, we enhance measurement accuracy. Our TFM investigation reveals traction forces along the centipede's longitudinal axis that effectively counterbalance inertial forces within the 0-10 mN range, providing the first report of non-vanishing inertia forces in TFM studies. Interestingly, we observe waves of forces propagating from the head to the tail of the centipede, corresponding to its locomotion speed. Furthermore, we discover a characteristic cycle of leg clusters engaging with the substrate: forward force (friction) upon leg tip contact, backward force (traction) as the leg pulls the substrate while stationary, and subsequent forward force as the leg tip detaches to reposition itself in the anterior direction. This work opens perspectives for TFM applications in ethology, tribology and robotics.

Impact of hindlimb length variation on jumping dynamics in the Longshanks mouse.

Distantly related mammals (e.g. jerboa, tarsiers, kangaroos) have convergently evolved elongated hindlimbs relative to body size. Limb elongation is hypothesized to make these species more effective jumpers by increasing their kinetic energy output (through greater forces or acceleration distances), thereby increasing take-off velocity and jump distance. This hypothesis, however, has rarely been tested at the population level, where natural selection operates. We examined the relationship between limb length, muscular traits and dynamics using Longshanks mice, which were selectively bred over 22 generations for longer tibiae. Longshanks mice have approximately 15% longer tibiae and 10% longer femora compared with random-bred Control mice from the same genetic background. We collected in vivo measures of locomotor kinematics and force production, in combination with behavioral data and muscle morphology, to examine how changes in bone and muscle structure observed in Longshanks mice affect their hindlimb dynamics during jumping and clambering. Longshanks mice achieved higher mean and maximum lunge-jump heights than Control mice. When jumping to a standardized height (14 cm), Longshanks mice had lower maximum ground reaction forces, prolonged contact times and greater impulses, without significant differences in average force, power or whole-body velocity. While Longshanks mice have longer plantarflexor muscle bodies and tendons than Control mice, there were no consistent differences in muscular cross-sectional area or overall muscle volume; improved lunge-jumping performance in Longshanks mice is not accomplished by simply possessing larger muscles. Independent of other morphological or behavioral changes, our results point to the benefit of longer hindlimbs for performing dynamic locomotion.

POSTURAL CONTROL IMPAIRED IN MYOARTHROKINETIC AND NEURO-SENSORY DISORDERS

Interdependent subsystems involved in dynamic posture and locomotion are represented by osteoarticular, neuromuscular, sensory systems. Postural control is maintained by somato-sensory, visual vestibular feedback, integrated at the level of the locomotor system and the central nervous system. Postural stability is disturbed in mio-arthro-kinetic disorders. In proprioceptive loss, the automatic postural responses are diminished in amplitude and delayed in time; stretch reflexes in soleus and medial gastrocnemius are severely diminished; balance-correcting responses in tibialis anterior are diminished and delayed; backward motion of the trunk is reduced; movement strategies and synergies are disturbed. In peripheral vestibular loss, there are increased trunk responses to disruptive stimuli, with hypermetric trunk muscle responses and hypometric knee responses, but unchanged synergies; pathological changes to the modulation depth are produced; the amplitude of balance correcting responses in ankle muscles is severely reduced. Visual input serves to decrease the stiffness of the musculoskeletal system; it can be accomplished by decreasing the level of muscular activity across the joints of the lower limbs (in eyes-open subjects) or by reducing the gains of the other postural feedback mechanisms, the proprioceptive or vestibular systems (in eyes-closed subjects). Keywords: postural control, proprioceptive insufficiency, vestibular impairment.

Robotics goes PRISMA

Abstract In this article, we review the main results achieved by the research activities carried out at PRISMA Lab of the University of Naples Federico II where, for 35 years, an interdisciplinary team of experts developed robots that are ultimately useful to humans. We summarize the key contributions made in the last decade in the six research areas of dynamic manipulation and locomotion, aerial robotics, human-robot interaction, artificial intelligence and cognitive robotics, industrial robotics, and medical robotics. After a brief overview of each research field, the most significant methodologies and results are reported and discussed, highlighting their cross-disciplinary and translational aspects. Finally, the potential future research directions identified are discussed.

Cascade Antidisturbance Control of Hydraulically Driven Bipedal Robots for High Dynamic Locomotion by Using Model Prediction and Task Hierarchical Optimization

Cascade Antidisturbance Control of Hydraulically Driven Bipedal Robots for High Dynamic Locomotion by Using Model Prediction and Task Hierarchical Optimization

Selective-collective scalable locomotion control of helical magnetic swimmers within confined channels using global magnetic fields

Achieving selective-individual and collective control over multiple magnetic microrobots remains a formidable challenge. Existing techniques for controlling identical magnetic swimmers are often limited to two-dimensional, small working spaces, while heterogeneous swimmers can only be controlled in small numbers without the option for collective control. In this study, we present a purely magnetic control methodology for the selective-scalable locomotion of helical magnetic swimmers within confined channels. By employing a unique gradient field distribution, referred to as the "selection field," along with space-uniform rotating fields, we establish a "selection volume" that allows swimmers within it to fully rotate, while those outside remain stationary. We explore various conditions of the selection volume to analyze the locomotion dynamics of the swimmers in relation to the position of the selection volume. Experimental results demonstrate the selective-scalable locomotion of identical robots, ranging from one to an arbitrary number (N) of robots, as well as their selective-individual manipulation for multitasking applications. Furthermore, compatibility of the proposed method with different magnetic torque-driven robots is exemplified through the selective control of rolling robots. Moreover, three-dimensional selective-scalable control is also demonstrated for four swimmers in a quasi-three-dimensional channel, as well as for two swimmers within a true three-dimensional channel.

Gait Factor on the Energy Harvesting for a Simple Biped Robot

To design walk-fast and energy-efficient robots, there has been lots of work in the last decade examining the locomotion dynamics of a passive biped. As the walking environment or system parameter changes, an energy use efficient robot may become inefficient. A possible approach to increase the energy efficiency is through the ability to harvest the energy used during the locomotion. The paper’s main goal is to investigate the relations between walking speed, the locomotion energy consumption of a passive biped, and the ability to retrieve the lost energy as locomotion energy efficiency varies. Piezoelectric bimorphs were attached to the feet of the biped to harvest energy via exploiting the acceleration excitations induced vibrations at the instant foot lift and heel strike. It is found that as a foot-to-hip mass ratio increases, the stable periodic-1 (P1) walking gait becomes slower and more energy costing. Also it means more available energy to harvest, although the retrieved energy is much smaller compared to the locomotive energy. Once the foot-to-hip mass ratio passes the periodic doubling (PD) point, P1 walking gaits will become limped P2 walking gaits, and the high energy cost situation alleviates, which also means less available energy to harvest. On the other hand, if the foot-to-hip mass ratio is fixed and the slope angle increases, the walking will experience sequences of PD bifurcations, and the walking gaits go through P1, P2, P4, P8, and chaotic walking. As the walking gaits change, the average walking efficiency, average locomotion energy consumption, and average harvested energy grow as the slope becomes deeper.

Planning and Execution of Dynamic Whole-body Locomotion for a Wheeled Biped Robot on Uneven Terrain

Planning and Execution of Dynamic Whole-body Locomotion for a Wheeled Biped Robot on Uneven Terrain

Sidewinder-Inspired Self-Adjusting, Lateral-Rolling Soft Robots for Autonomous Terrain Exploration.

Helical structures of liquid crystal elastomers (LCEs) hold promise in soft robotics for self-regulated rolling motions. The understanding of their motion paths and potentials for terrain exploration remains limited. This study introduces a self-adjusting, lateral-rolling soft robot inspired by sidewinder snakes. The spring-like LCE helical filaments (HFs) autonomously respond to thermal cues, demonstrating dynamic and sustainable locomotion with adaptive rolling along non-linear paths. By fine-tuning the diameter, pitch, and modulus of the LCE HFs, and the environmental temperature, the movements of the LCE HFs, allowing for exploration of diverse terrains over a 600cm2 area within a few minutes, can be programmed. LCE HFs are showcased to navigate through over nine obstacles, including maze escaping, terrain exploration, target hunting, and successfully surmounting staircases through adaptable rolling.

Mapping the neural dynamics of locomotion across the Drosophila brain

Locomotion engages widely distributed networks of neurons. However, our understanding of the spatial architecture and temporal dynamics of the networks that underpin walking remains incomplete. We use volumetric two-photon imaging to map neural activity associated with walking across the entire brain of Drosophila. We define spatially clustered neural signals selectively associated with changes in either forward or angular velocity, demonstrating that neurons with similar behavioral selectivity are clustered. These signals reveal distinct topographic maps in diverse brain regions involved in navigation, memory, sensory processing, and motor control, as well as regions not previously linked to locomotion. We identify temporal trajectories of neural activity that sweep across these maps, including signals that anticipate future movement, representing the sequential engagement of clusters with different behavioral specificities. Finally, we register these maps to a connectome and identify neural networks that we propose underlie the observed signals, setting a foundation for subsequent circuit dissection. Overall, our work suggests a spatiotemporal framework for the emergence and execution of complex walking maneuvers and links this brain-wide neural activity to single neurons and local circuits.

Determination of breeding criteria for gait proficiency in leisure riding and racing dromedary camels: a stepwise multivariate analysis of factors predicting overall biomechanical performance.

To date, the biomechanical dynamics in camelids have not been addressed, although it might be a factor that can affect selection and breeding in this species. Therefore, the aim of this article is to conduct curve fitting and discriminant canonical analysis to identify the mathematical function that best captures the dynamics of camel locomotion and to study the impact of kinematic, morphometric, physiological, and phaneroptic variables on gait performance in leisure riding and racing activities in dromedaries, respectively. The cubic function emerged as the most suitable mathematical model to represent the locomotive behavior of camels. Various factors were found to play a pivotal role in the athletic performance of leisure riding and racing dromedary camels. Concretely, angular measurements at the distal fore and rear extremity areas, pelvis inclination, relative volume of the hump, impact forces of the front limbs, post-neutering effects, and the kinematic behavior of the scapula, shoulder, carpus, hip, and foot are the factors that greatly impact gait performance in leisure riding and racing camels. The biomechanical performance at these specific body regions has a profound impact on weight absorption and minimization of mechanic impact during camel locomotion, static/dynamic balance, force distribution, energy of propulsion, movement direction and amplitude, and storage of elastic strain in leisure riding and racing dromedaries. In contrast, other animal- and environment-dependent factors do not exert significant influence on camel gait performance, which can be attributed to species-specific, inherited adaptations developed in response to desert conditions, including the pacing gait, broad foot pads, and energy-efficient movements. The outcomes of our functional data analysis can provide valuable insights for making informed breeding decisions aimed at enhancing animal functional performance in camel riding and racing activities. Furthermore, these findings can open avenues for exploring alternative applications, such as camel-assisted therapy.

Nezha‐IV: A hybrid aerial underwater vehicle in real ocean environments

AbstractHybrid aerial underwater vehicles (HAUVs) that are capable of autonomously operating in both the aerial and underwater environments with repeated rapid transitions have received great interest in recent years. Current HAUV prototypes cannot fully cope with the unstructured, harsh, and hazardous ocean environments considering the high‐pressure and the strong hydrodynamic perturbations. This work reports on the HAUV, Nezha‐IV, with all basic functions validated in a real ocean environment. Nezha‐IV has four aerial propellers and eight underwater thrusters. It is not only capable of maneuvering delicately during flight and underwater but can also perform dynamic transitions under rough sea conditions. We present the design, construction, control, and oceanic testing of Nezha‐IV and demonstrate reliability and robustness, especially during the transition phases. Performance estimation and results gathered from tests in the South China Sea show that Nezha‐IV can operate at various depths ranging from 0 to 50 m at a velocity of 1 kt for 22 min and hover in the air for 15 min or cruise at a velocity of 10 m/s for 7.2 km in 12 min. This project contributes to the field of HAUV with (i) a HAUV capable of dynamic locomotion with high stability in both media and during transitions; (ii) identification of challenges during water–air transition in harsh sea conditions, and a reliable transition strategy that helps the development of fully autonomous HAUVs; (iii) a modular, foldable, and impact‐resistant HAUV structure; (iv) vehicle's capability proved by extensive tests in dynamic ocean environment.

An Energy-Based Framework for Robust Dynamic Bipedal Walking Over Compliant Terrain

Abstract Bipedal locomotion over compliant terrain is an important and largely underexplored problem in the robotics community. Although robot walking has been achieved on some non-rigid surfaces with existing control methodologies, there is a need for a systematic framework applicable to different bipeds that enables stable locomotion over various compliant terrains. In this work, a novel energy-based framework is proposed that allows the dynamic locomotion of bipeds across a wide range of compliant surfaces. The proposed framework utilizes an extended version of the 3D Dual Spring-Loaded Inverted Pendulum (Dual-SLIP) model that supports compliant terrains, while a bioinspired controller is employed to regulate expected perturbations of extremely low ground-stiffness levels. An energy-based methodology is introduced for tuning the bioinspired controller to enable dynamic walking with robustness to a wide range of low ground-stiffness one-step perturbations. The proposed system and controller are shown to mimic the vertical Ground Reaction Force (GRF) responses observed in human walking over compliant terrains. Moreover, they succeed in handling repeated unilateral stiffness perturbations under specific conditions. This work can advance the field of biped locomotion by providing a biomimetic method for generating stable human-like walking trajectories for bipedal robots over various compliant surfaces. Furthermore, the concepts of the proposed framework could be incorporated into the design of controllers for lower-limb prostheses with adjustable stiffness to improve their robustness over compliant surfaces.