Self-organized adaptive legged locomotion in a compliant quadruped robot

In this contribution we present experiments of an adaptive locomotion controller on a compliant quadruped robot. The adaptive controller consists of adaptive frequency oscillators in different configurations and produces dynamic gaits such as bounding and jumping. We show two main results: (1)The adaptive controller is able to track the resonant frequency of the robot which is a function of different body parameters (2)controllers based on dynamical systems as we present are able to "recognize” mechanically intrinsic modes of locomotion, adapt to them and enforce them. More specifically the main results are supported by several experiments, showing first that the adaptive controller is constantly tracking body properties and readjusting to them. Second, that important gait parameters are dependent on the geometry and movement of the robot and the controller can account for that. Third, that local control is sufficient and the adaptive controller can adapt to the different mechanical modes. And finally, that key properties of the gaits are not only depending on properties of the body but also the actual mode of movement that the body is operating in. We show that even if we specify the gait pattern on the level of the CPG the chosen gait pattern does not necessarily correspond to the CPG's pattern. Furthermore, we present the analytical treatment of adaptive frequency oscillators in closed feedback loops, and compare the results to the data from the robot experiment

Adaptive Excitation Control for the Underactuated Biped Robot

AbstractA control method to make the chaotic gait converge to a stable cycle gait is proposed for the biped robot with knees. This control method is called adaptive excitation control. It is based on the principle of bionics and the principle of self-excited. The control law is a combination of sinusoidal input and sensory feedback control. The control torque is only inputted into the robot's hip. Therefore, the walking process is low energy consuming. Simulation results show that the control method proposed in this paper is effective. It can enlarge the basin of attraction of limit cycle and increase the gait stability

Physical and neural entrainment to rhythm: human sensorimotor coordination across tasks and effector systems.

The human sensorimotor system can be readily entrained to environmental rhythms, through multiple sensory modalities. In this review, we provide an overview of theories of timekeeping that make this neuroentrainment possible. First, we present recent evidence that contests the assumptions made in classic timekeeper models. The role of state estimation, sensory feedback and movement parameters on the organization of sensorimotor timing are discussed in the context of recent experiments that examined simultaneous timing and force control. This discussion is extended to the study of coordinated multi-effector movements and how they may be entrained

Sensorimotor postural control in healthy and pathological stance and gait

Postural control during standing and walking is an inherently unstable task requiring the interaction of various biomechanical, sensory, and neurophysiological mechanisms to shape stable patterns of whole-body coordination that are able to counteract postural disequilibrium. This thesis focused on the examination of central aspects of the functional roles of these mechanisms and the modes of interaction between them. A further aim was to determine the conditions of dynamic stability for healthy standing and walking performance as well as for certain balance and gait disorders. By studying movement fluctuations in the walking pattern it could be demonstrated that dynamic stability during walking depends on gait speed and is differentially regulated for the medio-lateral and the fore-aft walking planes. Stability control in the fore-aft walking plane exhibits attractor dynamics typical for a dynamical system. Accordingly, the most stable pattern of movement coordination in terms of minimal fluctuations in the order parameter (i.e., the relative phase between the two oscillating legs) can be observed at the attractor of self-paced walking. Critical fluctuations occur at increasingly non-preferred speeds, indicating a loss of dynamic gait stability close to the speed boundaries of the walking mode. Moreover, stability control during slow walking is critically dependent on sensory feedback control, whereas dynamic stability during fast walking relies mainly on the smooth operation of cerebellar pacemaker regions. Disturbances of sensory and cerebellar locomotor control in certain gait disorders could be further linked to a loss of dynamic gait stability, in particular an increased risk of falls. Furthermore, this thesis examined alterations in the sensorimotor postural control scheme that may trigger the experience of subjective imbalance and vertigo in the conditions of phobic postural vertigo and visual height intolerance. Both conditions are characterized by an inadequate mode of balance regulation featuring increased levels of open-loop balance control and a precipitate integration of closed-loop sensory feedback into the postural control scheme. This inadequate balance control strategy is accompanied by a stiffening of the anti-gravity musculature and is elicited by specific influences of attention and sensory feedback control. The findings of this thesis contribute to the understanding of central sensorimotor mechanisms involved in the control of dynamic postural stability during standing and walking. They further provide relevant information for the differential diagnosis and fall risk estimation of certain balance and gait disorders

On the Evolutionary Co-Adaptation of Morphology and Distributed Neural Controllers in Adaptive Agents

The attempt to evolve complete embodied and situated artificial creatures in which both morphological and control characteristics are adapted during the evolutionary process has been and still represents a long term goal key for the artificial life and the evolutionary robotics community. Loosely inspired by ancient biological organisms which are not provided with a central nervous system and by simple organisms such as stick insects, this thesis proposes a new genotype encoding which allows development and evolution of mor- phology and neural controller in artificial agents provided with a distributed neural network. In order to understand if this kind of network is appropriate for the evolution of non trivial behaviours in artificial agents, two experiments (description and results will be shown in chapter 3) in which evolution was applied only to the controller’s parameters were performed. The results obtained in the first experiment demonstrated how distributed neural networks can achieve a good level of organization by synchronizing the output of oscillatory elements exploiting acceleration/deceleration mechanisms based on local interactions. In the second experiment few variants on the topology of neural architecture were introduced. Results showed how this new control system was able to coordinate the legs of a simulated hexapod robot on two different gaits on the basis of the external circumstances. After this preliminary and successful investigation, a new genotype encoding able to develop and evolve artificial agents with no fixed morphology and with a distributed neural controller was proposed. A second set of experiments was thus performed and the results obtained confirmed both the effectiveness of genotype encoding and the ability of distributed neural network to perform the given task. The results have also shown the strength of genotype both in generating a wide range of different morphological structures and in favouring a direct co-adaptation between neural controller and morphology during the evolutionary process. Furthermore the simplicity of the proposed model has showed the effective role of specific elements in evolutionary experiments. In particular it has demonstrated the importance of the environment and its complexity in evolving non-trivial behaviours and also how adding an independent component to the fitness function could help the evolutionary process exploring a larger space solutions avoiding a premature convergence towards suboptimal solutions

An Analysis of the Relationship Between Complexity and Gait Adaptability

The presented sequence of studies considers theoretical applications from Complexity Science and Chaos Theory for gait time-series analysis. The main goal of this research is to build on insights from a previous body of knowledge, which have identified measures derived from Complexity Science and Chaos Theory as critical markers of gait control. Specifically, the studies presented in this dissertation attempt to directly test whether characterizing gait complexity relates to an ability to flexibly adjust gait. The broader impact of this research is utilizing measures of complexity to characterize gait control, and as a tool for rehabilitation which have both gained momentum in fall prevention research. Through a series of four studies, this dissertation was designed to test the theoretical viewpoint that complexity is related to gait control, particularly gait adaptability. Firstly, I sought to develop a paradigm for reliably entraining gait complexity with the use of several auditory fluctuating timing imperatives which, differed based on specified fractal characteristics. I also sought to quantify the duration of the retention of gait complexity, following entrainment. Thirdly, I assessed whether attentional demands required during entrainment were affected by the fractal characteristics of a fluctuating timing imperative. Lastly, I applied the developed paradigm to evaluate the theoretical relationship between gait complexity and stepping performance. The findings from this dissertation have developed a framework for assessing gait control. This series of projects has determined that a fluctuating timing imperative can reliably prescribe the gait pattern of healthy individuals towards a particular complexity. The use of a fluctuating timing imperative leads to entrainment of the stimulus complexity. Furthermore, once the timing imperative has ceased, there is a brief period of complexity retention in the walking pattern. This dissertation has also confirmed that entraining complexity to a fluctuating timing imperative does not alter the attentional demands associated with entrainment. However, entraining gait to fluctuating timing imperatives of different complexities alters the stepping strategy that is adopted. Lastly, this dissertation has shown that synchronizing gait to a fixed-interval stimulus following entrainment, depends on the complexities of the gait pattern

From locomotion to dance and back : exploring rhythmic sensorimotor synchronization

Le rythme est un aspect important du mouvement et de la perception de l’environnement. Lorsque l’on danse, la pulsation musicale induit une activité neurale oscillatoire qui permet au système nerveux d’anticiper les évènements musicaux à venir. Le système moteur peut alors s’y synchroniser. Cette thèse développe de nouvelles techniques d’investigation des rythmes neuraux non strictement périodiques, tels que ceux qui régulent le tempo naturellement variable de la marche ou la perception rythmes musicaux. Elle étudie des réponses neurales reflétant la discordance entre ce que le système nerveux anticipe et ce qu’il perçoit, et qui sont nécessaire pour adapter la synchronisation de mouvements à un environnement variable. Elle montre aussi comment l’activité neurale évoquée par un rythme musical complexe est renforcée par les mouvements qui y sont synchronisés. Enfin, elle s’intéresse à ces rythmes neuraux chez des patients ayant des troubles de la marche ou de la conscience.Rhythms are central in human behaviours spanning from locomotion to music performance. In dance, self-sustaining and dynamically adapting neural oscillations entrain to the regular auditory inputs that is the musical beat. This entrainment leads to anticipation of forthcoming sensory events, which in turn allows synchronization of movements to the perceived environment. This dissertation develops novel technical approaches to investigate neural rhythms that are not strictly periodic, such as naturally tempo-varying locomotion movements and rhythms of music. It studies neural responses reflecting the discordance between what the nervous system anticipates and the actual timing of events, and that are critical for synchronizing movements to a changing environment. It also shows how the neural activity elicited by a musical rhythm is shaped by how we move. Finally, it investigates such neural rhythms in patient with gait or consciousness disorders

Functional neuroimaging of the interference between working memory and the control of periodic ankle movement timing.

BACKGROUND: Limited information processing capacity in the brain necessitates task prioritisation and subsequent adaptive behavioural strategies for the dual-task coordination of locomotion with severe concurrent cognitive loading. Commonly observed strategies include prioritisation of gait at the cost of reduced performance in the cognitive task. Alternatively alterations of gait parameters such as gait velocity have been reported presumably to free processing capacity for the benefit of performance in the cognitive task. The aim of this study was to describe the neuroanatomical correlates of adaptive behavioural strategies in cognitive-motor dual-tasking when the competition for information processing capacity is severe and may exceed individuals' capacity limitations. METHODS: During an fMRI experiment, 12 young adults performed slow continuous, auditorily paced bilateral anti-phase ankle dorsi-plantarflexion movements as an element of normal gait at .5 Hz in single and dual task modes. The secondary task involved a visual, alphabetic N-back task with presentation rate jittered around .7 Hz. The N-back task, which randomly occurred in 0-back or 2-back form, was modified into a silent counting task to avoid confounding motor responses at the cost of slightly increasing the task's general coordinative complexity. Participants' ankle movements were recorded using an optoelectronic motion capture system to derive kinematic parameters representing the stability of the movement timing and synchronization. Participants were instructed to perform both tasks as accurately as possible. RESULTS: Increased processing complexity in the dual-task 2-back condition led to significant changes in movement parameters such as the average inter-response interval, the coefficient of variation of absolute asynchrony and the standard deviation of peak angular velocity. A regions-of-interest analysis indicated correlations between these parameters and local activations within the left inferior frontal gyrus (IFG) such that lower IFG activations coincided with performance decrements. CONCLUSIONS: Dual-task interference effects show that the production of periodically timed ankle movements, taken as modelling elements of the normal gait cycle, draws on higher-level cognitive resources involved in working memory. The interference effect predominantly concerns the timing accuracy of the ankle movements. Reduced activations within regions of the left IFG, and in some respect also within the superior parietal lobule, were identified as one factor affecting the timing of periodic ankle movements resulting in involuntary 'hastening' during severe dual-task working memory load. This 'hastening' phenomenon may be an expression of re-automated locomotor control when higher-order cognitive processing capacity can no longer be allocated to the movements due to the demands of the cognitive task. The results of our study also propose the left IFG as a target region to improve performance during dual-task walking by techniques for non-invasive brain stimulation

Review and classification of human gait training and rehabilitation devices

The number of people with reduced mobility capabilities increases every year. This reduction arises mainly due to spinal cord injuries; strokes which caused hemiparesis; or due to an advanced age. This decrease in mobility is a factor that influences both their quality of life and their dependence of others in daily life. Thus, it becomes necessary to find means and tools to prevent, compensate, improve or help to restore and increase the mobility of the affected people. The main expectation is that such means help to recover or ameliorate their independence in their daily life. Traditional training employs a treadmill with a support-weight system. This training is based on the principle of repetition of all the physical movements of a gait and has shown to produce good results in terms of rehabilitation of patients. However, this therapy requires two or more therapists in assisting patients during walking, to hold and adjust the patient’s lower limbs to correctly produce the desired gait. Thus, it requires a substantial commitment and effort of the therapists [1], and it is very expensive in terms of human resources. This leads to a boost on the population healthcare and assistive services demand and, thus an increase in the need for care givers. Assistive mobility robotic devices for gait training of disabled patients in treadmills and in the ground are one successful alternative. Other alternatives include devices that allow a broader training of patients, in different ground types, and the repetition of gait movements in uphill, downhill and trip. This paper reviews state of the art training gait devices focusing on passive and active devices. Passive devices rely on the principle of Gravity-Balancing in that they try to reduce or eliminate the effects of gravity during walking. Active devices are usually classified according to three different approaches: (i) treadmillexoskeleton based devices, (ii) robotic manipulators generating different types of gait patterns, and (iii) mobilite devices. In this review, several examples of current devices are presented

EEG During Pedaling: Brain Activity During a Locomotion-Like Task in Humans

This study characterized the brain electrical activity during pedaling, a locomotor-like task, in humans. We postulated that phasic brain activity would be associated with active pedaling, consistent with a cortical role in locomotor tasks. 64 channels of electroencephalogram (EEG) and 10 channels of electromyogram (EMG) data were recorded from 10 neurologically-intact volunteers while they performed active and passive (no effort) pedaling on a custom-designed stationary bicycle. Ensemble average waveforms, two dimensional topographic maps and amplitude of the beta (13-35 Hz) frequency band were analyzed and compared between active and passive trials. The absolute amplitude (peak positive-peak negative) of the EEG waveform recorded at the Cz electrode tended to be higher in the passive than the active trials (paired t-test; p\u3c0.01). Average power of the center beta-band frequency (20-25 Hz) in the active pedaling was significantly smaller than passive pedaling (Univariate ANOVA; p\u3c0.01), consistent with beta desynchronization. A significant negative correlation was observed between the ensemble average EEG waveform for active trials and the composite EMG (summated EMG from both limbs for each muscle) of the rectus femoris (r = -0.77, p\u3c0.01) the medial hamstrings (r = -0.85, p\u3c0.01) and the tibialis anterior (r = -0.70, p \u3c0.01) muscles. These results demonstrated that substantial sensorimotor processing occurs in the brain during pedaling in humans. Further, cortical activity seemed to be greatest during recruitment of the muscles critical for transitioning the legs from flexion to extension and vice versa. This is the first known study demonstrating the feasibility of EEG recording during pedaling, and owing to similarities between pedaling and bipedal walking, may provide valuable insight into brain activity during locomotion in humans