Adaptive, fast walking in a biped robot under neuronal control and learning

Human walking is a dynamic, partly self-stabilizing process relying on the interaction of the biomechanical design with its neuronal control. The coordination of this process is a very difficult problem, and it has been suggested that it involves a hierarchy of levels, where the lower ones, e.g., interactions between muscles and the spinal cord, are largely autonomous, and where higher level control (e.g., cortical) arises only pointwise, as needed. This requires an architecture of several nested, sensori–motor loops where the walking process provides feedback signals to the walker's sensory systems, which can be used to coordinate its movements. To complicate the situation, at a maximal walking speed of more than four leg-lengths per second, the cycle period available to coordinate all these loops is rather short. In this study we present a planar biped robot, which uses the design principle of nested loops to combine the self-stabilizing properties of its biomechanical design with several levels of neuronal control. Specifically, we show how to adapt control by including online learning mechanisms based on simulated synaptic plasticity. This robot can walk with a high speed (> 3.0 leg length/s), self-adapting to minor disturbances, and reacting in a robust way to abruptly induced gait changes. At the same time, it can learn walking on different terrains, requiring only few learning experiences. This study shows that the tight coupling of physical with neuronal control, guided by sensory feedback from the walking pattern itself, combined with synaptic learning may be a way forward to better understand and solve coordination problems in other complex motor tasks

In silico case studies of compliant robots: AMARSI deliverable 3.3

In the deliverable 3.2 we presented how the morphological computing ap- proach can significantly facilitate the control strategy in several scenarios, e.g. quadruped locomotion, bipedal locomotion and reaching. In particular, the Kitty experimental platform is an example of the use of morphological computation to allow quadruped locomotion. In this deliverable we continue with the simulation studies on the application of the different morphological computation strategies to control a robotic system

Biomechanics of foetal movement.

© 2015, AO Research Institute. All rights reserved.Foetal movements commence at seven weeks of gestation, with the foetal movement repertoire including twitches, whole body movements, stretches, isolated limb movements, breathing movements, head and neck movements, jaw movements (including yawning, sucking and swallowing) and hiccups by ten weeks of gestational age. There are two key biomechanical aspects to gross foetal movements; the first being that the foetus moves in a dynamically changing constrained physical environment in which the freedom to move becomes increasingly restricted with increasing foetal size and decreasing amniotic fluid. Therefore, the mechanical environment experienced by the foetus affects its ability to move freely. Secondly, the mechanical forces induced by foetal movements are crucial for normal skeletal development, as evidenced by a number of conditions and syndromes for which reduced or abnormal foetal movements are implicated, such as developmental dysplasia of the hip, arthrogryposis and foetal akinesia deformation sequence. This review examines both the biomechanical effects of the physical environment on foetal movements through discussion of intrauterine factors, such as space, foetal positioning and volume of amniotic fluid, and the biomechanical role of gross foetal movements in human skeletal development through investigation of the effects of abnormal movement on the bones and joints. This review also highlights computational simulations of foetal movements that attempt to determine the mechanical forces acting on the foetus as it moves. Finally, avenues for future research into foetal movement biomechanics are highlighted, which have potential impact for a diverse range of fields including foetal medicine, musculoskeletal disorders and tissue engineering

Incremental embodied chaotic exploration of self-organized motor behaviors with proprioceptor adaptation

This paper presents a general and fully dynamic embodied artificial neural system, which incrementally explores and learns motor behaviors through an integrated combination of chaotic search and reflex learning. The former uses adaptive bifurcation to exploit the intrinsic chaotic dynamics arising from neuro-body-environment interactions, while the latter is based around proprioceptor adaptation. The overall iterative search process formed from this combination is shown to have a close relationship to evolutionary methods. The architecture developed here allows realtime goal-directed exploration and learning of the possible motor patterns (e.g., for locomotion) of embodied systems of arbitrary morphology. Examples of its successful application to a simple biomechanical model, a simulated swimming robot, and a simulated quadruped robot are given. The tractability of the biomechanical systems allows detailed analysis of the overall dynamics of the search process. This analysis sheds light on the strong parallels with evolutionary search

Comfort-Centered Design of a Lightweight and Backdrivable Knee Exoskeleton

This paper presents design principles for comfort-centered wearable robots and their application in a lightweight and backdrivable knee exoskeleton. The mitigation of discomfort is treated as mechanical design and control issues and three solutions are proposed in this paper: 1) a new wearable structure optimizes the strap attachment configuration and suit layout to ameliorate excessive shear forces of conventional wearable structure design; 2) rolling knee joint and double-hinge mechanisms reduce the misalignment in the sagittal and frontal plane, without increasing the mechanical complexity and inertia, respectively; 3) a low impedance mechanical transmission reduces the reflected inertia and damping of the actuator to human, thus the exoskeleton is highly-backdrivable. Kinematic simulations demonstrate that misalignment between the robot joint and knee joint can be reduced by 74% at maximum knee flexion. In experiments, the exoskeleton in the unpowered mode exhibits 1.03 Nm root mean square (RMS) low resistive torque. The torque control experiments demonstrate 0.31 Nm RMS torque tracking error in three human subjects.Comment: 8 pages, 16figures, Journa

Ambulatory Assessment of Ankle and Foot Dynamics

Ground reaction force (GRF) measurement is important in the analysis of human body movements. The main drawback of the existing measurement systems is the restriction to a laboratory environment. This paper proposes an ambulatory system for assessing the dynamics of ankle and foot, which integrates the measurement of the GRF with the measurement of human body movement. The GRF and the center of pressure (CoP) are measured using two six-degrees-of-freedom force sensors mounted beneath the shoe. The movement of foot and lower leg is measured using three miniature inertial sensors, two rigidly attached to the shoe and one on the lower leg. The proposed system is validated using a force plate and an optical position measurement system as a reference. The results show good correspondence between both measurement systems, except for the ankle power estimation. The root mean square (RMS) difference of the magnitude of the GRF over 10 evaluated trials was (0.012 plusmn 0.001) N/N (mean plusmn standard deviation), being (1.1 plusmn 0.1)% of the maximal GRF magnitude. It should be noted that the forces, moments, and powers are normalized with respect to body weight. The CoP estimation using both methods shows good correspondence, as indicated by the RMS difference of (5.1 plusmn 0.7) mm, corresponding to (1.7 plusmn 0.3)% of the length of the shoe. The RMS difference between the magnitudes of the heel position estimates was calculated as (18 plusmn 6) mm, being (1.4 plusmn 0.5)% of the maximal magnitude. The ankle moment RMS difference was (0.004 plusmn 0.001) Nm/N, being (2.3 plusmn 0.5)% of the maximal magnitude. Finally, the RMS difference of the estimated power at the ankle was (0.02 plusmn 0.005) W/N, being (14 plusmn 5)% of the maximal power. This power difference is caused by an inaccurate estimation of the angular velocities using the optical reference measurement system, which is due to considering the foot as a single segment. The ambulatory system considers separat- - e heel and forefoot segments, thus allowing an additional foot moment and power to be estimated. Based on the results of this research, it is concluded that the combination of the instrumented shoe and inertial sensing is a promising tool for the assessment of the dynamics of foot and ankle in an ambulatory setting

A functional electrical stimulation system for human walking inspired by reflexive control principles

This study presents an innovative multichannel functional electrical stimulation gait-assist system which employs a well-established purely reflexive control algorithm, previously tested in a series of bipedal walking robots. In these robots, ground contact information was used to activate motors in the legs, generating a gait cycle similar to that of humans. Rather than developing a sophisticated closed-loop functional electrical stimulation control strategy for stepping, we have instead utilised our simple reflexive model where muscle activation is induced through transfer functions which translate sensory signals, predominantly ground contact information, into motor actions. The functionality of the functional electrical stimulation system was tested by analysis of the gait function of seven healthy volunteers during functional electrical stimulation–assisted treadmill walking compared to unassisted walking. The results demonstrated that the system was successful in synchronising muscle activation throughout the gait cycle and was able to promote functional hip and ankle movements. Overall, the study demonstrates the potential of human-inspired robotic systems in the design of assistive devices for bipedal walking

Biomechanical mechanisms underlying exosuit-induced improvements in walking economy after stroke

Stroke-induced hemiparetic gait is characteristically asymmetric and metabolically expensive. Weakness and impaired control of the paretic ankle contribute to reduced forward propulsion and ground clearance—walking subtasks critical for safe and efficient locomotion. Targeted gait interventions that improve paretic ankle function after stroke are therefore warranted. We have developed textile-based, soft wearable robots that transmit mechanical power generated by off-board or body-worn actuators to the paretic ankle using Bowden cables (soft exosuits) and have demonstrated the exosuits can overcome deficits in paretic limb forward propulsion and ground clearance, ultimately reducing the metabolic cost of hemiparetic walking. This study elucidates the biomechanical mechanisms underlying exosuit-induced reductions in metabolic power. We evaluated the relationships between exosuit-induced changes in the body center of mass (COM) power generated by each limb, individual joint powers, and metabolic power. Compared to walking with an exosuit unpowered, exosuit assistance produced more symmetrical COM power generation during the critical period of the step-to-step transition (22.4±6.4% more symmetric). Changes in individual limb COM power were related to changes in paretic (R2= 0.83, P= 0.004) and nonparetic (R2= 0.73, P= 0.014) ankle power. Interestingly, despite the exosuit providing direct assistance to only the paretic limb, changes in metabolic power were related to changes in nonparetic limb COM power (R2= 0.80, P= 0.007), not paretic limb COM power (P> 0.05). These findings provide a fundamental understanding of how individuals poststroke interact with an exosuit to reduce the metabolic cost of hemiparetic walking.Accepted manuscript2019-03-0