Chaotic exploration and learning of locomotion behaviours

We present a general and fully dynamic neural system, which exploits intrinsic chaotic dynamics, for the real-time goal-directed exploration and learning of the possible locomotion patterns of an articulated robot of an arbitrary morphology in an unknown environment. The controller is modeled as a network of neural oscillators that are initially coupled only through physical embodiment, and goal-directed exploration of coordinated motor patterns is achieved by chaotic search using adaptive bifurcation. The phase space of the indirectly coupled neural-body-environment system contains multiple transient or permanent self-organized dynamics, each of which is a candidate for a locomotion behavior. The adaptive bifurcation enables the system orbit to wander through various phase-coordinated states, using its intrinsic chaotic dynamics as a driving force, and stabilizes on to one of the states matching the given goal criteria. In order to improve the sustainability of useful transient patterns, sensory homeostasis has been introduced, which results in an increased diversity of motor outputs, thus achieving multiscale exploration. A rhythmic pattern discovered by this process is memorized and sustained by changing the wiring between initially disconnected oscillators using an adaptive synchronization method. Our results show that the novel neurorobotic system is able to create and learn multiple locomotion behaviors for a wide range of body configurations and physical environments and can readapt in realtime after sustaining damage

Stability analysis and control for bipedal locomotion using energy methods

In this thesis, we investigate the stability of limit cycles of passive dynamic walking. The formation process of the limit cycles is approached from the view of energy interaction. We introduce for the first time the notion of the energy portrait analysis originated from the phase portrait. The energy plane is spanned by the total energy of the system and its derivative, and different energy trajectories represent the energy portrait in the plane. One of the advantages of this method is that the stability of the limit cycles can be easily shown in a 2D plane regardless of the dimension of the system. The energy portrait of passive dynamic walking reveals that the limit cycles are formed by the interaction between energy loss and energy gain during each cycle, and they are equal at equilibria in the energy plane. In addition, the energy portrait is exploited to examine the existence of semi-passive limit cycles generated using the energy supply only at the take-off phase. It is shown that the energy interaction at the ground contact compensates for the energy supply, which makes the total energy invariant yielding limit cycles. This result means that new limit cycles can be generated according to the energy supply without changing the ground slope, and level ground walking, whose energy gain at the contact phase is always zero, can be achieved without actuation during the swing phase. We design multiple switching controllers by virtue of this property to increase the basin of attraction. Multiple limit cycles are linearized using the Poincare map method, and the feedback gains are computed taking into account the robustness and actuator saturation. Once a trajectory diverges from a basin of attraction, we switch the current controller to one that includes the trajectory in its basin of attraction. Numerical simulations confirm that a set of limit cycles can be used to increase the basin of attraction further by switching the controllers one after another. To enhance our knowledge of the limit cycles, we performed sophisticated simulations and found all stable and unstable limit cycles from the various ground slopes not only for the symmetric legs but also for the unequal legs that cause gait asymmetries. As a result, we present a novel classification of the passive limit cycles showing six distinct groups that are consecutive and cyclical

Countermeasure Development for Lumbopelvic Deconditioning in Space

Physical inactivity and lumbopelvic deconditioning have been linked to increased incidence of non-specific low back pain (LBP) and spinal injury in those who are exposed to microgravity (e.g. astronauts and individuals on long-duration bed rest) and in the general population. Astronauts have an increased risk of experiencing moderate to severe LBP during microgravity exposure and herniated intervertebral discs within 1 year following spaceflight. Atrophy and reduced motor control of the lumbar multifidus (LM) and transversus abdominis (TrA) muscles resulting from periods of deconditioning are linked to non-specific LBP and spinal injury risk in both post-flight astronauts and general populations. However, voluntary recruitment of these two key muscles is difficult and presents a rehabilitation challenge. This chapter reviews the concept of spinal stability as it relates to microgravity, discusses how existing exercise countermeasures used in space do not successfully maintain lumbopelvic muscle size, and introduces the functional readaptive exercise device (FRED) that shows potential to activate the LM and TrA muscles automatically and in a tonic fashion, which has relevance to rehabilitation of both astronaut and terrestrial populations

Review of Anthropomorphic Head Stabilisation and Verticality Estimation in Robots

International audienceIn many walking, running, flying, and swimming animals, including mammals, reptiles, and birds, the vestibular system plays a central role for verticality estimation and is often associated with a head sta-bilisation (in rotation) behaviour. Head stabilisation, in turn, subserves gaze stabilisation, postural control, visual-vestibular information fusion and spatial awareness via the active establishment of a quasi-inertial frame of reference. Head stabilisation helps animals to cope with the computational consequences of angular movements that complicate the reliable estimation of the vertical direction. We suggest that this strategy could also benefit free-moving robotic systems, such as locomoting humanoid robots, which are typically equipped with inertial measurements units. Free-moving robotic systems could gain the full benefits of inertial measurements if the measurement units are placed on independently orientable platforms, such as a human-like heads. We illustrate these benefits by analysing recent humanoid robots design and control approaches

Biodynamic Parameters During a Step Down Task in Subjects with Chronic or Recurrent Low Back Pain Classified with Lumbar Instability

Background: Low back pain (LBP) affect a majority of the population. Lumbar instability has been identified as a factor in a significant portion of individuals with LBP but movement characteristics of this population has seen limited research regarding functional tasks. Objective: This study examined biodynamic parameters during a step task. Design: Quasi-experimental with 2 factors, group and side (L/R), and 1 repeated measure (stepping). Statistics: Two-way Mixed-Design Repeated Measures ANOVA with Alpha = .05. Movement task: Subjects with LBP and lumbar spine clinical instability classification (N=11) and control subjects (N=11) performed a step down task from a 9.5 inch height on left and right side. Main outcomes: sEMG activation (%MVC), sEMG onset time at first weight acceptance, Ground Reaction Force; rise time GRF(z) and 3D trunk range of motion (ROM) related to three phases of the step: (1) First single leg support, (2) double support and (3) second single leg support. Main results: ROM was reduced in the LBP group in the full step phase in the sagittal plane (p=.003, power= .99), in the final phase in the frontal plane (p=.021, power=.99) and in the transverse plane (p=.018, power=.99) on left steps. GRF(z) was slower in the LBP group at first weight acceptance when leading with the left leg (p=.016, power= .99). EMG onsets: The LBP group had delayed muscle onsets of the right hip abductors (p=.043, power=.99), left abdominals with left stepping (p=.008, power=.91) and right lumbar extensors with right stepping (p=.025, power=.93). The LBP group had delayed onset of right lumbar extensors with right stepping but earlier onset with left stepping (p=.025, power.93). EMG activation levels was higher in the LBP group in both left and right steps of right lumbar extensors (p=.047, power=.93), right hip abductors (p=.017, power= .68) and left hip abductors (p= .035, power= .96). Conclusion: Subjects with LBP demonstrated a high-load movement strategy during this low-load step task with reduced ROM, increased muscle activation, delayed muscle onsets and slow GRF(z) rise time. Left stepping presented more challenge for this group of predominantly right-footed subjects with LBP classified with lumbar instability

Biodynamic Parameters During a Step Down Task in Subjects with Chronic or Recurrent Low Back Pain Classified with Lumbar Instability

Background: Low back pain (LBP) affect a majority of the population. Lumbar instability has been identified as a factor in a significant portion of individuals with LBP but movement characteristics of this population has seen limited research regarding functional tasks. Objective: This study examined biodynamic parameters during a step task. Design: Quasi-experimental with 2 factors, group and side (L/R), and 1 repeated measure (stepping). Statistics: Two-way Mixed-Design Repeated Measures ANOVA with Alpha = .05. Movement task: Subjects with LBP and lumbar spine clinical instability classification (N=11) and control subjects (N=11) performed a step down task from a 9.5 inch height on left and right side. Main outcomes: sEMG activation (%MVC), sEMG onset time at first weight acceptance, Ground Reaction Force; rise time GRF(z) and 3D trunk range of motion (ROM) related to three phases of the step: (1) First single leg support, (2) double support and (3) second single leg support. Main results: ROM was reduced in the LBP group in the full step phase in the sagittal plane (p=.003, power= .99), in the final phase in the frontal plane (p=.021, power=.99) and in the transverse plane (p=.018, power=.99) on left steps. GRF(z) was slower in the LBP group at first weight acceptance when leading with the left leg (p=.016, power= .99). EMG onsets: The LBP group had delayed muscle onsets of the right hip abductors (p=.043, power=.99), left abdominals with left stepping (p=.008, power=.91) and right lumbar extensors with right stepping (p=.025, power=.93). The LBP group had delayed onset of right lumbar extensors with right stepping but earlier onset with left stepping (p=.025, power.93). EMG activation levels was higher in the LBP group in both left and right steps of right lumbar extensors (p=.047, power=.93), right hip abductors (p=.017, power= .68) and left hip abductors (p= .035, power= .96). Conclusion: Subjects with LBP demonstrated a high-load movement strategy during this low-load step task with reduced ROM, increased muscle activation, delayed muscle onsets and slow GRF(z) rise time. Left stepping presented more challenge for this group of predominantly right-footed subjects with LBP classified with lumbar instability

Dynamic Determinants of the Uncontrolled Manifold during Human Quiet Stance

Human postural sway during stance arises from coordinated multi-joint movements. Thus, a sway trajectory represented by a time-varying postural vector in the multiple-joint-angle-space tends to be constrained to a low-dimensional subspace. It has been proposed that the subspace corresponds to a manifold defined by a kinematic constraint, such that the position of the center of mass (CoM) of the whole body is constant in time, referred to as the kinematic uncontrolled manifold (kinematic-UCM). A control strategy related to this hypothesis (CoM-control-strategy) claims that the central nervous system (CNS) aims to keep the posture close to the kinematic-UCM using a continuous feedback controller, leading to sway patterns that mostly occur within the kinematic-UCM, where no corrective control is exerted. An alternative strategy proposed by the authors (intermittent control-strategy) claims that the CNS stabilizes posture by intermittently suspending the active feedback controller, in such a way to allow the CNS to exploit a stable manifold of the saddle-type upright equilibrium in the state-space of the system, referred to as the dynamic-UCM, when the state point is on or near the manifold. Although the mathematical definitions of the kinematic- and dynamic-UCM are completely different, both UCMs play similar roles in the stabilization of multi-joint upright posture. The purpose of this study was to compare the dynamic performance of the two control strategies. In particular, we considered a double-inverted-pendulum-model of postural control, and analyzed the two UCMs defined above. We first showed that the geometric configurations of the two UCMs are almost identical. We then investigated whether the UCM-component of experimental sway could be considered as passive dynamics with no active control, and showed that such UCM-component mainly consists of high frequency oscillations above 1 Hz, corresponding to anti-phase coordination between the ankle and hip. We also showed that this result can be better characterized by an eigenfrequency associated with the dynamic-UCM. In summary, our analysis highlights the close relationship between the two control strategies, namely their ability to simultaneously establish small CoM variations and postural stability, but also make it clear that the intermittent control hypothesis better explains the spectral characteristics of sway

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