A comprehensive gaze stabilization controller based on cerebellar internal models

Gaze stabilization is essential for clear vision; it is the combined effect of two reflexes relying on vestibular inputs: the vestibulocollic reflex (VCR), which stabilizes the head in space and the vestibulo-ocular reflex (VOR), which stabilizes the visual axis to minimize retinal image motion. The VOR works in conjunction with the opto-kinetic reflex (OKR), which is a visual feedback mechanism that allows the eye to move at the same speed as the observed scene. Together they keep the image stationary on the retina. In this work, we implement on a humanoid robot a model of gaze stabilization based on the coordination of VCR, VOR and OKR. The model, inspired by neuroscientific cerebellar theories, is provided with learning and adaptation capabilities based on internal models. We present the results for the gaze stabilization model on three sets of experiments conducted on the SABIAN robot and on the iCub simulator, validating the robustness of the proposed control method. The first set of experiments focused on the controller response to a set of disturbance frequencies along the vertical plane. The second shows the performances of the system under three-dimensional disturbances. The last set of experiments was carried out to test the capability of the proposed model to stabilize the gaze in locomotion tasks. The results confirm that the proposed model is beneficial in all cases reducing the retinal slip (velocity of the image on the retina) and keeping the orientation of the head stable

Biologically-plausible six-legged running : control and simulation

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (p. 63-66).This thesis presents a controller which produces a stable, dynamic 1.4 meter per second run in a simulated twelve degree of freedom six-legged robot. The algorithm is relatively simple; it consists of only a few hand-tuned feedback loops and is defined by a total of 13 parameters. The control utilizes no vestibular-type inputs to actively control orientation. Evidence from perturbation, robustness, motion analysis, and parameter sensitivity tests indicate a high degree of stability in the simulated gait. The control approach generates a run with an aerial phase, utilizes force information to signal aerial phase leg retraction, has a forward running velocity determined by a single parameter, and couples stance and swing legs using angular momentum information. Both the hypotheses behind the control and the resulting gait are argued to be plausible models of biological locomotion.by Matthew David Malchano.M.Eng

Pattern Generation for Rough Terrain Locomotion with Quadrupedal Robots:Morphed Oscillators & Sensory Feedback

Animals are able to locomote on rough terrain without any apparent difficulty, but this does not mean that the locomotor system is simple. The locomotor system is actually a complex multi-input multi-output closed-loop control system. This thesis is dedicated to the design of controllers for rough terrain locomotion, for animal-like quadrupedal robots. We choose the problem of blind rough terrain locomotion as the target of experiments. Blind rough terrain locomotion requires continuous and momentary corrections of leg movements and body posture, and provides a proper testbed to observe the interaction of different mod- ules involved in locomotion control. As for the specific case of this thesis, we have to design rough terrain locomotion controllers that do not depend on the torque-control capability, have limited sensing, and have to be computationally light, all due to the properties of the robotics platform that we use. We propose that a robust locomotion controller, taking into account the aforementioned constraints, is constructed from at least three modules: 1) pattern generators providing the nominal patterns of locomotion; 2) A posture controller continuously adjusting the attitude of the body and keeping the robot upright; and 3) quick reflexes to react to unwanted momentary events like stumbling or an external force impulse. We introduce the framework of morphed oscillators to systematize the design of pattern gen- erators realized as coupled nonlinear oscillators. Morphed oscillators are nonlinear oscillators that can encode arbitrary limit cycle shapes and simultaneously have infinitely large basins of attraction. More importantly, they provide dynamical systems that can assume the role of feedforward locomotion controllers known as Central Pattern Generators (CPGs), and accept discontinuous sensory feedback without the risk of producing discontinuous output. On top of the CPG module, we add a kinematic model-based posture controller inspired by virtual model control (VMC), to control the body attitude. Virtual model control produces forces, and through the application of the Jacobian transpose method, generates torques which are added to the CPG torques. However, because our robots do not have a torque- control capability, we adapt the posture controller by producing task-space velocities instead of forces, thus generating joint-space velocity feedback signals. Since the CPG model used for locomotion generates joint velocities and accepts feedback without the fear of instability or discontinuity, the posture control feedback is easily integrated into the CPG dynamics. More- over, we introduce feedback signals for adjusting the posture by shifting the trunk positions, which directly update the limit cycle shape of the morphed oscillator nodes of the CPG. Reflexes are added, with minimal complexity, to react to momentary events. We implement simple impulse-based feedback mechanisms inspired by animals and successful rough terrain robots to 1) flex the leg if the robot is stumbling (stumbling correction reflex); 2) extend the leg if an expected contact is missing (leg extension reflex); or 3) initiate a lateral stepping sequence in response to a lateral external perturbation. CPG, posture controller, and reflexes are put together in a modular control architecture alongside additional modules that estimate inclination, control speed and direction, maintain timing of feedback signals, etc. [...

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

AGE- AND SEX-DEPENDENT ALTERATIONS IN PRIMARY SOMATOSENSORY NEURONAL CALCIUM NETWORK DYNAMICS DURING LOCOMOTION

Over the past 30 years, the calcium (Ca2+) hypothesis of brain aging has provided clear evidence that hippocampal neuronal Ca2+ dysregulation is a key biomarker of aging. Indeed, age-dependent Ca2+-mediated changes in intrinsic excitability, synaptic plasticity, and activity have helped identify some of the mechanisms engaged in memory and cognitive decline. However, much of this work has been done at the single-cell level, mostly in slice preparations, and in restricted structures of the brain. Recently, our lab identified age- and Ca2+-related neuronal network dysregulation in the cortex of the anesthetized animal. Still, investigations in the awake animal are needed to test the generalizability of the Ca2+ hypothesis of brain aging and dementia. Here, we used in vigilo two-photon (2P) imaging in ambulating mice, to image GCaMP8f in the primary somatosensory cortex (S1), during ambulation and at rest. In order to investigate aging- and sex- related changes in the neuronal Ca2+ network, a continuous wavelet transform (CWT) analysis was developed (MATLAB) to extract measures of network communication while also addressing pair-wise correlations at single-cell resolution. Following imaging, gait behavior was characterized to test for changes in locomotor stability. During ambulation and compared to rest, in both young (4 months) and aged mice (22 months), an increase in connectivity and synchronicity was noted. An age-dependent increase in network synchronicity was seen in ambulating aged males only. Additionally, females displayed a greater number of active neurons, area-under-curve, and neuronal activity compared to males, particularly during ambulation. These results suggest S1 Ca2+ dynamics and network synchronicity are likely contributors of locomotor stability. We believe this work raises awareness of central elements at play in S1 where neuronal Ca2+ network dysregulation is seen with aging, perhaps highlighting potential therapeutic targets that may help offset age-dependent increases in falls

Towards understanding of climbing, tip-over prevention and self-righting behaviors in Hexapoda

Die vorliegende Dissertation mit dem Titel “Towards understanding of climbing, tip-over prevention and self-righting behaviors in Hexapoda” untersucht in drei Studien exemplarisch, wie (i) Wüstenameisen ihre Beine einsetzen um An- und Abstiege zu überwinden, wie (ii) Wüsten- und Waldameisen ein Umkippen an steilen Anstiegen vermeiden, und wie sich (iii) Madagaskar-Fauchschaben, Amerikanische Großschaben und Blaberus discoidalis Audinet-Servill, 1839 aus Rückenlagen drehen und aufrichten. Neuartige biomechanischen Beschreibungen umfassen unter anderem: Impuls- und Kraftwirkungen einzelner Ameisenbeine auf den Untergrund beim Bergauf- und Bergabklettern, Kippmomente bei kletternden Ameisen, Energiegebirge-Modelle (energy landscapes) zur Quantifizierung der Körperform für die funktionelle Beschreibung des Umdrehens aus der Rückenlage

Analysis of Human Push Recovery Motions Based on Optimization

The ability to cope with large perturbations is essential to avoid falling for humans as well as for humanoid robots. Every day millions of people are affected by injuries due to falling. This is a huge problem not only for the individuum but also for the society as it costs the health care systems billions of euros. Also in the field of humanoid robots fall avoidance is very important as it protects robots against breakage. In this thesis, the problem of fall avoidance is addressed using a combination of optimization, human-modeling and recorded push recovery motions. The aim is to identify the principles that lead to human-like push recovery motions. The human is modeled by rigid segments combined by joints leading to an underactuated multi-body representation. These models are included in multiple stage optimal control problems to reconstruct and sythesize human push recovery motions considering the dynamics of a human over the whole time horizon. Due to the high nonlinearity, the optimization problem is solved based on a direct multiple shooting method. To analyze the human push recovery motions, dynamically-consistent motions for the model that closely track experimental data are produced. The joint angles and joint torques for the human model controlled by joint torque derivatives are compared for perturbed and unperturbed motions from two subjects. The results verify the assumption that the heavier the perturbation is and the higher it is applied at the upper body, the larger are the resulting joint torques. We show that including optimally chosen spring-damper elements in the joints can reduce the active joint torques significantly. We further exploit our motion reconstruction approach to determine the states that are most affected during a perturbation. Relevant parameters such as the orientation and position of the head and body, joint angles and torques of the perturbed motions are analyzed for deviations to the unperturbed motions at the point in time when the push occurs. Identifying the point in time when the model states of the perturbed motions differ from the unperturbed motions, the reaction times are determined. To better understand human push recovery motions, we also investigate in a motion sythesis approach. This approach enables a control hypothesis, in the form of a specific objective function, to be formed. The minimization of effort combined with a periodicity formulation results in human-like motions and the influence of the push strength is analyzed. Formulating the objective function as a weighted linear combination of possible optimality criteria provides the possibility to analyze different optimality criteria and their resulting motion. The difficulty is, that for a given motion, it is not known, which criteria lead to that specific motion. In this thesis, the results for different basal objective functions are analyzed. These studies prepare to determine the optimal weights of the criteria by including the presented motion generation formulation in an inverse optimal control problem. Having analyzed general weights that lead to a good approximation of the human recovery motions, the resulting objective function can be used to generate push recovery motions also for humanoid robots or assistive devices such as exoskeletons. To show another application in the improvement of technical assistive devices, we include two combined human exoskeleton models of different weights in our calculations. This allows us to analyze the joint torques for these models including the exoskeletons and compare the results to a human model. As the resulting joint torques are quite large, we also formulate combined human exoskeleton models with passive spring-damper elements that act in parallel to the active torques. This compliant formulation leads to a significant reduction of the active joint torque needed for the recovery motion. The reduction of the active joint torques allows the reduction of energy needed for the recovery motion or can enable the recovery from stronger perturbations

Fast Sensing and Adaptive Actuation for Robust Legged Locomotion

Robust legged locomotion in complex terrain demands fast perturbation detection and reaction. In animals, due to the neural transmission delays, the high-level control loop involving the brain is absent from mitigating the initial disturbance. Instead, the low-level compliant behavior embedded in mechanics and the mid-level controllers in the spinal cord are believed to provide quick response during fast locomotion. Still, it remains unclear how these low- and mid-level components facilitate robust locomotion. This thesis aims to identify and characterize the underlining elements responsible for fast sensing and actuation. To test individual elements and their interplay, several robotic systems were implemented. The implementations include active and passive mechanisms as a combination of elasticities and dampers in multi-segment robot legs, central pattern generators inspired by intraspinal controllers, and a synthetic robotic version of an intraspinal sensor. The first contribution establishes the notion of effective damping. Effective damping is defined as the total energy dissipation during one step, which allows quantifying how much ground perturbation is mitigated. Using this framework, the optimal damper is identified as viscous and tunable. This study paves the way for integrating effective dampers to legged designs for robust locomotion. The second contribution introduces a novel series elastic actuation system. The proposed system tackles the issue of power transmission over multiple joints, while featuring intrinsic series elasticity. The design is tested on a hopper with two more elastic elements, demonstrating energy recuperation and enhanced dynamic performance. The third contribution proposes a novel tunable damper and reveals its influence on legged hopping. A bio-inspired slack tendon mechanism is implemented in parallel with a spring. The tunable damping is rigorously quantified on a central-pattern-generator-driven hopping robot, which reveals the trade-off between locomotion robustness and efficiency. The last contribution explores the intraspinal sensing hypothesis of birds. We speculate that the observed intraspinal structure functions as an accelerometer. This accelerometer could provide fast state feedback directly to the adjacent central pattern generator circuits, contributing to birds’ running robustness. A biophysical simulation framework is established, which provides new perspectives on the sensing mechanics of the system, including the influence of morphologies and material properties. Giving an overview of the hierarchical control architecture, this thesis investigates the fast sensing and actuation mechanisms in several control layers, including the low-level mechanical response and the mid-level intraspinal controllers. The contributions of this work provide new insight into animal loco-motion robustness and lays the foundation for future legged robot design