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

Modeling of the human vestibular system and integration in a simulator for the study of orientation and balance control

[Abstract] Biologically, the vestibular feedback is critical to the ability of human body to balance in different conditions. This paper presents a human-inspired orientation and balance control of a three degree- of-freedom (DOF) simulator that emulates a person sitting in a platform. In accordance with the role in humans, the control is essentially based on the vestibular system (VS), which regulates and stabilizes gaze during head motion, by means of modeling the behavior of the semicircular canals and otoliths in the presence of stimuli, i.e., linear and angular accelerations/velocities derived by the turns experienced by the robot head on the three Cartesian axes. The semicircular canal is used as the angular velocity sensor to perform the postural control of the robot. Simulation results in the MATLAB/Simulink environment are given to show that the orientation of the head in space (roll, pitch and yaw) can be successfully controlled by a proportional-integral-derivative (PID) with noise filter for each DOF.[Resumen] Biológicamente, la retroalimentación vestibular es crítica para la capacidad del cuerpo humano para equilibrarse en diferentes condiciones. Este artículo presenta una orientación inspirada por el hombre y el control de equilibrio de un simulador de tres grados de libertad (DOF) que emula a una persona sentada en una plataforma. De acuerdo con el papel en los humanos, el control se basa esencialmente en el sistema vestibular (VS), que regula y estabiliza la mirada durante el movimiento de la cabeza, mediante el modelado del comportamiento de los canales semicirculares y los otolitos en presencia de estímulos, es decir, aceleraciones / velocidades lineales y angulares derivadas de los giros experimentados por la cabeza del robot en los tres ejes cartesianos. El canal semicircular se utiliza como sensor de velocidad angular para realizar el control postural del robot. Los resultados de la simulación en el entorno de MATLAB / Simulink se proporcionan para mostrar que la orientación de la cabeza en el espacio (balanceo, inclinación y guiñada) se puede controlar con éxito mediante un derivado proporcional-integral (PID) con filtro de ruido para cada DOF

Idiothetic Verticality Estimation Through Head Stabilization Strategy

International audienceThe knowledge of the gravitational vertical is fundamental for the autonomous control of humanoids and other free-moving robotic systems such as rovers and drones. This article deals with the hypothesis that the so-called 'head stabilization strategy' observed in humans and animals facilitates the estimation of the true vertical from inertial sensing only. This problem is difficult because inertial measurements respond to a combination of gravity and fictitious forces that are hard to disentangle. From simulations and experiments, we found that the angular stabilization of a platform bearing inertial sensors enables the application of the separation principle. This principle, which permits one to design estimators and controllers independently from each other, typically applies to linear systems, but rarely to nonlinear systems. We found empirically that, given inertial measurements, the angular regulation of a platform results in a system that is stable and robust and which provides true vertical estimates as a byproduct of the feedback. We conclude that angularly stabilized inertial measurement platforms could liberate robots from ground-based measurements for postural control, locomotion, and other functions, leading to a true idiothetic sensing modality, that is, not based on any external reference but the gravity field

The design, analysis and evaluation of a humanoid robotic head

Where robots interact directly with humans on a ‘one-to-one’ basis, it is often quite important for them to be emotionally acceptable, hence the growing interesting in humanoid robots. In some applications it is important that these robots do not just resemble a human being in appearance, but also move like a human being too, to make them emotionally acceptable – hence the interest in biomimetic humanoid robotics. The research described in this thesis is concerned with the design, analysis and evaluation of a biomimetic humanoid robotic head. It is biomimetic in terms of physical design - which is based around a simulated cervical spine, and actuation, which is achieved using pneumatic air muscles (PAMS). The primary purpose of the research, however, and the main original contribution, was to create a humanoid robotic head capable of mimicking complex non-purely rotational human head movements. These include a sliding front-to-back, lateral movement, and a sliding, side-to-side lateral movement. A number of different approaches were considered and evaluated, before finalising the design. As there are no generally accepted metrics in the literature regarding the full range of human head movements, the best benchmarks for comparison are the angular ranges and speeds of humans in terms on pitch (nod), roll (tilt) and yaw (rotate) were used for comparison, and these they were considered desired ranges for the robot. These measured up well in comparison in terms of angular speed and some aspects of range of human necks. Additionally, the lateral movements were measured during the nod, tilt and rotate movements, and established the ability of the robot to perform the complex lateral movements seen in humans, thus proving the benefits of the cervical spine approach. Finally, the emotional acceptance of the robot movements was evaluated against another (commercially made) robot and a human. This was a blind test, in that the (human) evaluators had no way of knowing whether they were evaluation a human or a robot. The tests demonstrated that on scales of Fake/Natural, Machinelike/Humanlike and Unconcsious/Conscious the robot the robot scored similarly to the human

Learning body models: from humans to humanoids

Humans and animals excel in combining information from multiple sensory modalities, controlling their complex bodies, adapting to growth, failures, or using tools. These capabilities are also highly desirable in robots. They are displayed by machines to some extent. Yet, the artificial creatures are lagging behind. The key foundation is an internal representation of the body that the agent - human, animal, or robot - has developed. The mechanisms of operation of body models in the brain are largely unknown and even less is known about how they are constructed from experience after birth. In collaboration with developmental psychologists, we conducted targeted experiments to understand how infants acquire first "sensorimotor body knowledge". These experiments inform our work in which we construct embodied computational models on humanoid robots that address the mechanisms behind learning, adaptation, and operation of multimodal body representations. At the same time, we assess which of the features of the "body in the brain" should be transferred to robots to give rise to more adaptive and resilient, self-calibrating machines. We extend traditional robot kinematic calibration focusing on self-contained approaches where no external metrology is needed: self-contact and self-observation. Problem formulation allowing to combine several ways of closing the kinematic chain simultaneously is presented, along with a calibration toolbox and experimental validation on several robot platforms. Finally, next to models of the body itself, we study peripersonal space - the space immediately surrounding the body. Again, embodied computational models are developed and subsequently, the possibility of turning these biologically inspired representations into safe human-robot collaboration is studied.Comment: 34 pages, 5 figures. Habilitation thesis, Faculty of Electrical Engineering, Czech Technical University in Prague (2021

Modeling the Bat Spatial Navigation System: A Neuromorphic VLSI Approach

Autonomously navigating robots have long been a tough challenge facing engineers. The recent push to develop micro-aerial vehicles for practical military, civilian, and industrial use has added a significant power and time constraint to the challenge. In contrast, animals, from insects to humans, have been navigating successfully for millennia using a wide range of variants of the ultra-low-power computational system known as the brain. For this reason, we look to biological systems to inspire a solution suitable for autonomously navigating micro-aerial vehicles. In this dissertation, the focus is on studying the neurobiological structures involved in mammalian spatial navigation. The mammalian brain areas widely believed to contribute directly to navigation tasks are the Head Direction Cells, Grid Cells and Place Cells found in the post-subiculum, the medial entorhinal cortex, and the hippocampus, respectively. In addition to studying the neurobiological structures involved in navigation, we investigate various neural models that seek to explain the operation of these structures and adapt them to neuromorphic VLSI circuits and systems. We choose the neuromorphic approach for our systems because we are interested in understanding the interaction between the real-time, physical implementation of the algorithms and the real-world problem (robot and environment). By utilizing both analog and asynchronous digital circuits to mimic similar computations in neural systems, we envision very low power VLSI implementations suitable for providing practical solutions for spatial navigation in micro-aerial vehicles

Aerospace Medicine and Biology. A continuing bibliography with indexes

This bibliography lists 244 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1981. Aerospace medicine and aerobiology topics are included. Listings for physiological factors, astronaut performance, control theory, artificial intelligence, and cybernetics are included

The Consequences of Speed: Studies of Cavitation During the Mantis Shrimp Strike and the Control of Rapid Deceleration During Toad Landing

There are consequences of moving quickly in this world. Here we investigate how two very different species, mantis shrimp (Odontodactylus scyllarus) and cane toads (Bufo marinus), negotiate forces that result from moving rapidly in different environments. To study the mechanical principles and fluid dynamics of ultrafast power-amplified systems, we built Ninjabot, a physical model of the extremely fast mantis shrimp. While mantis shrimp produce damaging cavitation upon impact with their prey, they do not cavitate during the forward portion of their strike despite extreme speeds. In order to study cavitation onset in non-linear flows common during the mantis shrimp strike, we used Ninjabot to produce strikes of varying kinematics and measured cavitation presence or absence. We found that in rotating and accelerating biological conditions, cavitation inception is best explained only by maximum linear velocity. Thus, studies of cavitation onset in biological conditions only need to focus on maximum velocity. On land, moving quickly requires avoiding or preparing for impact with other objects, often the ground. Within anurans (frogs and toads), a group well known for jumping, cane toads are known to perform particularly controlled landings in which the forelimbs are used to decelerate and balance the body after impact as the hind limbs are lowered to the ground. Here I explore whether and how toads modulate landing preparation depending on hopping and landing conditions and what this can tell us about how they utilize sensory information to help them perform controlled landings. We found that toads modulate three components of impact preparation to specific hop conditions: 1) They position the forelimbs to hit the ground first by protracting and abducting the humeri, 2) They prepare and brace for impact by extending the elbows and activating underlying musculature to stiffen the joint and 3) they control torques during the landing by retracting the hind limbs and rotating the forelimbs to align with the impact angle. By perturbing landing conditions we found that toads tune these components to specific landing conditions with a combination of passive and active control and toads do so by primarily relying on non-visual sensory feedback

How to build a biological machine using engineering materials and methods

We present work in 3D printing electric motors from basic materials as the key to building a self-replicating machine to colonise the Moon. First, we explore the nature of the biological realm to ascertain its essence, particularly in relation to the origin of life when the inanimate became animate. We take an expansive view of this to ascertain parallels between the biological and the manufactured worlds. Life must have emerged from the available raw material on Earth and, similarly, a self-replicating machine must exploit and leverage the available resources on the Moon. We then examine these lessons to explore the construction of a self-replicating machine using a universal constructor. It is through the universal constructor that the actuator emerges as critical. We propose that 3D printing constitutes an analogue of the biological ribosome and that 3D printing may constitute a universal construction mechanism. Following a description of our progress in 3D printing motors, we suggest that this engineering effort can inform biology, that motors are a key facet of living organisms and illustrate the importance of motors in biology viewed from the perspective of engineering (in the Feynman spirit of "what I cannot create, I cannot understand")