Two explorations in Dynamical Systems and Mechanics: avoiding cones conditions and higher dimensional twist. Directional friction in bio-inspired locomotion

This thesis contains the work done by Paolo Gidoni during the doctorate programme in Matematical Analysis at SISSA, under the supervision of A. Fonda and A. DeSimone. The thesis is composed of two parts: "Avoiding cones conditions and higher dimensional twist" and "Directional friction in bio-inspired locomotion"

From cell to robot : A bio-inspired locomotion device

Bionics or biomimetics is an interdisciplinary research field, a scientific approach to applicate naturally developed biological systems, methods and solutions to the study and design of technology and engineering systems. Therefore bionics is based on an exclusive mutuality between life sciences and technology and its associated sciences, such as robotics. Robots are special artificial agents, and they have much in common with biological agents in case of the need to adapt to their environment. A popular trend in robotics is the development of soft robots – artificial agents with a rather flexible skin or shape, propulsing itself with some type of crawling movement. These robots are able to deform and adapt to obstacles during locomotion, which is an advantage over classical wheeled or legged propulsion. Bionics is helpful in developing locomotion devices for robots, e. g. bio-inspired climbing robots, such as geckobots, utilise the biological gecko adhesion model for climbing. Most of these bio-inspired climbing robots have the disadvantage of using legs for locomotion. The idea is to find a new biological model for a bionic robotic locomotion device that is using an adhesion-dependent crawling locomotion, which allows the robot to climb (or at least be able to master inclinations) and still has a rather soft and deformable shape providing the flexibility of adaptation to obstacles or a changing environment. Surprisingly, single cells, such as amoebae or animal tissue cells, provide these required properties: the ability to crawl on surfaces by formation of adhesion bonds and a very deformable shape – a perfect model for such robots. These cells are reorganising their cytoskeletal cortex and create a visco-elastic gradient which is polarising the cell with a sol-like "sloppy" leading edge at the front and a gel-like "stiff" rear end. This work demonstrates that it is possible to transfer the biophysical locomotion mechanism of cell migration to a simulation model of soft robots, which use an adhesion-dependent mechanism to autonomously create a polarising elasticity gradient during motion. It introduces and analyses three robot models, which are able to move on surfaces with different built-in integrations of this polarisation mechanism. Simulations show that the robots are flexible enough to adapt to changing environments, such as rough surfaces. One model is even able to crawl on walls and ceilings against the direction of gravity. Finally, this work offers some ideas for possible constructions and usability of these robots, and what insights their analysis might give into principles of biological cell migration

Bio-inspired locomotion using oscillating elastic plates

We develop a fluid-structure interaction computational model based on the lattice Boltzmann method and the thin plate model to investigate the impact of different strategies for bio-inspired locomotion with an oscillating elastic plate. We first probe the effects of actuation patterns on the dynamic response of plates with different mechanical and geometrical properties. In particular, we consider the actuation using a distributed internal moment that represents the actuation of piezoelectric smart materials and compare the hydrodynamic performance of such plates with the hydrodynamics of a plunging elastic plate. We then examine the combined plate actuation that integrates plunging using an external actuator with internal piezoelectric actuation. We search for hydrodynamic regimes in which the synergy of two different actuation modes leads to improved thrust production and efficiency. Furthermore we investigate the impact of inhomogeneous mechanical properties through a tapered geometry. We show that the tapered thickness, and ultimately stiffness gradient, can be harnessed to enhance the propulsive performance and efficiency. We link this increased performance to the shift from oscillatory to undulatory regime. We demonstrate that this shift is due to the acoustic black hole effect, a phenomenon where waves are trapped in tapered structures, which allows to maintain travelling waves in the plate. Finally, we explore this vast parameter space through a multi-objective optimization procedure based on a genetic algorithm to highlight key futures of tapered designs to maximize the swimming performance.Ph.D

Sma control for bio-mimetic fish locomotion

In this paper, we describe our current work on bio-inspired locomotion systems using smart materials. The aim of this work is to investigate alternative actuation mechanisms based on smart materials, exploring the possibility of building motor-less and gear-less robots. A swimming underwater robot is being developed whose movements are generated using such materials, concretely Shape Memory Alloys. This paper focuses on the actuators control in order to generate the desired motion pattern

Understanding the Role of Morphology and Kinematics in Bio-Inspired Locomotion

Inspired by the advanced capabilities of fish and other aquatic swimmers, in this thesis, a greater understanding of fish-like propulsion has been sought in terms of morphology and kinematics. Unsteady potential flow simulations on real cetacean flukes reveal that the effect of shape and gait on the swimming performance are not intertwined and are in fact independent. There is one fluke shape that maximizes the propulsive efficiency regardless of the gait and vice versa. It is also determined that the shape and the gait of the fluke have a considerable influence on the wake topology and in turn the Strouhal number. Evolutionary optimization is used to isolate the shape effects and study optimum conditions when the kinematic features of the animals are varied. Searching the optimum swimmer in terms of swimming gait is performed by considering the three main aspects of the swimming performance: swimming speed, swimming range, and efficiency. Optimum conditions are found when i) the swimmer keeps the duty cycle low and uses sinusoidal-like motion by maintaining higher pitching amplitudes to provide higher thrust and swimming range; ii) the swimmer uses square-like waveform shapes by increasing the duty cycle and using small pitching amplitudes which decrease the swimming range but increase the swimming speed. In all combinations, swimming efficiency is maintained at the maximum achievable level. Scaling laws are presented to predict thrust production and power consumption of the swimmers by accounting for three-dimensionality with shape and gait variations. The scaling laws presented here provide insight into the flow physics that drive thrust production, power consumption, and efficient swimming when the morphology and kinematics are varied

Dynamic Analysis and Modeling of Jansen Mechanism

AbstractTheo Jansen mechanism is gaining wide spread popularity among legged robotics researchers due to its scalable design, energy efficiency, low payload to machine load ratio, bio-inspired locomotion, deterministic foot trajectory among others. In this paper, we present dynamic analysis of a four legged Theo Jansen link mechanism using projection method that results in constraint force and equivalent Lagrange's equation of motion necessary for any meaningful extension and/or optimization of this niche mechanism. Numerical simulations using MaTX is presented in conjunction with the dynamic analysis. This research sets a theoretical basis for future investigation into Theo Jansen mechanism

Bio-inspired locomotion control for UBot self-reconfigurable modular robot

This paper first presents a mathematic CPG (central pattern generator) model which has been developed based on the characteristics of a self-reconfigurable modular robot (UBot)'s modules with universal joints. Then, a bionic motion neural control network based on the CPG is proposed to solve the problem of multi-mode locomotion control problem in the complex environment. The bionic network is composed of perceptual neurons, CPG phase modulation network and motor neurons, so it can coordinate the walking and creeping gait of the modular robot before and after deformation, and adapt to autonomous movement in the complex environment with challenging features, such as steps, slopes and obstacles. Finally, the proposed motion control algorithm is verified by experiments

Rich and Robust Bio-Inspired Locomotion Control for Humanoid Robots

Bipedal locomotion is a challenging task in the sense that it requires to maintain dynamic balance while steering the gait in potentially complex environments. Yet, humans usually manage to move without any apparent difficulty, even on rough terrains. This requires a complex control scheme which is far from being understood. In this thesis, we take inspiration from the impressive human walking capabilities to design neuromuscular controllers for humanoid robots. More precisely, we control the robot motors to reproduce the action of virtual muscles commanded by stimulations (i.e. neural signals), similarly to what is done during human locomotion. Because the human neural circuitry commanding these muscles is not completely known, we make hypotheses about this control scheme to simplify it and progressively refine the corresponding rules. This thesis thus aims at developing new walking algorithms for humanoid robots in order to obtain fast, human-like and energetically efficient gaits. In particular, gait robustness and richness are two key aspects of this work. In other words, the gaits developed in the thesis can be steered by an external operator, while being resistant to external perturbations. This is mainly tested during blind walking experiments on COMAN, a 95 cm tall humanoid robot. Yet, the proposed controllers can be adapted to other humanoid robots. In the beginning of this thesis, we adapt and port an existing reflex-based neuromuscular model to the real COMAN platform. When tested in a 2D simulation environment, this model was capable of reproducing stable human-like locomotion. By porting it to real hardware, we show that these neuromuscular controllers are viable solutions to develop new controllers for robotics locomotion. Starting from this reflex-based model, we progressively iterate and transform the stimulation rules to add new features. In particular, gait modulation is obtained with the inclusion of a central pattern generator (CPG), a neural circuit capable of producing rhythmic patterns of neural activity without receiving rhythmic inputs. Using this CPG, the 2D walker controllers are incremented to generate gaits across a range of forward speeds close to the normal human one. By using a similar control method, we also obtain 2D running gaits whose speed can be controlled by a human operator. The walking controllers are later extended to 3D scenarios (i.e. no motion constraint) with the capability to adapt both the forward speed and the heading direction (including steering curvature). In parallel, we also develop a method to automatically learn stimulation networks for a given task and we study how flexible feet affect the gait in terms of robustness and energy efficiency. In sum, we develop neuromuscular controllers generating human-like gaits with steering capabilities. These controllers recruit three main components: (i) virtual muscles generating torque references at the joint level, (ii) neural signals commanding these muscles with reflexes and CPG signals, and (iii) higher level commands controlling speed and heading. Interestingly, these developments target humanoid robots locomotion but can also be used to better understand human locomotion. In particular, the recruitment of a CPG during human locomotion is still a matter open to debate. This question can thus benefit from the experiments performed in this thesis