Enabling New Functionally Embedded Mechanical Systems Via Cutting, Folding, and 3D Printing

Traditional design tools and fabrication methods implicitly prevent mechanical engineers from encapsulating full functionalities such as mobility, transformation, sensing and actuation in the early design concept prototyping stage. Therefore, designers are forced to design, fabricate and assemble individual parts similar to conventional manufacturing, and iteratively create additional functionalities. This results in relatively high design iteration times and complex assembly strategies

Non-inertial Undulatory Locomotion Across Scales

Locomotion is crucial to behaviors such as predator avoidance, foraging, and mating. In particular, undulatory locomotion is one of the most common forms of locomotion. From microscopic flagellates to swimming fish and slithering snakes, this form of locomotion is a remarkably robust self-propulsion strategy that allows a diversity of organisms to navigate myriad environments. While often thought of as exclusive to limbless organisms, a variety of locomotors possessing few to many appendages rely on waves of undulation for locomotion. In inertial regimes, organisms can leverage the forces generated by their body and the surrounding medium's inertia to enhance their locomotion (e.g., coast or glide). On the other hand, in non-inertial regimes self-propulsion is dominated by damping (viscous or frictional), and thus the ability for organisms to generate motion is dependent on the sequence of internal shape changes. In this thesis, we study a variety of undulating systems that locomote in highly damped regimes. We perform studies on systems ranging from zero to many appendages. Specifically, we focus on four distinct undulatory systems: 1) C. elegans, 2) quadriflagellate algae (bearing four flagella), 3) centipedes on terrestrial environments, and 4) centipedes on fluid environments. For each of these systems, we study how the coordination of their many degrees of freedom leads to specific locomotive behaviors. Further, we propose hypotheses for the observed behaviors in the context of each of these system's ecology.Ph.D

Climbing and Walking Robots

With the advancement of technology, new exciting approaches enable us to render mobile robotic systems more versatile, robust and cost-efficient. Some researchers combine climbing and walking techniques with a modular approach, a reconfigurable approach, or a swarm approach to realize novel prototypes as flexible mobile robotic platforms featuring all necessary locomotion capabilities. The purpose of this book is to provide an overview of the latest wide-range achievements in climbing and walking robotic technology to researchers, scientists, and engineers throughout the world. Different aspects including control simulation, locomotion realization, methodology, and system integration are presented from the scientific and from the technical point of view. This book consists of two main parts, one dealing with walking robots, the second with climbing robots. The content is also grouped by theoretical research and applicative realization. Every chapter offers a considerable amount of interesting and useful information

Improved Lighthill fish swimming model for bio-inspired robots - Modelling, computational aspects and experimental comparisons.

International audienceThe best known analytical model of swimming was originally developed by Lighthill and is known as large amplitude elongated body theory (LAEBT). Recently, this theory has been improved and adapted to robotics through a series of studies [Boyer et al., 2008, 2010; Candelier et al., 2011] ranging from hydrodynamic modelling to mobile multibody system dynamics. This article marks a further step towards the Lighthill theory. The LAEBT is ap- plied to one of the best bio-inspired swimming robots yet built: the AmphiBot III, a modular anguilliform swimming robot. To that end, we apply a Newton-Euler modelling approach and focus our attention on the model of hydrodynamic forces. This model is numerically in- tegrated in real time by using an extension of the Newton-Euler recursive forward dynamics algorithm for manipulators to a robot without a fixed base. Simulations and experiments are compared on undulatory gaits and turning manoeuvres for a wide range of parameters. The discrepancies between modelling and reality do not exceed 16% for the swimming speed, while requiring only the one-time calibration of a few hydrodynamic parameters. Since the model can be numerically integrated in real time, it has significantly superior accuracy com- pared with computational speed ratio, and is, to the best of our knowledge, one of the most accurate models that can be used in real-time. It should provide an interesting tool for the design and control of swimming robots. The approach is presented in a self contained manner, with the concern to help the reader not familiar with fluid dynamics to get insight both into the physics of swimming and the mathematical tools that can help its modelling

Simplifying robotic locomotion by escaping traps via an active tail

Legged systems offer the ability to negotiate and climb heterogeneous terrains, more so than their wheeled counterparts \cite{freedberg_2012}. However, in certain complex environments, these systems are susceptible to failure conditions. These scenarios are caused by the interplay between the locomotor's kinematic state and the local terrain configuration, thus making them challenging to predict and overcome. These failures can cause catastrophic damage to the system and thus, methods to avoid such scenarios have been developed. These strategies typically take the form of environmental sensing or passive mechanical elements that adapt to the terrain. Such methods come at an increased control and mechanical design complexity for the system, often still being susceptible to imperceptible hazards. In this study, we investigated whether a tail could serve to offload this complexity by acting as a mechanism to generate new terradynamic interactions and mitigate failure via substrate contact. To do so, we developed a quadrupedal C-leg robophysical model (length and width = 27 cm, limb radius = 8 cm) capable of walking over rough terrain with an attachable actuated tail (length = 17 cm). We investigated three distinct tail strategies: static pose, periodic tapping, and load-triggered (power) tapping, while varying the angle of the tail relative to the body. We challenged the system to traverse a terrain (length = 160 cm, width = 80 cm) of randomized blocks (length and width = 10 cm, height = 0 to 12 cm) whose dimensions were scaled to the robot. Over this terrain, the robot exhibited trapping failures independent of gait pattern. Using the tail, the robot could free itself from trapping with a probability of 0 to 0.5, with the load-driven behaviors having comparable performance to low frequency periodic tapping across all tested tail angles. Along with increasing this likelihood of freeing, the robot displayed a longer survival distance over the rough terrain with these tail behaviors. In summary, we present the beginning of a framework that leverages mechanics via tail-ground interactions to offload limb control and design complexity to mitigate failure and improve legged system performance in heterogeneous environments.M.S

MOTION CONTROL SIMULATION OF A HEXAPOD ROBOT

This thesis addresses hexapod robot motion control. Insect morphology and locomotion patterns inform the design of a robotic model, and motion control is achieved via trajectory planning and bio-inspired principles. Additionally, deep learning and multi-agent reinforcement learning are employed to train the robot motion control strategy with leg coordination achieves using a multi-agent deep reinforcement learning framework. The thesis makes the following contributions: First, research on legged robots is synthesized, with a focus on hexapod robot motion control. Insect anatomy analysis informs the hexagonal robot body and three-joint single robotic leg design, which is assembled using SolidWorks. Different gaits are studied and compared, and robot leg kinematics are derived and experimentally verified, culminating in a three-legged gait for motion control. Second, an animal-inspired approach employs a central pattern generator (CPG) control unit based on the Hopf oscillator, facilitating robot motion control in complex environments such as stable walking and climbing. The robot\u27s motion process is quantitatively evaluated in terms of displacement change and body pitch angle. Third, a value function decomposition algorithm, QPLEX, is applied to hexapod robot motion control. The QPLEX architecture treats each leg as a separate agent with local control modules, that are trained using reinforcement learning. QPLEX outperforms decentralized approaches, achieving coordinated rhythmic gaits and increased robustness on uneven terrain. The significant of terrain curriculum learning is assessed, with QPLEX demonstrating superior stability and faster consequence. The foot-end trajectory planning method enables robot motion control through inverse kinematic solutions but has limited generalization capabilities for diverse terrains. The animal-inspired CPG-based method offers a versatile control strategy but is constrained to core aspects. In contrast, the multi-agent deep reinforcement learning-based approach affords adaptable motion strategy adjustments, rendering it a superior control policy. These methods can be combined to develop a customized robot motion control policy for specific scenarios

3D Modelling and design of a bioloid compliant quadruped leg

Dissertação de mestrado integrado em Engenharia BiomédicaIn the growing fields of rehabilitation robotics, prosthetics, and walking robots, the modeling of a real robot is a complex and passionate challenge. On the crossing point of mechanics, physics and computer-science, the development of a complete model involves multiple tasks ranging from the 3D modeling of the different body parts, the measure of the different physic properties, the understanding of the requirements for an accurate simulation, to the development of a robotic controller. In order to minimize large forces due to shocks, to safely interact with the user or the environment, and knowing the ability of passive elastic elements to store and release energy, compliant mechanisms are increasingly being applied in robots applications. This work aims to the elaboration of an accurate efficient three-dimensional model of the legs of the quadruped Bioloid robot and the development of a world showing the effect on WebotsTM simulation software developed by Cyberbotics Ltd. The goal was to design a segmented pantographic leg with compliant joints, in order to actively retract the collision and the impact of the quadruped legs with the ground during locomotion. Geometrical and mechanical limits have to be evaluated and considered for the modeling setup. Finally a controller based on the use of Central Pattern Generators was improved in order to adapt to the novel model and simple tests were performed in the WebotsTM, rendering a 3D model simulation for the different values of spring-damping coefficients at the legs knee joint. Through the a MATLAB® algorithm, the characterization of the joint angles during simulation was possible to be assessed.A modelação de um robot real é um desafio complexo e fascinante na crescente área da Robótica, que engloba desde robots de reabilitação, próteses a uma diversidade de outros dispositivos locomotores. No cruzamento da mecânica com a física e as ciências computacionais, o desenvolvimento de um modelo completo envolve várias tarefas que vão desde a modelação 3D das diferentes partes do corpo, a medição das propriedades físicos inerentes, a compreensão dos requisitos para uma simulação precisa bem como a aplicação de um controlador robótico. A fim de minimizar grandes forças devido a choques, interagir com segurança com o utilizador ou o ambiente e conhecendo a capacidade de armazenagem de energia por parte de elementos elásticos passivos, um sistema de amortecimento-mola demonstra ser uma aplicação de crescente interesse na Robótica. Este trabalho visa a elaboração de um modelo tridimensional eficiente e preciso das pernas do robô quadrúpede Bioloid a ser reproduzido num mundo no software WebotsTM desenvolvido pela Cyberbotics Ltd. O objectivo foi desenhar uma perna pantográfica segmentada tridimensional a ser aplicada em paralelo com um sistema de amortecimento-mola de forma a retrair activamente a colisão e o impacto das patas do quadrúpede com o solo durante a locomoção. Deste modo para uma configuração do modelo bem sucedida são tidos em conta limites geométricos e mecânicos. Por ultimo, o controlador com base no uso de ‘Central Pattern Generators’ foi melhorado a fim de se adaptar ao novo modelo e por conseguinte foram realizados testes simples usando o simulador WebotsTM. Nesta parte experimental é realizada a simulação do modelo permitindo avaliar o comportamento do modelo 3D para diferentes valores de coeficientes de mola e de amortecimento aplicados a nível do joelho da perna. Através de um algoritmo MATLAB® é possível caracterizar e analisar o comportamento doa ângulos das juntas durante a simulação

Locomotion and pose estimation in compliant, torque-controlled hexapedal robots

Several scenarios, such as disaster response or terrestrial and extra-terrestrial exploration, comprise environments that are dangerous or even inaccessible for humans. In those cases, autonomous robots pose a promising alternative to render such endeavours possible. While most of today’s robotic explorers are wheeled or tracked vehicles, legged systems gained increased attention in recent years. With their unique combination of omnidirectional mobility and intrinsic manipulation capabilities, they are envisioned to serve as the rough terrain specialists in scouting or sample and return missions. Especially, small to mid-size hexapods are of great interest for those scenarios. Providing static stability across a wide range of walking speeds, they offer an attractive trade-off between versatility and complexity. Another important advantage is their redundancy, allowing them to tolerate the loss of single legs. However, due to their small size, the computational on-board resources are limited. Thus, the use of smart and efficient algorithms is of utmost importance in order to enable autonomous operation within a priori unknown rough environments. Working towards such autonomous robotic scouts, this thesis contributes with the development, implementation, and test of a self-contained walking layer as well as a 6 degrees of freedom (DOF) leg odometry for compliant, torque-controlled, hexapedal robots. Herein, the important property of all presented algorithms is the sole use of proprioceptive measurements provided by the legs, i. e. joint angles and joint torques. Especially the joint torque sensors improve the walking process by enabling the use of sensitive compliance controllers and distributed collision detection. Comprising a set of algorithms, the walking layer organises and structures the walking process in order to generate robust, adaptive, and leg loss tolerant locomotion in uneven terrain. Furthermore, it encapsulates the walking process, and thus hides its complexity from higher-level algorithms such as navigation. Its three main functional components are a flexible, biologically-inspired gait coordination algorithm, single leg reflexes, and active joint compliance control. Thereof, the gait coordination algorithm realises temporal adaptation of the step sequence while reflexes adjust the leg trajectories to the local terrain. The joint compliance control reduces internal forces and allows for situation dependent stiffness adjustments. An algorithmic extensions to the basic gait coordination enables the immediate adaptation to leg loss. In combination with stiffness and pose adjustments, this allows the hexapod to retain stable locomotion on five legs. In order to account for the emerging gait, the leg odometry algorithm employs an optimisation approach to obtain a kinematics-based pose estimate from joint angle measurements. Fusing the resulting pitch and roll angle estimates with joint-torque-measurement-based attitude data, reduces the associated drift, and thus stabilises the overall pose estimate. Various simulations and experiments with the six-legged, torque-controlled DLR Crawler demonstrate the effectiveness of the proposed walking layer as well as the 6-DOF leg odometry.Für die planetare Exploration sowie den Einsatz in Katastrophengebieten sind autonome Laufroboter zunehmend von Interesse. In diesen Szenarien sollen sie den Menschen an gefährlichen oder schwer zugänglichen Orten ersetzen und dort Erkundungseinsätze sowie Probenahmen in schwierigem Gelände durchführen. Unter der Vielzahl an möglichen Systemen bieten im Besonderen kleinere Sechsbeiner einen sehr guten Kompromiss zwischen Stabilität, hoher Beweglichkeit, Vielseitigkeit und einer vertretbaren Komplexität der Regelung. Ein weiterer Vorteil ist ihre Redundanz, die es ihnen erlaubt, den Ausfall einzelner Beine mit geringem Aufwand zu kompensieren. Dementgegen ist die beschränkte Rechenkapazität ein Nachteil der reduzierten Größe. Um diesen auszugleichen und das autonome Agieren in einer unbekannten Umgebung zu ermöglichen, werden daher einfache und effiziente Algorithmen benötigt, die im Zusammenspiel jedoch ein komplexes Verhalten erzeugen. Auf dem Weg zum autonom explorierenden Laufroboter entwickelt diese Arbeit einen robusten, adaptiven und fehlertoleranten Laufalgorithmus sowie eine 6D Eigenbewegungsschätzung für nachgiebige, drehmomentgeregelte Sechsbeiner. Besonders herauszustellen ist, dass alle in der Arbeit vorgestellten Algorithmen ausschließlich die propriozeptive Sensorik der Beine verwenden. Durch diesen Ansatz kann der Laufprozess von anderen Prozessen, wie der Navigation, getrennt und somit der Datenaustausch effizient gestaltet werden. Für die Fortbewegung in unebenem Gelände kombiniert der vorgestellte Laufalgorithmus eine flexible, biologisch inspirierte Gangkoordination mit verschiedenen Einzelbeinreflexen und einer nachgiebigen Gelenkregelung. Hierbei übernimmt die Gangkoordination die zeitliche Steuerung der Schrittfolge, während die Einzelbeinreflexe für eine räumliche Variation der Fußtrajektorien zuständig sind. Die nachgiebige Gelenkregelung reduziert interne Kräfte und erlaubt eine Anpassung der Gelenksteifigkeiten an die lokalen Umgebungsbedingungen sowie den aktuellen Zustand des Roboters. Eine wichtige Eigenschaft des Laufalgorithmus ist seine Fähigkeit, den Ausfall einzelner Beine zu kompensieren. In diesem Fall erfolgt eine Adaption der Gangkoordination über die Erneuerung der Nachbarschaftsbeziehungen der Beine. Zusätzlich verbessern eine Veränderung der Pose und eine Erhöhung der Gelenksteifigkeiten die Stabilität des durch den Beinverlust beeinträchtigten Roboters. Gleich dem Laufalgorithmus verwendet die 6D Eigenbewegungsschätzung nur die Messungen der propriozeptiven Sensoren der Beine. Hierbei arbeitet der Algorithmus in einem dreistufigen Verfahren. Zuerst berechnet er mit Hilfe der Beinkinematik und einer Optimierung die Pose des Roboters. Nachfolgend bestimmt er aus den Gelenkmomentmessungen den Gravitationsvektor und berechnet daraus die Neigungswinkel des Systems. Eine Fusion dieser Werte mit den Nick- und Rollwinkeln der ersten Stufe stabilisiert daraufhin die gesamte Odometrie und reduziert deren Drift. Alle in dieser Arbeit entwickelten Algorithmen wurden mit Hilfe von Simulationen sowie Experimenten mit dem drehmomentgeregelten DLR Krabbler erfolgreich validiert

System Design, Motion Modelling and Planning for a Recon figurable Wheeled Mobile Robot

Over the past ve decades the use of mobile robotic rovers to perform in-situ scienti c investigations on the surfaces of the Moon and Mars has been tremendously in uential in shaping our understanding of these extraterrestrial environments. As robotic missions have evolved there has been a greater desire to explore more unstructured terrain. This has exposed mobility limitations with conventional rover designs such as getting stuck in soft soil or simply not being able to access rugged terrain. Increased mobility and terrain traversability are key requirements when considering designs for next generation planetary rovers. Coupled with these requirements is the need to autonomously navigate unstructured terrain by taking full advantage of increased mobility. To address these issues, a high degree-of-freedom recon gurable platform that is capable of energy intensive legged locomotion in obstacle-rich terrain as well as wheeled locomotion in benign terrain is proposed. The complexities of the planning task that considers the high degree-of-freedom state space of this platform are considerable. A variant of asymptotically optimal sampling-based planners that exploits the presence of dominant sub-spaces within a recon gurable mobile robot's kinematic structure is proposed to increase path quality and ensure platform safety. The contributions of this thesis include: the design and implementation of a highly mobile planetary analogue rover; motion modelling of the platform to enable novel locomotion modes, along with experimental validation of each of these capabilities; the sampling-based HBFMT* planner that hierarchically considers sub-spaces to better guide search of the complete state space; and experimental validation of the planner with the physical platform that demonstrates how the planner exploits the robot's capabilities to uidly transition between various physical geometric con gurations and wheeled/legged locomotion modes

Optimization-based control and planning for highly dynamic legged locomotion in complex environments

Legged animals can dynamically traverse unstructured environments in an elegant and efficient manner, whether it be running down a steep hill or leaping between branches. To harness part of the animal agility to the legged robot would unlock potential applications such as disaster response and planetary exploration. The unique challenge of these tasks is that the robot has to produce highly dynamic maneuvers in complex environments with minimum human guidance. This thesis explores how an optimization-based method can be applied in the control and planning of highly dynamic legged motions to address the locomotion problem in complex environments. Specifically, this work first describes the design synthesis of a small and agile quadrupedal robot \panther. Based on the quadruped platform, we developed a model predictive control (MPC) control framework to realize complex 3D acrobatic motions without resorting to switching among controllers. We present the MPC formulation that directly uses the rotation matrix, which avoids the singularity issue associated with Euler angles. Motion planning algorithms are developed for planar-legged robot traversing challenging terrains. Dynamic trajectories that simultaneously reason about contact, centroidal dynamics, and joint torque limit are obtained by solving mixed-integer convex programs (MICP) without requiring any initial guess from the operator. We further reduce the computational expense of long-horizon planning by leveraging the benefits of both optimization and sampling-based approaches for a simple legged robot. Finally, we present experimental results for each topic on legged robot hardware to validate the proposed method. It is our hope that the results presented in this thesis will eventually enable legged robots to achieve mobility autonomy at the level of biological systems