New insights for the design of bionic robots:adaptive motion adjustment strategies during feline landings

Felines have significant advantages in terms of sports energy efficiency and flexibility compared with other animals, especially in terms of jumping and landing. The biomechanical characteristics of a feline (cat) landing from different heights can provide new insights into bionic robot design based on research results and the needs of bionic engineering. The purpose of this work was to investigate the adaptive motion adjustment strategy of the cat landing using a machine learning algorithm and finite element analysis (FEA). In a bionic robot, there are considerations in the design of the mechanical legs. (1) The coordination mechanism of each joint should be adjusted intelligently according to the force at the bottom of each mechanical leg. Specifically, with the increase in force at the bottom of the mechanical leg, the main joint bearing the impact load gradually shifts from the distal joint to the proximal joint; (2) the hardness of the materials located around the center of each joint of the bionic mechanical leg should be strengthened to increase service life; (3) the center of gravity of the robot should be lowered and the robot posture should be kept forward as far as possible to reduce machine wear and improve robot operational accuracy

Theory of Self-maintaining Robots

This thesis proposes a theory for robotic systems that can be fully self-maintaining. The presented design principles focus on functional survival of the robots over long periods of time without human maintenance. Self-maintaining semi-autonomous mobile robots are in great demand in nuclear disposal sites from where their removal for maintenance is undesirable due to their radioactive contamination. Similar are requirements for robots in various defence tasks or space missions. For optimal design, modular solutions are balanced against capabilities to replace smaller components in a robot by itself or by help from another robot. Modules are proposed for the basic platform, which enable self-maintenance within a team of robots helping each other. The primary method of self-maintenance is replacement of malfunctioning modules or components by the robots themselves. Replacement necessitates a robot team’s ability to diagnose and replace malfunctioning modules as needed. Due to their design, these robots still remain manually re-configurable if opportunity arises for human intervention. A system reliability model is developed to describe the new theory. Depending on the system reliability model, the redundancy allocation problem is presented and solved by a multi objective algorithm. Finally, the thesis introduces the self-maintaining process and transfers it to a multi robot task allocation problem with a solution by genetic algorithm

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

Electromechanical Performance of HASEL Actuators: Fundamentals and Applications

Soft robotic systems are well-suited to unstructured, dynamic tasks and environments, but are currently limited by the soft actuators that power them. Most current soft actuators are based on pneumatics or shape-memory alloys, which have issues with efficiency, response speed, and portability. More recently, dielectric elastomer actuators (DEAs) have shown promise, but they have limited material selection, fabrication methods, and modes of actuation. As such, there remains a need for new types of high performance and well-rounded soft actuators. This dissertation focuses on the development and exploration of a new class of soft electrohydraulic actuators called hydraulically amplified self-healing electrostatic (HASEL) actuators. The first part of this dissertation (Chapter 2) presents of a subclass of HASEL actuators called Peano-HASELs that simultaneously introduce a breakthrough materials system based on thermoplastic films as well as a novel contractile mode of actuation. This approach enables industrially-amenable fabrication techniques, vastly expands the usable materials for actuator construction, and results in high performance actuators with fast linear contraction on activation. The second part of this dissertation (Chapter 3) elucidates the fundamentals of the electromechanical coupling that drives HASEL actuators. An analytical model is developed that accurately describes the quasi-static actuation behavior of Peano-HASEL actuators without relying on fitting parameters. Using this model, we identify a theory-driven approach to actuator design, including a roadmap for actuators with drastically improved specific energies. The final section of this dissertation (Chapter 4 and 5) looks towards more integrated and applied designs of HASEL actuators. First, a new type of articulating actuator is presented that integrates both compliant and rigid components. These spider-inspired electrohydraulic soft-actuated (SES) joints demonstrate high torque and high-speed actuation in an independently-addressable multi-joint limb, a bidirectional actuator, and a versatile gripper. Second, a biodegradable materials system is presented for high performance Peano-HASEL actuators that reduce environmental impact. Finally, a new method of capacitive self-sensing is presented that enables inexpensive and compact circuits that use only off-the-shelf and low voltage components. The results presented in this dissertation provide a framework for the development of high-performance actuators that may one day power the next generation of capable soft robots.</p

Hybrid bio-robotics: from the nanoscale to the macroscale

[eng] Hybrid bio-robotics is a discipline that aims at integrating biological entities with synthetic materials to incorporate features from biological systems that have been optimized through millions of years of evolution and are difficult to replicate in current robotic systems. We can find examples of this integration at the nanoscale, in the field of catalytic nano- and micromotors, which are particles able to self-propel due to catalytic reactions happening in their surface. By using enzymes, these nanomotors can achieve motion in a biocompatible manner, finding their main applications in active drug delivery. At the microscale, we can find single-cell bio-swimmers that use the motion capabilities of organisms like bacteria or spermatozoa to transport microparticles or microtubes for targeted therapeutics or bio-film removal. At the macroscale, cardiac or skeletal muscle tissue are used to power small robotic devices that can perform simple actions like crawling, swimming, or gripping, due to the contractions of the muscle cells. This dissertation covers several aspects of these kinds of devices from the nanoscale to the macro-scale, focusing on enzymatically propelled nano- and micromotors and skeletal muscle tissue bio-actuators and bio-robots. On the field of enzymatic nanomotors, there is a need for a better description of their dynamics that, consequently, might help understand their motion mechanisms. Here, we focus on several examples of nano- and micromotors that show complex dynamics and we propose different strategies to analyze their motion. We develop a theoretical framework for the particular case of enzymatic motors with exponentially decreasing speed, which break the assumptions of constant speed of current methods of analysis and need different strategies to characterize their motion. Finally, we consider the case of enzymatic nanomotors moving in complex biological matrices, such as hyaluronic acid, and we study their interactions and the effects of the catalytic reaction using dynamic light scattering, showing that nanomotors with negative surface charge and urease-powered motion present enhanced parameters of diffusion in hyaluronic acid. Moving towards muscle-based robotics, we investigate the application of 3D bioprinting for the bioengineering of skeletal muscle tissue. We demonstrate that this technique can yield well-aligned and functional muscle fibers that can be stimulated with electric pulses. Moreover, we develop and apply a novel co-axial approach to obtain thin and individual muscle fibers that resemble the bundle-like organization of native skeletal muscle tissue. We further exploit the versatility of this technique to print several types of materials in the same process and we fabricate bio-actuators based on skeletal muscle tissue with two soft posts. Due to the deflection of these cantilevers when the tissue contracts upon stimulation, we can measure the generated forces, therefore obtaining a force measurement platform that could be useful for muscle development studies or drug testing. With these applications in mind, we study the adaptability of muscle tissue after applying various exercise protocols based on different stimulation frequencies and different post stiffness, finding an increase of the force generation, especially at medium frequencies, that resembles the response of native tissue. Moreover, we adapt the force measurement platform to be used with human-derived myoblasts and we bioengineer two models of young and aged muscle tissue that could be used for drug testing purposes. As a proof of concept, we analyze the effects of a cosmetic peptide ingredient under development, focusing on the kinematics of high stimulation contractions. Finally, we present the fabrication of a muscle-based bio-robot able to swim by inertial strokes in a liquid interface and a nanocomposite-laden bio-robot that can crawl on a surface. The first bio-robot is thoroughly characterized through mechanical simulations, allowing us to optimize the skeleton, based on a serpentine or spring-like structure. Moreover, we compare the motion of symmetric and asymmetric designs, demonstrating that, although symmetric bio-robots can achieve some motion due to spontaneous symmetry breaking during its self-assembly, asymmetric bio-robots are faster and more consistent in their directionality. The nanocomposite-laden crawling bio-robot consisted of embedded piezoelectric boron nitride nanotubes that improved the differentiation of the muscle tissue due to a feedback loop of piezoelectric effect activated by the same spontaneous contractions of the tissue. We find that bio-robots with those nanocomposites achieve faster motion and stronger force outputs, demonstrating the beneficial effects in their differentiation. This research presented in this thesis contributes to the development of the field of bio-hybrid robotic devices. On enzymatically propelled nano- and micromotors, the novel theoretical framework and the results regarding the interaction of nanomotors with complex media might offer useful fundamental knowledge for future biomedical applications of these systems. The bioengineering approaches developed to fabricate murine- or human-based bio-actuators might find applications in drug screening or to model heterogeneous muscle diseases in biomedicine using the patient’s own cells. Finally, the fabrication of bio-hybrid swimmers and nanocomposite crawlers will help understand and improve the swimming motion of these devices, as well as pave the way towards the use of nanocomposite to enhance the performance of future actuators.[spa] La bio-robótica híbrida es una disciplina cuyo objetivo es la integración de entidades biológicas con materiales sintéticos para superar los desafíos existentes en el campo de la robótica blanda, incorporando características de los sistemas biológicos que han sido optimizadas durante millones de años de evolución natural y no son fáciles de reproducir artificialmente. Esta tesis cubre varios aspectos de este tipo de dispositivos desde la nanoescala a la macroescala, enfocándose en nano- y micromotores propulsados enzimáticamente y bio-actuadores y bio-robots basados en tejido muscular esquelético. En el campo de nanomotores enzimáticos, existe la necesidad de encontrar mejores modelos que puedan describir la dinámica de su movimiento para llegar a entender sus mecanismos de propulsión subyacentes. Aquí, nos enfocamos en diversos ejemplos de nano- y micromotores que muestran dinámicas de movimiento complejas y proponemos diferentes estrategias que se pueden utilizar para analizar y caracterizar este movimiento. Moviéndonos hacia robots basados en células musculares, investigamos la aplicación de la técnica de bioimpresión en 3D para la biofabricación de músculo esquelético. Demostramos que esta técnica puede producir fibras musculares funcionales y bien alineadas que puede ser estimuladas y contraerse con pulsos eléctricos. Investigamos la versatilidad de esta técnica para imprimir varios tipos de materiales en el mismo proceso y fabricamos bio-actuadores basados en músculo esquelético. Debido a los movimientos de unos postes gracias a las contracciones musculares, podemos obtener medidas de la fuerza ejercida, obteniendo una plataforma de medición de fuerzas que podría ser de utilidad para estudios sobre el desarrollo del músculo o para testeo de fármacos. Finalmente, presentamos la fabricación de un bio-robot basado en músculo esquelético capaz de nadar en la superficie de un líquido y un bio-robot con nanocompuestos incrustados que puede arrastrarse por una superficie sólida. El primer de ellos es minuciosamente caracterizado a través de simulaciones mecánicas, permitiéndonos optimizar su esqueleto, basado en una estructura tipo serpentina o muelle. El segundo bio-robot contiene nanotubos piezoeléctricos incrustados en su tejido, los cuales ayudan en la diferenciación del músculo debido a una retroalimentación basada en su efecto piezoeléctrico y activada por las contracciones espontáneas del tejido. Mostramos que estos bio-robots pueden generar un movimiento más rápido y una mayor generación de fuerza, demostrando los efectos beneficiales en la diferenciación del tejido

Aisimam - An Artificial immune system based intelligent multiangent model

The goal of this thesis is to develop a biological model for multiagent systems. This thesis explores artificial immune systems, a novel evolutionary paradigm based on the immunological principles. Artificial Immune systems (AIS) are found to be powerful to solve complex computational tasks. The main focus of the thesis is to develop a generic mathematical model that uses the principles of the human immune system in multiagent systems (MAS). The components and properties of the human immune system are studied. On understanding the concepts of A/5, a literature survey of multiagent systems is performed to understand and compare the multiagent concepts and AIS concepts. An analogy between the immune system parameters and the agent theory was derived. Then, an intelligent multiagent model named AISIMAM is derived. It exploits several properties and features of the immune system in multiagent systems. In other words, the intelligence of the immune systems to kill the antigen and the characteristics of the agents are combined in the model. The model is expressed in terms of mathematical expressions. The model is applied to a specific application namely the mine detection and defusion. The simulations are done in MATLAB that runs on a PC. The experimental results of AISIMAM applied to the mine detection problem are discussed. The results are successful and shows that AISIMAM could be an alternative solution to agent based problems. Artificial Immune System is also applied to a pattern recognition problem. The problem experimented is a color image classification problem useful in a real time industrial application. The images are those of wooden components that need to be classified according to the color and type of wood. To solve the classification task, a simple negative selection and genetic algorithm based A/5 algorithm was developed and simulated. The results are compared with the radial basis function approach applied to the same set of input images

An analysis of the locomotory behaviour and functional morphology of errant polychaetes

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Development, evolution and genetic analysis of C. elegans-inspired foraging algorithms under different environmental conditions

In this work 3 minimalist bio-inspired foraging algorithms based on C. elegans’ chemotaxis and foraging behaviour were developed and investigated. The main goal of the work is to apply the algorithms to robots with limited sensing capabilities. The refined versions of these algorithms were developed and optimised in 22 different environments. The results were processed using a novel set of techniques presented here, named Genotype Clustering. The results lead to two distinct conclusions, one practical and one more academic. From a practical perspective, the results suggest that, when suitably tuned, minimalist C. elegans-inspired foraging algorithms can lead to effective navigation to unknown targets even in the presence of repellents and under the influence of a significant sensor noise. From an academic perspective, the work demonstrates that even simple models can serve as an interesting and informative testbed for exploring fundamental evolutionary principles. The simulated robots were grounded in real hardware parameters, aiming at future application of the foraging algorithms in real robots. Another achievement of the project was the development of the simulation framework that provides a simple yet flexible program for the development and optimisation of behavioural algorithms

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Autonomy in the real real-world: A behaviour based view of autonomous systems control in an industrial product inspection system

The thesis presented in this dissertation appears in two sequential parts that arose from an exploration of the use of Behaviour Based Artificial Intelligence (BBAI) techniques in a domain outside that of robotics, where BBAI is most frequently used. The work details a real-world physical implementation of the control and interactions of an industrial product inspection system from a BBAI perspective. It concentrates particularly on the control of a number of active laser scanning sensor systems (each a subsystem of a larger main inspection system), using a subsumption architecture. This industrial implementation is in itself a new direction for BBAI control and an important aspect of this thesis. However, the work has also led on to the development of a number of key ideas which contribute to the field of BBAI in general. The second part of the thesis concerns the nature of physical and temporal constraints on a distributed control system and the desirability of utilising mechanisms to provide continuous, low-level learning and adaptation of domain knowledge on a sub-behavioural basis. Techniques used include artificial neural networks and hill-climbing state-space search algorithms. Discussion is supported with examples from experiments with the laser scanning inspection system. Encouraging results suggest that concerted design effort at this low level of activity will benefit the whole system in terms of behavioural robustness and reliability. Relevant aspects of the design process that should be of value in similar real-world projects are identified and emphasised. These issues are particularly important in providing a firm foundation for artificial intelligence based control systems