Swimming direction reversal of flagella through ciliary motion of mastigonemes.

Bio-inspired designs can provide an answer to engineering problems such as swimming strategies at the micron or nano-scale. Scientists are now designing artificial micro-swimmers that can mimic flagella-powered swimming of micro-organisms. In an application such as lab-on-a-chip in which micro-object manipulation in small flow geometries could be achieved by micro-swimmers, control of the swimming direction becomes an important aspect for retrieval and control of the micro-swimmer. A bio-inspired approach for swimming direction reversal (a flagellum bearing mastigonemes) can be used to design such a system and is being explored in the present work. We analyze the system using a computational framework in which the equations of solid mechanics and fluid dynamics are solved simultaneously. The fluid dynamics of Stokes flow is represented by a 2D Stokeslets approach while the solid mechanics behavior is realized using Euler-Bernoulli beam elements. The working principle of a flagellum bearing mastigonemes can be broken up into two parts: (1) the contribution of the base flagellum and (2) the contribution of mastigonemes, which act like cilia. These contributions are counteractive, and the net motion (velocity and direction) is a superposition of the two. In the present work, we also perform a dimensional analysis to understand the underlying physics associated with the system parameters such as the height of the mastigonemes, the number of mastigonemes, the flagellar wave length and amplitude, the flagellum length, and mastigonemes rigidity. Our results provide fundamental physical insight on the swimming of a flagellum with mastigonemes, and it provides guidelines for the design of artificial flagellar systems.

Resonance based multi-gaited robot locomotion

In order to understand the underlying mechanisms of animals' agility, dexterity and efficiency in motor control, there has been an increasing interest in the study of gait patterns in biological and artificial legged systems. This paper presents a novel approach to the study of gait patterns which makes use of intrinsic mechanical dynamics of robotic systems. Each of these robots consists of a U-shape elastic beam and exploits free vibration to generate different gait patterns. We developed a conceptual model for these robots, and through simulation and real-world experiments, we show three distinct mechanisms for generating four different gait patterns in these robots. © 2012 IEEE.

Finding resonance: Adaptive frequency oscillators for dynamic legged locomotion

There is much to gain from providing walking machines with passive dynamics, e.g. by including compliant elements in the structure. These elements can offer interesting properties such as self-stabilization, energy efficiency and simplified control. However, there is still no general design strategy for such robots and their controllers. In particular, the calibration of control parameters is often complicated because of the highly nonlinear behavior of the interactions between passive components and the environment. In this article, we propose an approach in which the calibration of a key parameter of a walking controller, namely its intrinsic frequency, is done automatically. The approach uses adaptive frequency oscillators to automatically tune the intrinsic frequency of the oscillators to the resonant frequency of a compliant quadruped robot The tuning goes beyond simple synchronization and the learned frequency stays in the controller when the robot is put to halt. The controller is model free, robust and simple. Results are presented illustrating how the controller can robustly tune itself to the robot, as well as readapt when the mass of the robot is changed. We also provide an analysis of the convergence of the frequency adaptation for a linearized plant, and show how that analysis is useful for determining which type of sensory feedback must be used for stable convergence. This approach is expected to explain some aspects of developmental processes in biological and artificial adaptive systems that "develop" through the embodied system-environment interactions. © 2006 IEEE.

Introduction to the development of an information management system for soil mix technology using artificial neural networks

This paper introduces current work in collating data from different projects using soil mix technology and establishing trends using artificial neural networks (ANNs). Variation in unconfined compressive strength as a function of selected soil mix variables (e.g., initial soil water content and binder dosage) is observed through the data compiled from completed and on-going soil mixing projects around the world. The potential and feasibility of ANNs in developing predictive models, which take into account a large number of variables, is discussed. The main objective of the work is the management and effective utilization of salient variables and the development of predictive models useful for soil mix technology design. Based on the observed success in the predictions made, this paper suggests that neural network analysis for the prediction of properties of soil mix systems is feasible. © ASCE 2011.

Rationales of holonic manufacturing systems in leather industry

This paper presents an insight into leather manufacturing processes, depicting peculiarities and challenges faced by leather industry. An analysis of this industry reveals the need for a new approach to optimize the productivity of leather processing operations, ensure consistent quality of leather, mitigate the adverse health effects in tannery workers exposed to chemicals and comply with environmental regulation. Holonic manufacturing systems (HMS) paradigm represent a bottom-up distributed approach that provides stability, adaptability, efficient use of resources and a plug and operate functionality to the manufacturing system. A vision of how HMS might operate in a tannery is illustrated presenting the rationales behind its application in this industry. © 2013 Springer-Verlag.

New robotics: design principles for intelligent systems.

New robotics is an approach to robotics that, in contrast to traditional robotics, employs ideas and principles from biology. While in the traditional approach there are generally accepted methods (e. g., from control theory), designing agents in the new robotics approach is still largely considered an art. In recent years, we have been developing a set of heuristics, or design principles, that on the one hand capture theoretical insights about intelligent (adaptive) behavior, and on the other provide guidance in actually designing and building systems. In this article we provide an overview of all the principles but focus on the principles of ecological balance, which concerns the relation between environment, morphology, materials, and control, and sensory-motor coordination, which concerns self-generated sensory stimulation as the agent interacts with the environment and which is a key to the development of high-level intelligence. As we argue, artificial evolution together with morphogenesis is not only "nice to have" but is in fact a necessary tool for designing embodied agents.