Bioinspired Actuators And Sensors

From experts in engineering and biology, this is the first book to integrate sensor and actuator technology with bioinspired design.

From experts in engineering and biology, this is the first book to integrate sensor and actuator technology with bioinspired design.

This book includes representative research from the state‐of‐the‐art in the emerging field of soft robotics, with a special focus on bioinspired soft robotics for underwater applications. Topics include novel materials, sensors, actuators, and system design for distributed estimation and control of soft robotic appendages inspired by the octopus and seastar. It summarizes the latest findings in an emerging field of bioinspired soft robotics for the underwater domain, primarily drawing from (but not limited to) an ongoing research program in bioinspired autonomous systems sponsored by the Office of Naval Research. The program has stimulated cross‐disciplinary research in biology, material science, computational mechanics, and systems and control for the purpose of creating novel robotic appendages for maritime applications. The book collects recent results in this area.

This book discusses biologically inspired robotic actuators designed to offer improved robot performance and approaching human-like efficiency and versatility. It assesses biological actuation and control in the human motor system, presents a range of technical actuation approaches, and discusses potential applications in wearable robots, i.e., powered prostheses and exoskeletons. Gathering the findings of internationally respected researchers from various fields, the book provides a uniquely broad perspective on bioinspired actuator designs for robotics. Its scope includes fundamental aspects of biomechanics and neuromechanics, actuator and control design, and their application in (wearable) robotics. The book offers PhD students and advanced graduate students an essential introduction to the field, while providing researchers a cutting-edge research perspective.

Chemical sensing is likely the most primordial sensory modality that emerged in the evolution of life. Without chemical sensing life on earth would probably not exist. It is used for detecting nutrients, avoiding threats, finding mating partners and various forms of communication and social interaction between animals. The advent of artificial sensors has created a myriad of problems in the areas of chemical detection and identification with applications in food quality and pollution control, chemical threat detection, health monitoring, robot control and even odor and taste synthesis. Efficient algorithms are needed to address the many challenges of chemical sensing in these areas, including (but not limited to) sensitivity levels, sensor drift, concentration invariance of analyte identity and complex mixtures. Defining and improving analysis methods for artificial chemical sensing remains an active research area in engineering and machine learning alike. In the course of evolution animals, bacteria and plants have developed sophisticated methods and algorithms for solving difficult problems in chemical sensing very efficiently. Complex signalling pathways inside single cells can trigger movement toward the source of a nutrient. Complex networks of neurons appear to be able to compute odor types and the distance to a source in turbulent flows. These networks of neurons use a combination of temporal coding, layered structures, simple Hebbian learning rules, reinforcement learning and inhibition to quickly learn about chemical stimuli that are critical for their survival. Olfaction is a vibrant filed of research because recent technological advances allow monitoring and manipulating brain areas inaccessible in the past thus allowing for rapid progress. This is particularly relevant because to this date the best solutions to many general chemical sensing problems are still found in animals rather than artificial devices. Many lessons may yet have to be learned from biological systems to solve the complex problems of chemical sensing with similar success as animals routinely do. This special issue has the ambitious goal of bringing together biologists and engineers to report on biological solutions and engineering approaches to chemical sensing challenges in order to better understand in what aspects both fields can find common ground of discussion and to thus promote novel areas of interdisciplinary research.

​This book discusses the field of bioinspired smell and taste sensors which includes many new areas: sensitive materials, physiological modelling and simulation, and more. Similar to biological chemical sensing systems, bioinspired smell and taste sensors are characterized with fast responsive, high specificity and sensitivity. One of the most important parts of the field is that of sensitive elements originated from biological components, which enable the detection of chemical signals by mimicking the biological mechanisms. This book detailed describes processing, devices, recognition principles of sensitive materials, and concrete realizations. It is written for researchers, engineers and biologists who engages in interdisciplinary research and applications. Dr. Ping Wang is a professor at Zhejiang University, Hangzhou, China. Dr. Qingjun Liu is a professor at Zhejiang University, Hangzhou, China. Dr. Chunsheng Wu is an associated professor at Zhejiang University, Hangzhou, China. Dr. K. Jimmy Hsia is a professor at University of Illinois at Urbana-Champaign, Urbana, USA.

Eugene Goldfield lays out principles of engineering found in the natural world, with a focus on how components of coordinated structures organize themselves into autonomous functional systems. This self-organizing capacity is one of many qualities which can be harnessed to design technologies that can interact seamlessly with human bodies.

This title explores the potential of bio-inspired materials and sensing systems by describing a conceptual model of distributed intelligent autonomous sensing.