Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Opinions and Outlooks on Morphological Computation

Morphological Computation is based on the observation that biological systems seem to carry out relevant computations with their morphology (physical body) in order to successfully interact with their environments. This can be observed in a whole range of systems and at many different scales. It has been studied in animals – e.g., while running, the functionality of coping with impact and slight unevenness in the ground is "delivered" by the shape of the legs and the damped elasticity of the muscle-tendon system – and plants, but it has also been observed at the cellular and even at the molecular level – as seen, for example, in spontaneous self-assembly. The concept of morphological computation has served as an inspirational resource to build bio-inspired robots, design novel approaches for support systems in health care, implement computation with natural systems, but also in art and architecture. As a consequence, the field is highly interdisciplinary, which is also nicely reflected in the wide range of authors that are featured in this e-book. We have contributions from robotics, mechanical engineering, health, architecture, biology, philosophy, and others

Learning locomotion gait through hormone-based controller in modular robots

Modular robots are robots composed of multiple units, called 'modules'. Each module is an independent robot, with its own control electronics, actuators, sensors, communications and power. These modules can change their position and configuration in order to adapt to the requirements of the situation, making modular robot suitable for tasks that involve unknown or unstructured terrains, in which a robot cannot be designed speci cally for them. Some examples of those applications are space exploration, battlefield reconnaissance, finding victims among the debris in natural catastrophes and other similar tasks involving complicated terrains, which require a high versability. But this versability comes with several drawbacks. As modular robots are composed of several independent robots, the nature of their controller is distributed, which difficults their design and programming, requiring additionally a robust communication protocol to share information among modules. The high number of modules also results in a robot with a with number of degrees of freedom, for which achieving the coordination required for locomotion becomes increasingly difficult. Finally, as the modules are fully independent robots, the cost of researching modular robotics is usually very high, since the price of building a single robot has to be multiplied by the high number of modules. This thesis addresses those three mentioned problems: obtaining optimal locomotion gaits from a biologically inspired approach, using sinusoidal oscillators whose parameters are found through evolutionary optimization algorithms; developing a homogenous, distributed controller based on digital hormones that can recognize the current robot configuration and select the proper gait; and the development of a low-cost modular robotic platform to reseach locomotion gaits for different configurations.Ingeniería Electrónica Industrial y Automátic