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

A generalized laser simulator algorithm for optimal path planning in constraints environment

Path planning plays a vital role in autonomous mobile robot navigation, and it has thus become one of the most studied areas in robotics. Path planning refers to a robot's search for a collision-free and optimal path from a start point to a predefined goal position in a given environment. This research focuses on developing a novel path planning algorithm, called Generalized Laser Simulator (GLS), to solve the path planning problem of mobile robots in a constrained environment. This approach allows finding the path for a mobile robot while avoiding obstacles, searching for a goal, considering some constraints and finding an optimal path during the robot movement in both known and unknown environments. The feasible path is determined between the start and goal positions by generating a wave of points in all directions towards the goal point with adhering to constraints. A simulation study employing the proposed approach is applied to the grid map settings to determine a collision-free path from the start to goal positions. First, the grid mapping of the robot's workspace environment is constructed, and then the borders of the workspace environment are detected based on the new proposed function. This function guides the robot to move toward the desired goal. Two concepts have been implemented to find the best candidate point to move next: minimum distance to goal and maximum index distance to the boundary, integrated by negative probability to sort out the most preferred point for the robot trajectory determination. In order to construct an optimal collision-free path, an optimization step was included to find out the minimum distance within the candidate points that have been determined by GLS while adhering to particular constraint's rules and avoiding obstacles. The proposed algorithm will switch its working pattern based on the goal minimum and boundary maximum index distances. For static obstacle avoidance, the boundaries of the obstacle(s) are considered borders of the environment. However, the algorithm detects obstacles as a new border in dynamic obstacles once it occurs in front of the GLS waves. The proposed method has been tested in several test environments with different degrees of complexity. Twenty different arbitrary environments are categorized into four: Simple, complex, narrow, and maze, with five test environments in each. The results demonstrated that the proposed method could generate an optimal collision-free path. Moreover, the proposed algorithm result are compared to some common algorithms such as the A* algorithm, Probabilistic Road Map, RRT, Bi-directional RRT, and Laser Simulator algorithm to demonstrate its effectiveness. The suggested algorithm outperforms the competition in terms of improving path cost, smoothness, and search time. A statistical test was used to demonstrate the efficiency of the proposed algorithm over the compared methods. The GLS is 7.8 and 5.5 times faster than A* and LS, respectively, generating a path 1.2 and 1.5 times shorter than A* and LS. The mean value of the path cost achieved by the proposed approach is 4% and 15% lower than PRM and RRT, respectively. The mean path cost generated by the LS algorithm, on the other hand, is 14% higher than that generated by the PRM. Finally, to verify the performance of the developed method for generating a collision-free path, experimental studies were carried out using an existing WMR platform in labs and roads. The experimental work investigates complete autonomous WMR path planning in the lab and road environments using live video streaming. The local maps were built using data from live video streaming s by real-time image processing to detect the segments of the lab and road environments. The image processing includes several operations to apply GLS on the prepared local map. The proposed algorithm generates the path within the prepared local map to find the path between start-to-goal positions to avoid obstacles and adhere to constraints. The experimental test shows that the proposed method can generate the shortest path and best smooth trajectory from start to goal points in comparison with the laser simulator

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

An overview on structural health monitoring: From the current state-of-the-art to new bio-inspired sensing paradigms

In the last decades, the field of structural health monitoring (SHM) has grown exponentially. Yet, several technical constraints persist, which are preventing full realization of its potential. To upgrade current state-of-the-art technologies, researchers have started to look at nature’s creations giving rise to a new field called ‘biomimetics’, which operates across the border between living and non-living systems. The highly optimised and time-tested performance of biological assemblies keeps on inspiring the development of bio-inspired artificial counterparts that can potentially outperform conventional systems. After a critical appraisal on the current status of SHM, this paper presents a review of selected works related to neural, cochlea and immune-inspired algorithms implemented in the field of SHM, including a brief survey of the advancements of bio-inspired sensor technology for the purpose of SHM. In parallel to this engineering progress, a more in-depth understanding of the most suitable biological patterns to be transferred into multimodal SHM systems is fundamental to foster new scientific breakthroughs. Hence, grounded in the dissection of three selected human biological systems, a framework for new bio-inspired sensing paradigms aimed at guiding the identification of tailored attributes to transplant from nature to SHM is outlined.info:eu-repo/semantics/acceptedVersio

An Approach Based on Particle Swarm Optimization for Inspection of Spacecraft Hulls by a Swarm of Miniaturized Robots

The remoteness and hazards that are inherent to the operating environments of space infrastructures promote their need for automated robotic inspection. In particular, micrometeoroid and orbital debris impact and structural fatigue are common sources of damage to spacecraft hulls. Vibration sensing has been used to detect structural damage in spacecraft hulls as well as in structural health monitoring practices in industry by deploying static sensors. In this paper, we propose using a swarm of miniaturized vibration-sensing mobile robots realizing a network of mobile sensors. We present a distributed inspection algorithm based on the bio-inspired particle swarm optimization and evolutionary algorithm niching techniques to deliver the task of enumeration and localization of an a priori unknown number of vibration sources on a simplified 2.5D spacecraft surface. Our algorithm is deployed on a swarm of simulated cm-scale wheeled robots. These are guided in their inspection task by sensing vibrations arising from failure points on the surface which are detected by on-board accelerometers. We study three performance metrics: (1) proximity of the localized sources to the ground truth locations, (2) time to localize each source, and (3) time to finish the inspection task given a 75% inspection coverage threshold. We find that our swarm is able to successfully localize the present so

Mechatronic Systems

Mechatronics, the synergistic blend of mechanics, electronics, and computer science, has evolved over the past twenty five years, leading to a novel stage of engineering design. By integrating the best design practices with the most advanced technologies, mechatronics aims at realizing high-quality products, guaranteeing at the same time a substantial reduction of time and costs of manufacturing. Mechatronic systems are manifold and range from machine components, motion generators, and power producing machines to more complex devices, such as robotic systems and transportation vehicles. With its twenty chapters, which collect contributions from many researchers worldwide, this book provides an excellent survey of recent work in the field of mechatronics with applications in various fields, like robotics, medical and assistive technology, human-machine interaction, unmanned vehicles, manufacturing, and education. We would like to thank all the authors who have invested a great deal of time to write such interesting chapters, which we are sure will be valuable to the readers. Chapters 1 to 6 deal with applications of mechatronics for the development of robotic systems. Medical and assistive technologies and human-machine interaction systems are the topic of chapters 7 to 13.Chapters 14 and 15 concern mechatronic systems for autonomous vehicles. Chapters 16-19 deal with mechatronics in manufacturing contexts. Chapter 20 concludes the book, describing a method for the installation of mechatronics education in schools

An approach for real-time motion planning of an inchworm robot in complex steel bridge environments

© Cambridge University Press 2016. Path planning can be difficult and time consuming for inchworm robots especially when operating in complex 3D environments such as steel bridges. Confined areas may prevent a robot from extensively searching the environment by limiting its mobility. An approach for real-time path planning is presented. This approach first uses the concept of line-of-sight (LoS) to find waypoints from the start pose to the end node. It then plans smooth, collision-free motion for a robot to move between waypoints using a 3D-F2 algorithm. Extensive simulations and experiments are conducted in 2D and 3D scenarios to verify the approach

A review: On path planning strategies for navigation of mobile robot

This paper presents the rigorous study of mobile robot navigation techniques used so far. The step by step investigations of classical and reactive approaches are made here to understand the development of path planning strategies in various environmental conditions and to identify research gap. The classical approaches such as cell decomposition (CD), roadmap approach (RA), artificial potential field (APF); reactive approaches such as genetic algorithm (GA), fuzzy logic (FL), neural network (NN), firefly algorithm (FA), particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization (BFO), artificial bee colony (ABC), cuckoo search (CS), shuffled frog leaping algorithm (SFLA) and other miscellaneous algorithms (OMA) are considered for study. The navigation over static and dynamic condition is analyzed (for single and multiple robot systems) and it has been observed that the reactive approaches are more robust and perform well in all terrain when compared to classical approaches. It is also observed that the reactive approaches are used to improve the performance of the classical approaches as a hybrid algorithm. Hence, reactive approaches are more popular and widely used for path planning of mobile robot. The paper concludes with tabular data and charts comparing the frequency of individual navigational strategies which can be used for specific application in robotics

Towards Fault Diagnosis in Reconfigurable Robot

東京電機大学201