Control of a Snake Robot for Ascending and Descending Steps

This paper proposes control method for a snake robot to ascend and descend steps. In a multiplane step environment, it is necessary for locomotion to transfer from one plane to another. When a snake robot moves, it touches several planes as its body is long and thin. In this paper, we propose a control method to track the trajectory of a snake robot in a step environment. We decomposed the 3-D motion of the robot into two simple models by introducing an assumption that simplifies the model and controller, and derive a model of the robot as a hybrid system with switching. The control method consists of a tracking controller, a method for shifting the robot\u27s part connecting the planes, and active lifting to control the shape of the robot. Ascent and descent experiments confirm the effectiveness of the proposed controller and the method for shifting the connecting part of the robot\u27s body

Mechanical Description of a Hyper-Redundant Robot Joint Mechanism Used for a Design of a Biomimetic Robotic Fish

A biologically inspired robot in the form of fish (mackerel) model using rubber (as the biomimetic material) for its hyper-redundant joint is presented in this paper. Computerized simulation of the most critical part of the model (the peduncle) shows that the rubber joints will be able to take up the stress that will be created. Furthermore, the frequency-induced softening of the rubber used was found to be critical if the joints are going to oscillate at frequency above 25 Hz. The robotic fish was able to attain a speed of 0.985 m/s while the tail beats at a maximum of 1.7 Hz when tested inside water. Furthermore, a minimum turning radius of 0.8 m (approximately 2 times the fish body length) was achieved

Modified serpentine motion of the snake robot

The frequent occurrence of earthquake in New Zealand drives the research on snake robot for search and rescue operation because of its elongated body shape and locomotion mimicry of the biological snake. Both features are in favour of moving the snake robot through the earthquake disaster area. To facilitate the robot control and information gathering, it is usually required to install a camera on the snake robot head so that the video images of the disaster area can be send back to the human operator. This thesis presents the simulation of a snake robot performing serpentine motion. A camera is attached on the snake robot head to obtain the video image along the line of sight. A remote controller is incorporated to control the advancement based on the video images. This simulation reveals that the video images from the camera oscillate seriously because the camera on the snake robot head follows serpenoid curve during the locomotion. As a result, both robot control and information gathering are affected. A solution is proposed to stabilize the snake robot head and its camera by introducing a correction at the joint between the robot head and its body. This correction aligns the camera sight direction with the moving direction of the snake robot to yield satisfactory video images. Finally, an actual snake robot is implemented with a wireless camera installed on the head to show the effect of correction. Experiments are conducted to control the advancement of snake robot remotely just based on the video images obtained from the camera. This greatly improves the performance of the snake robot

A Snake-Inspired Multi-Segmented Magnetic Soft Robot Towards Medical Applications

Magnetically-actuated soft robots have potential for medical application but require further innovation on functionality and biocompatibility. In this letter, a multi-segmented snake-inspired soft robot with dissolvable and hiocompatible segments is designed. The actuation response under external magnetic field is investigated through simulations and experiments. A dissolve-controllable mixture of gelatin, glycerol and water (GGW) in a mass ratio of 1:5:6 is used to form the structure of the robot. The dissolution of GGW in water and mucus is tested. Magnetic cubes made of silicone rubber mixed with ferromagnetic particles are used to achieve snake-like motion under the influence of a rotating magnetic field. The motion of the robot is tested under different magnitudes and frequencies of the magnetic field. The ability of the robot to navigate obstacles, move over ground and under water as well as on the oil-coated surface, dissolve and release a drug is demonstrated through experiments. The combination of multi-segmented design and biocompatible and dissolvable materials illustrates the potential of such robots for medical applications

Motion control of a snake robot moving between two non-parallel planes

A control method that makes the head of a snake robot follow an arbitrary trajectory on two non-parallel planes, including coexisting sloped and flat planes, is presented. We clarify an appropriate condition of contact between the robot and planes and design a controller for the part of the robot connecting the two planes that satisfies the contact condition. Assuming that the contact condition is satisfied, we derive a simplified model of the robot and design a controller for trajectory tracking of the robot’s head. The controller uses kinematic redundancy to avoid violating the limit of the joint angle and a collision between the robot and the edge of a plane. The effectiveness of the proposed method is demonstrated in experiments using an actual robot

Design and Analysis of Exaggerated Rectilinear Gait-Based Snake-Inspired Robots

Snake-inspired locomotion is much more maneuverable compared to conventional locomotion concepts and it enables a robot to navigate through rough terrain. A rectilinear gait is quite flexible and has the following benefits: functionality on a wide variety of terrains, enables a highly stable robot platform, and provides pure undulatory motion without passive wheels. These benefits make rectilinear gaits especially suitable for search and rescue applications. However, previous robot designs utilizing rectilinear gaits were slow in speed and required considerable vertical motion. This dissertation will explore the development and implementation of a new exaggerated rectilinear gait that which will enable high speed locomotion and more efficient operation in a snake-inspired robot platform. The exaggerated rectilinear gait will emulate the natural snake's rectilinear gait to gain the benefit a snake's terrain adaptability, but the sequence and range of joint motion will be greatly exaggerated to achieve higher velocities to support robot speeds within the range of human walking speed. The following issues will be investigated in this dissertation. First, this dissertation will address the challenge of developing a snake-inspired robot capable of executing exaggerated rectilinear gaits. To successfully execute the exaggerated rectilinear gait, a snake-inspired robot platform must be able to perform high speed linear expansion/contraction and pivoting motions between segments. In addition to high speed joint motion, the new mechanical architecture much also incorporate a method for providing positive traction during gait execution. Second, a new exaggerated gait dynamics model will be developed using well established kinematics and dynamics analysis techniques. In addition to the exaggerated rectilinear gaits which emphasize high speed, a set of exaggerated rectilinear gaits which emphasize high traction will also be developed for application on difficult terrain types. Finally, an exaggerated rectilinear that emphasizes energy efficiency is defined and analyzed. This dissertation provides the foundations for realizing a high speed limbless locomotion capable of meeting the needs of the search, rescue, and recovery applications

Locomotion through morphology, evolution and learning for legged and limbless robots

Mención Internacional en el título de doctorRobot locomotion is concerned with providing autonomous locomotion capabilities to mobile robots. Most current day robots feature some form of locomotion for navigating in their environment. Modalities of robot locomotion includes: (i) aerial locomotion, (ii) terrestrial locomotion, and (iii) aquatic locomotion (on or under water). Three main forms of terrestrial locomotion are, legged locomotion, limbless locomotion and wheel-based locomotion. A Modular Robot (MR), on the other hand, is a robotic system composed of several independent unit modules, where, each module is a robot by itself. The objective in this thesis is to develop legged locomotion in a humanoid robot, as well as, limbless locomotion in modular robotic configurations. Taking inspiration from biology, robot locomotion from the perspective of robot’s morphology, through evolution, and through learning are investigated in this thesis. Locomotion is one of the key distinguishing characteristics of a zoological organism. Almost all animal species, and even some plant species, produce some form of locomotion. In the past few years, robots have been “moving out” of the factory floor and research labs, and are becoming increasingly common in everyday life. So, providing stable and agile locomotion capabilities for robots to navigate a wide range of environments becomes pivotal. Developing locomotion in robots through biologically inspired methods, also facilitates furthering our understanding on how biological processes may function. Connected modules in a configuration, exert force on each other as a result of interaction between each other and their environment. This phenomenon is studied and quantified, and then used as implicit communication between robot modules for producing locomotion coordination in MRs. Through this, a strong link between robot morphology and the gait that emerge in it is established. A variety of locomotion controller, some periodic-function based and some morphology based, are developed for MR locomotion and bipedal gait generation. A hybrid Evolutionary Algorithm (EA) is implemented for evolving gaits, both in simulation as well as in the real-world on a physical modular robotic configuration. Limbless gaits in MRs are also learnt by learning optimal control policies, through Reinforcement Learning (RL).En robótica, la locomoción trata de proporcionar capacidades de locomoción autónoma a robots móviles. La mayoría de los robots actuales tiene alguna forma de locomoción para navegar en su entorno. Los modos de locomoción robótica se pueden repartir entre: (i) locomoción aérea, (ii) locomoción terrestre, y (iii) locomoción acuática (sobre o bajo el agua). Las tres formas básicas de locomoción terrestre son la locomoción mediante piernas, la locomoción sin miembros, y la locomoción basada en ruedas. Un Robot Modular, por otra parte, es un sistema robótico compuesto por varios módulos independientes, donde cada módulo es un robot en sí mismo. El objetivo de esta tesis es el desarrollo de la locomoción mediante piernas para un robot humanoide, así como el de la locomoción sin miembros para varias configuraciones de robots modulares. Inspirándose en la biología, también se investiga en esta tesis el desarrollo de la locomoción del robot según su morfología, gracias a técnicas de evolución y de aprendizaje. La locomoción es una de las características distintivas de un organismo zoológico. Casi todas las especies animales, e incluso algunas especies de plantas, poseen algún tipo de locomoción. En los últimos años, los robots han “migrado” desde las fábricas y los laboratorios de investigación, y se están integrando cada vez más en nuestra vida diaria. Por estas razones, es crucial proporcionar capacidades de locomoción estables y ágiles a los robots para que puedan navegar por todo tipo de entornos. El uso de métodos de inspiración biológica para alcanzar esta meta también nos ayuda a entender mejor cómo pueden funcionar los procesos biológicos equivalentes. En una configuración de módulos conectados, puesto que cada uno interacciona con su entorno, los módulos ejercen fuerza los unos sobre los otros. Este fenómeno se ha estudiado y cuantificado, y luego se ha usado como comunicación implícita entre los módulos para producir la coordinación en la locomoción de este robot. De esta manera, se establece un fuerte vínculo entre la morfología de un robot y el modo de andar que este desarrolla. Se han desarrollado varios controladores de locomoción para robots modulares y robots bípedos, algunos basados en funciones periódicas, otros en la morfología del robot. Un algoritmo evolutivo híbrido se ha implementado para la evolución de locomociones, tanto en simulación como en el mundo real en una configuración física de robot modular. También se pueden generar locomociones sin miembros para robots modulares, determinando las políticas de control óptimo gracias a técnicas de aprendizaje por refuerzo. Se presenta en primer lugar en esta tesis el estado del arte de la robótica modular, enfocándose en la locomoción de robots modulares, los controladores, la locomoción bípeda y la computación morfológica. A continuación se describen cinco configuraciones diferentes de robot modular que se utilizan en esta tesis, seguido de cuatro controladores de locomoción. Estos controladores son el controlador heterogéneo, el controlador basado en funciones periódicas, el controlador homogéneo y el controlador basado en la morfología del robot. Se desarrolla como parte de este trabajo un controlador de locomoción lineal, periódico, basado en features, para la locomoción bípeda de robots humanoides. Los parámetros de control se ajustan primero a mano para reproducir un modelo cart-table, y el controlador se evalúa en un robot humanoide simulado. A continuación, gracias a un algoritmo evolutivo, la optimización de los parámetros de control permite desarrollar una locomoción sin modelo predeterminado. Se desarrolla como parte de esta tesis un enfoque sobre algoritmos de Embodied Evolución, en otras palabras el uso de robots modulares físicos en la fase de evolución. La implementación material, la configuración experimental, y el Algoritmo Evolutivo implementado para Embodied Evolución, se explican detalladamente. El trabajo también incluye una visión general de las técnicas de aprendizaje por refuerzo y de los Procesos de Decisión de Markov. A continuación se presenta un algoritmo popular de aprendizaje por refuerzo, llamado Q-Learning, y su adaptación para aprender locomociones de robots modulares. Se proporcionan una implementación del algoritmo de aprendizaje y la evaluación experimental de la locomoción generada.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Antonio Barrientos Cruz.- Secretario: Luis Santiago Garrido Bullón.- Vocal: Giuseppe Carbon

Modular Self-Reconfigurable Robotic Systems: A Survey on Hardware Architectures

Modular self-reconfigurable robots present wide and unique solutions for growing demands in the domains of space exploration, automation, consumer products, and so forth. The higher utilization factor and self-healing capabilities are most demanded traits in robotics for real world applications and modular robotics offer better solutions in these perspectives in relation to traditional robotics. The researchers in robotics domain identified various applications and prototyped numerous robotic models while addressing constraints such as homogeneity, reconfigurability, form factor, and power consumption. The diversified nature of various modular robotic solutions proposed for real world applications and utilization of different sensor and actuator interfacing techniques along with physical model optimizations presents implicit challenges to researchers while identifying and visualizing the merits/demerits of various approaches to a solution. This paper attempts to simplify the comparison of various hardware prototypes by providing a brief study on hardware architectures of modular robots capable of self-healing and reconfiguration along with design techniques adopted in modeling robots, interfacing technologies, and so forth over the past 25 years