Diseño y construcción de un robot tipo serpiente que implementa movimientos de marcha rectilínea y sidewinding

Bio-inspired robots offer locomotion versatility in a wide variety of terrains that conventional robots cannot access.  One such bio-inspired platform is snake-like robots, which are mechanisms designed to move like biological snakes. The aim of this paper was to implement and validate, through comparison in real and simulation tests on flat terrain, the design of a snake robot that allows movements in two perpendicular planes, by the application of three-dimensional locomotion modes. The prototype robot had a modular and sequential architecture composed of eight 3D printed segments. The necessary torques for each motor are found by means of a simulation in Matlab – Simulink and the SimScape tool. The Webots mobile robotics simulator was used to create a parameterized virtual model of the robot, where two types of gaits were programmed: sidewinding and rectilinear. Results showed that the robot undertakes lower than 1 second in execution time to reach the total distance in each of the proposed marches when comparted to the simulation. In addition, mean differences of 6 cm for the distances during the sidewinding mode experiment and 1.2 cm in the deviation in the rectilinear mode on flat terrain were obtained. In conclusion, there is a great similarity between the simulation tests and those performed with the actual robot, and it was also possible to verify that the behavior of the prototype robot is satisfactory over short distances.Los robots bioinspirados ofrecen versatilidad de locomoción en una amplia variedad de terrenos a los que los robots convencionales no pueden acceder. Una de esas plataformas bioinspiradas son los robots con forma de serpiente, que son mecanismos diseñados para moverse como serpientes biológicas. El objetivo de este artículo fue implementar y validar, mediante la comparación en pruebas reales y de simulación sobre un terreno llano, el diseño de un robot serpiente que permite movimientos en dos planos perpendiculares mediante la aplicación de modos tridimensionales de locomoción. El prototipo del robot contó con una arquitectura modular y secuencial compuesto por ocho segmentos impresos en 3D. Los pares necesarios para cada motor se encuentran mediante una simulación en Matlab – Simulink y la herramienta SimScape. El simulador de robótica móvil Webots se utilizó para crear un modelo virtual parametrizado del robot, donde se programaron dos tipos de marcha: sidewinding y rectilínea. Los resultados mostraron que el comportamiento del robot evidencia valores menores a 1 segundo en el tiempo de ejecución para alcanzar la distancia total en cada una de las marchas propuestas en comparación con la simulación. Además, se obtuvieron diferencias en promedio de 6 cm para las distancias durante el experimento del modo sidewinding y de 1.2 cm en el desvió rectilíneo sobre un terreno plano. En conclusión, existe una gran similitud entre las pruebas de simulación y las realizadas al robot real; igualmente se pudo verificar que el comportamiento del prototipo del robot es satisfactorio en recorridos cortos

Heterogeneous Self-Reconfiguring Robotics: Ph.D. Thesis Proposal

Self-reconfiguring robots are modular systems that can change shape, or reconfigure, to match structure to task. They comprise many small, discrete, often identical modules that connect together and that are minimally actuated. Global shape transformation is achieved by composing local motions. Systems with a single module type, known as homogeneous systems, gain fault tolerance, robustness and low production cost from module interchangeability. However, we are interested in heterogeneous systems, which include multiple types of modules such as those with sensors, batteries or wheels. We believe that heterogeneous systems offer the same benefits as homogeneous systems with the added ability to match not only structure to task, but also capability to task. Although significant results have been achieved in understanding homogeneous systems, research in heterogeneous systems is challenging as key algorithmic issues remain unexplored. We propose in this thesis to investigate questions in four main areas: 1) how to classify heterogeneous systems, 2) how to develop efficient heterogeneous reconfiguration algorithms with desired characteristics, 3) how to characterize the complexity of key algorithmic problems, and 4) how to apply these heterogeneous algorithms to perform useful new tasks in simulation and in the physical world. Our goal is to develop an algorithmic basis for heterogeneous systems. This has theoretical significance in that it addresses a major open problem in the field, and practical significance in providing self-reconfiguring robots with increased capabilities

Autonomous Task-Based Evolutionary Design of Modular Robots

In an attempt to solve the problem of finding a set of multiple unique modular robotic designs that can be constructed using a given repertoire of modules to perform a specific task, a novel synthesis framework is introduced based on design optimization concepts and evolutionary algorithms to search for the optimal design. Designing modular robotic systems faces two main challenges: the lack of basic rules of thumb and design bias introduced by human designers. The space of possible designs cannot be easily grasped by human designers especially for new tasks or tasks that are not fully understood by designers. Therefore, evolutionary computation is employed to design modular robots autonomously. Evolutionary algorithms can efficiently handle problems with discrete search spaces and solutions of variable sizes as these algorithms offer feasible robustness to local minima in the search space; and they can be parallelized easily to reducing system runtime. Moreover, they do not have to make assumptions about the solution form. This dissertation proposes a novel autonomous system for task-based modular robotic design based on evolutionary algorithms to search for the optimal design. The introduced system offers a flexible synthesis algorithm that can accommodate to different task-based design needs and can be applied to different modular shapes to produce homogenous modular robots. The proposed system uses a new representation for modular robotic assembly configuration based on graph theory and Assembly Incidence Matrix (AIM), in order to enable efficient and extendible task-based design of modular robots that can take input modules of different geometries and Degrees Of Freedom (DOFs). Robotic simulation is a powerful tool for saving time and money when designing robots as it provides an accurate method of assessing robotic adequacy to accomplish a specific task. Furthermore, it is difficult to predict robotic performance without simulation. Thus, simulation is used in this research to evaluate the robotic designs by measuring the fitness of the evolved robots, while incorporating the environmental features and robotic hardware constraints. Results are illustrated for a number of benchmark problems. The results presented a significant advance in robotic design automation state of the art

Modular Self-Reconfigurable Robot Systems

The field of modular self-reconfigurable robotic systems addresses the design, fabrication, motion planning, and control of autonomous kinematic machines with variable morphology. Modular self-reconfigurable systems have the promise of making significant technological advances to the field of robotics in general. Their promise of high versatility, high value, and high robustness may lead to a radical change in automation. Currently, a number of researchers have been addressing many of the challenges. While some progress has been made, it is clear that many challenges still exist. By illustrating several of the outstanding issues as grand challenges that have been collaboratively written by a large number of researchers in this field, this article has shown several of the key directions for the future of this growing fiel

Configuration Recognition, Communication Fault Tolerance and Self-reassembly for the CKBot

We present and experimentally verify novel methods for increasing the generality of control, autonomy and reliability for modular robotic systems. In particular, we demonstrate configuration recognition, distributed communication fault tolerance, and the organization and control of self-reassembly with the Connector Kinetic roBot (CKBot). The primary contribution of this work is the presentation and experimental verification of these innovative methods that are general and applicable to other modular robotic systems. We describe our CKBot system and compare it to other similar, state-of-the-art modular robotic systems. Our description and comparison highlights various design developments, features, and notable achievements of these systems. We present work on isomorphic configuration recognition with CKBot. Here, we utilize basic principles from graph theory to create and implement an algorithm on CKBot that automatically recognizes modular robot configurations. In particular, we describe how comparing graph spectra of configuration matrices can be used to find a permutation matrix that maps a given configuration to a known one. If a configuration is matched to one in a library of stored gaits, a permutation mapping is applied and the corresponding coordinated control for locomotion is executed. An implementation of the matching algorithm with small configurations of CKBot configurations that can be rearranged during runtime is presented. We also present work on a distributed fault-tolerance algorithm used to control CKBot configurations. Here, we use a triple modular redundancy approach for CKBot units to collectively vote on observations and execute commands in the presence of infrared (IR) communication failures. In our implementation, we broadcast infrared signals to modules which collaboratively vote on a majority course of action. Various gait selections for a seven module caterpillar and sixteen module quadruped with faulty subsets of IR receivers have been verified to demonstrate the algorithm\u27s robustness. Lastly, we present work on the communication hierarchy and control state machine for the Self-reassembly After Explosion (SAE) robot. Here, we discuss the interaction and integration of the various sensory inputs and control outputs implemented for camera-guided self-reassembly with CKBot. This section describes the overall communication system and reassembly sequence planning after a group of CKBot clusters is kicked apart