Natural User Interface for Roombots

Roombots (RB) are self-reconfigurable modular robots designed to study robotic reconfiguration on a structured grid and adaptive locomotion off grid. One of the main goals of this platform is to create adaptive furniture inside living spaces such as homes or offices. To ease the control of RB modules in these environments, we propose a novel and more natural way of interaction with the RB modules on a RB grid, called the Natural Roombots User Interface. In our method, the user commands the RB modules using pointing gestures. The user's body is tracked using multiple Kinects. The user is also given real-time visual feedback of their physical actions and the state of the system via LED illumination electronics installed on both RB modules and the grid. We demonstrate how our interface can be used to efficiently control RB modules on simple point-to-point grid locomotion and conclude by discussing future extensions

Challenges in the Locomotion of Self-Reconfigurable Modular Robots

Self-Reconfigurable Modular Robots (SRMRs) are assemblies of autonomous robotic units, referred to as modules, joined together using active connection mechanisms. By changing the connectivity of these modules, SRMRs are able to deliberately change their own shape in order to adapt to new environmental circumstances. One of the main motivations for the development of SRMRs is that conventional robots are limited in their capabilities by their morphology. The promise of the field of self-reconfigurable modular robotics is to design robots that are robust, self-healing, versatile, multi-purpose, and inexpensive. Despite significant efforts by numerous research groups worldwide, the potential advantages of SRMRs have yet to be realized. A high number of degrees of freedom and connectors make SRMRs more versatile, but also more complex both in terms of mechanical design and control algorithms. Scalability issues affect these robots in terms of hardware, low-level control, and high-level planning. In this thesis we identify and target three major challenges: (i) Hardware design; (ii) Planning and control; and, (iii) Application challenges. To tackle the hardware challenges we redesigned and manufactured the Self-Reconfigurable Modular Robot Roombots to meet desired requirements and characteristics. We explored in detail and improved two major mechanical components of an SRMR: the actuation and the connection mechanisms. We also analyzed the use of compliant extensions to increase locomotion performance in terms of locomotion speed and power consumption. We contributed to the control challenge by developing new methods that allow an arbitrary SRMR structure to learn to locomote in an efficient way. We defined a novel bio-inspired locomotion-learning framework that allows the quick and reliable optimization of new gaits after a morphological change due to self-reconfiguration or human construction. In order to find new suitable application scenarios for SRMRs we envision the use of Roombots modules to create Self-Reconfigurable Robotic Furniture. As a first step towards this vision, we explored the use and control of Plug-n-Play Robotic Elements that can augment existing pieces of furniture and create new functionalities in a household to improve quality of life

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

On the dynamics of human locomotion and co-design of lower limb assistive devices

Recent developments in lower extremities wearable robotic devices for the assistance and rehabilitation of humans suffering from an impairment have led to several successes in the assistance of people who as a result regained a certain form of locomotive capability. Such devices are conventionally designed to be anthropomorphic. They follow the morphology of the human lower limbs. It has been shown previously that non-anthropomorphic designs can lead to increased comfort and better dynamical properties due to the fact that there is more morphological freedom in the design parameters of such a device. At the same time, exploitation of this freedom is not always intuitive and can be difficult to incorporate. In this work we strive towards a methodology aiding in the design of possible non-anthropomorphic structures for the task of human locomotion assistance by means of simulation and optimization. The simulation of such systems requires state of the art rigid body dynamics, contact dynamics and, importantly, closed loop dynamics. Through the course of our work, we first develop a novel, open and freely available, state of the art framework for the modeling and simulation of general coupled dynamical systems and show how such a framework enables the modeling of systems in a novel way. The resultant simulation environment is suitable for the evaluation of structural designs, with a specific focus on locomotion and wearable robots. To enable open-ended co-design of morphology and control, we employ population-based optimization methods to develop a novel Particle Swarm Optimization derivative specifically designed for the simultaneous optimization of solution structures (such as mechanical designs) as well as their continuous parameters. The optimizations that we aim to perform require large numbers of simulations to accommodate them and we develop another open and general framework to aid in large scale, population based optimizations in multi-user environments. Using the developed tools, we first explore the occurrence and underlying principles of natural human gait and apply our findings to the optimization of a bipedal gait of a humanoid robotic platform. Finally, we apply our developed methods to the co-design of a non-anthropomorphic, lower extremities, wearable robot in simulation, leading to an iterative co-design methodology aiding in the exploration of otherwise hard to realize morphological design

Graph signature for self-reconfiguration planning

This project incorporates modular robots as building blocks for furniture that moves and self-reconfigures. The reconfiguration is done using dynamic connection / disconnection of modules and rotations of the degrees of freedom. This paper introduces a new approach to self-reconfiguration planning for modular robots based on the graph signature and the graph edit-distance. The method has been tested in simulation on two type of modules: YaMoR and M-TRAN. The simulation results shows interesting features of the approach, namely rapidly finding a near-optimal solutio

IkeaBot: An autonomous multi-robot coordinated furniture assembly system

We present an automated assembly system that directs the actions of a team of heterogeneous robots in the completion of an assembly task. From an initial user-supplied geometric specification, the system applies reasoning about the geometry of individual parts in order to deduce how they fit together. The task is then automatically transformed to a symbolic description of the assembly-a sort of blueprint. A symbolic planner generates an assembly sequence that can be executed by a team of collaborating robots. Each robot fulfills one of two roles: parts delivery or parts assembly. The latter are equipped with specialized tools to aid in the assembly process. Additionally, the robots engage in coordinated co-manipulation of large, heavy assemblies. We provide details of an example furniture kit assembled by the system.Boeing Compan

Sensors in modular robotics for pipeline inspection : design and test of erekobot- σ module

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, 2014.Oleodutos ainda são os meios mais eficientes, seguros, ecológicos e econômicos para transportar petróleo bruto a longas distâncias. Porém, o petróleo transportado e o meio em que o oleoduto se encontra podem corroer o metal a ponto de surgir falhas, afetando não só a produção, mas também o meio ambiente. Além disso, atividades como inspeção e manutenção são dificultadas devido ao difícil acesso para operadores – exposições a toxinas, uma grande variedade de terrenos e a utilização de roupas específicas são apenas alguns dos desafios. Portanto, oleodutos requerem ainda mais processos recorrentes e autônomos, o que motiva o desenvolvimento de novas tecnologias: o maquinário de inspeção deve ser barato, robusto e versátil para tarefas de manutenção, limpeza, remoção de líquidos, separação de produtos e inspeção. Os robôs modulares reconfiguráveis são máquinas autônomas com morfologia variável e, com a reorganização das conectividades de suas partes (chamados módulos), essa arquitetura oferece um maior grau de flexibilidade e tolerância a falhas por um custo menor. Por serem baratos, robustos e versáteis, os robôs modulares reconfiguráveis podem realizar tarefas de inspeção e reduzir custos de produção na Indústria do Petróleo e Óleo. O objetivo deste trabalho é projetar, construir e testar um módulo de um robô modular reconfigurável com sensores para inspeção em tubulações, chamado ErekoBot. Cada módulo deve ter a capacidade de estimar sua própria pose, detectar um obstáculo e alinhar-se com um plano (simulando uma tubulação). Neste trabalho foram escolhidos os sensores mais adequados para o ErekoBot: quatro sensores infravermelhos e uma unidade de medição inercial. Depois da definição dos sensores, o módulo completo foi projetado e seu protótipo construído, considerando forma, tamanho, peso, circuito eletrônico, posição dos componentes e material. Os testes com o protótipo mostraram que esse módulo é capaz de (1) estimar sua própria orientação, (2) detectar a presença de obstáculos e (3) alinhar-se com um plano. Essas habilidades são suficientes para simular uma situação em que o robô deve se locomover por uma tubulação, desviar de obstáculos e parar em uma posição específica para realizar uma inspeção no interior do tubo.Pipelines still are the most efficient, safe, ecological and economical environmental to transport crude oil over long distances. However, the transported oil and the environment in which the pipeline is located may corrode the metal to the point of failure, affecting not only production but also the environment. In addition, activities such as inspection and maintenance are more complex due to difficult access – exposure to toxins, a wide variety of terrains and the special cloths are just some of the challenges. Therefore, pipelines require processes recurrent and autonomous, which motivates the development of new technologies: the machinery of inspection should be cheap, robust and versatile for maintenance, cleaning, removal of fluids, product separation and inspection. The reconfigurable modular robots are autonomous machines with variable morphology and, with the reorganization of the connectivity of parts (called modules), this architecture offers a greater degree of flexibility and fault tolerance at a lower cost. Because of its low cost, robustness and versatility reconfigurable modular robots can perform inspection tasks and reduce production costs in the Oil and Oil Industry. The objective of this work is to design, build and test a module of a reconfigurable modular robot with sensors for inspection in pipelines, called ErekoBot. Each module must have the ability to estimate its own pose, detect an obstacle and align yourself with a plan (simulating a pipe). In this work, the most suitable sensors for ErekoBot were chosen: four infrared sensors and an inertial measurement unit. After the definition of the sensors, the complete module was designed and its prototype was built, considering shape, size, weight, electronic circuit, position of components and material. Tests with the prototype has shown that the module is capable of (1) to estimate its own orientation, (2) detecting the presence of obstacles and (3) align with a plane. These abilities are sufficient to allow a situation where the robot must move moved through a pipeline, avoid obstacles and stop at a specific position to perform an inspection inside the tube