Design and dock analysis for the interactive module of a lattice-based self-reconfigurable robot

In this paper, a novel, lattice-based self-reconfigurable modular robot is presented. Each module is composed of a cubic part and six rotary sides. There are two holes and two extension pegs on each side. Rotary motion is generated by a motor with a reducer by using cone-shaped gears, clutches and so on. Its quick disconnect/connect mechanism is analyzed. A face-face incidence matrix (FFIM) is proposed to describe the relationship between modules in detail. The states of docking and constraint between modules are analyzed with the geometric method and the contact force of docking is described. Lastly, a self-reconfigurable robot consisting of five similar modules designed to pass the groove in simulation with the proposed motion rules and its FFIM is presented. The results verify that the above analysis is effective.     

基于万向式关节的模块化自重构机器人

提出了一种基于万向式关节的模块化自重构机器人——UBot．该机器人模块结构紧凑、刚性好、运动灵活,具有运动、 重构和处理任务的能力．它由许多标准模块组成,模块均采用万向式结构的正立方体外形,具有4个可以与相邻模块连接\/断开的连接面． 设计了钩爪式连接机构,它可以快速可靠地与相邻模块连接/断开,该连接机构连接后具有自锁功能,节省能量．设计了 模块电气系统．最后进行了连接机构和机器人运动实验,证明了UBot系统的可靠性和运动灵活性．     

一种自重构机器人手抓取构形的拓扑转换

自重构机器人手是由一些模块构成的复杂的模块化自重构机器人系统。本文提出了一种能够准确描述了这类机器人手抓取构形拓扑结构的方法;分析了构形拓扑转换的规律和步骤,并结合模块的运动形式,描述了拓扑结构转换的操作过程,并运用智能算法对构形拓扑结构转换进行优化。经验证,拓扑转换的操作步骤减少了,自重构机器人手的构形转化效率提高了。     

A membrane computing framework for self-reconfigurable robots

Self-reconfigurable robots are built by modules which can move in relationship to each other, which allows the robot to change its physical form. Finding a sequence of module moves that reconfigures the robot from the initial configuration to the goal configuration is a hard task and many control algorithms have been proposed. In this paper, we present a novel method which combines a cluster-flow locomotion based on cellular automata together with a decentralized local representation of the spatial geometry based on membrane computing ideas. This new approach has been tested with computer simulations and real-world experiments performed with modular self-reconfigurable robots and represents a new point of view with respect other control methods found in the literature.

     

可重构阵列自主容错方法研究

设计了一种具有故障自诊断和自修复能力的可重构阵列单元结构。在功能细胞单元内部实现分布式的故障自诊断,在测试到故障后,可以自主地将距故障单元最近的空闲单元进行替换,接着自动取消受故障影响的线网,并在新的布线端点间对这些线网重新布线。以4位并行乘法器为例,实验结果证明了可重构单元阵列的故障自修复能力,并验证其重构时间较短且可靠性较高。     

A Modular Self-Reconfigurable Robot with Enhanced Locomotion Performances: Design,Modeling, Simulations,and Experiments

This paper presents the design and implementation of a modular self-reconfigurable robot with enhanced locomotion capabilities. It is a small hexahedron robot which is 160 mm × 140 mm × 60 mm in size and 405 g in weight. The robot is driven by three omnidirectional wheels, with up and down symmetrical structure. The robot can perform rectilinear and rotational locomotion, and turn clockwise and counterclockwise without limitation. A new docking mechanism that combines the advantages of falcula and pin-hole has been designed for attaching and detaching different modules. The communication and image data transmission are based on a wireless network. The kinematics and dynamics of the single module has been analyzed, and the enhanced locomotion capabilities of the prototype robot are verified through experiments. The maximum linear velocity is 25.1cm/s, which is much faster than other modular self-reconfigurable robots. The mobility of two connected modules is analyzed in the ADAMS simulator. The locomotion of the docking modules is more flexible. Simulations on the wheel and crawling locomotion are conducted, the trajectories of the robot are shown, and the movement efficiency is analyzed. The docking mechanisms are tested through docking experiments, and the effectiveness has been verified. When the transmission time interval between the adjacent packets is more than 4 ms, the wireless network will not lose any packet at the maximum effective distance of 37 m in indoor environments.     

Modules Classification and Automatic Generation of Kinematics on Self-reconfigurable Modular Machines

Self-reconfigurable modular mechanical systems consist of a set of homogeneous units. We analyze the abstract modular structure of self-reconfigurable machines. A total of seven types of cuboid modules and two types of cubic modules have been classified. The concepts of basic group and basic cycle subgroup are proposed. The geometric relationships of each type of modules are derived with group theory. The transformation matrix T _L and other characteristic parameters can be obtained iteratively and simply. For the purpose of automatic generation of the forward kinematics, an approach has been adopted by a series of elemental matrixes multiplication with PME (product of matrix exponentials). The methods used are very general and can be applied easily to other modular robots. Examples of the kinematics for a quadruped and a morphing dual-arm reconfigurable robot are given to demonstrate the applicability and effectiveness of the proposed methods generating the kinematics.     

Man-machine interface for modular robot systems

A modular robot is composed of multiple modules, each comprising a sensor, an actuator, and a control system. Each module accumulates information about its own sensor, actuator, and connections to other modules, as well as communication information between adjoining modules. The user obtains this information via an interface, and can thus recognize the state of the robot and issue commands. However, when the number of modules becomes large, the amount of information sent from the modules becomes too much for the user to deal with effectively. Naturally, it also becomes more difficult for the user to issue commands to the modular robot as the number of modules increases. In this study, we developed an interface to present, in a simple manner, information aggregated in a certain module from other modules, and we examined its effectiveness in a modular robot composed of these modules.     

Design of the ATRON lattice-based self-reconfigurable robot

Self-reconfigurable robots are robots that can change their shape in order to better suit their given task in their immediate environment. Related work on around fifteen such robots is presented, compared and discussed. Based on this survey, design considerations leading to a novel design for a self-reconfigurable robot, called “ATRON”, is described. The ATRON robot is a lattice-based self-reconfigurable robot with modules composed of two hemispheres joined by a single revolute joint. Mechanical design and resulting system properties are described and discussed, based on FEM analyses as well as real-world experiments. It is concluded that the ATRON design is both competent and novel. Even though the ATRON modules are minimalistic, in the sense that they have only one actuated degree of freedom, the collective of modules is capable of self-reconfiguring in three dimensions. Also, a question is raised on how to compare and evaluate designs for self-reconfigurable robots, with a focus on lattice-based systems.     

Multiagent control of self-reconfigurable robots

We demonstrate how multiagent systems provide useful control techniques for modular self-reconfigurable (metamorphic) robots. Such robots consist of many modules that can move relative to each other, thereby changing the overall shape of the robot to suit different tasks. Multiagent control is particularly well-suited for tasks involving uncertain and changing environments. We illustrate this approach through simulation experiments of Proteo, a metamorphic robot system currently under development.     

ModRED: Hardware design and reconfiguration planning for a high dexterity modular self-reconfigurable robot for extra-terrestrial exploration

This paper presents a homogeneous modular robot system design based on four per-module degrees of freedom (DOF), including a prismatic DOF to increase the versatility of its reconfiguration and locomotion capabilities. The ModRED (Modular Robot for Exploration and Discovery) modules are developed with rotary-plate genderless single sided docking mechanisms (RoGenSiD) that allow chain-type configurations and lead towards hybrid-type configurations. Various locomotion gaits are simulated through the Webots robot simulator and implemented in the real ModRED system. This work also addresses the problem of dynamic reconfiguration in a modular self-reconfigurable robot (MSR). The self-reconfiguration problem is modeled as an instance of the graph-based coalition formation problem. We formulate the problem as a linear program that finds the “best” partition or coalition structure among a set of ModRED modules. The technique is verified experimentally for a variety of settings on an accurately simulated model of the ModRED robot within the Webots robot simulator. Our experimental results show that our technique can find the best partition with a reasonably low computational overhead.     

一种模块化可重构机器人系统的研制

在教育和科研领域中,为使机器人兼有较好的重构能力与操作性能,研制了一种模块化可重构机器人系统MRRES.提出了一种机器人模块划分及重构的方法,构建出机器人模块库,研制出集成传动、控制及传感于一体的系列化关节模块.基于Open GL和VC++开发了具有建模、仿真和运动控制功能的应用软件MRR-SIM.给出了一个基于任务和模块库的机器人设计实例,进行了实验测试.实验结果表明,MRRES系统模块划分和设计合理,机器人在保证重构能力的同时具有较好的操作性能,可应用于教育和科研等领域.     

Autonomous reconfiguration of robot shape by using Q-learning

A modular robot can be built with a shape and function that matches the working environment. We developed a four-arm modular robot system which can be configured in a planar structure. A learning mechanism is incorporated in each module constituting the robot. We aim to control the overall shape of the robot by an accumulation of the autonomous actions resulting from the individual learning functions. Considering that the overall shape of a modular robot depends on the learning conditions in each module, this control method can be treated as a dispersion control learning method. The learning object is cooperative motion between adjacent modules. The learning process proceeds based on Q-learning by trial and error. We confirmed the effectiveness of the proposed technique by computer simulation.     

Programming for modular reconfigurable robots

Composed of multiple modular robotic units, self-reconfigurable modular robots are metamorphic systems that can autonomously rearrange the modules and form different configurations depending on dynamic environments and tasks. The goal of self-reconfiguration is to determine how to change connectivity of modules to transform the robot from the current configuration to the goal configuration subject to restrictions of physical implementation. The existing reconfiguration algorithms use different methods, such as divide-and-conquer, graph matching, and the like, to reduce the reconfiguration cost. However, an optimal solution with a minimal number of reconfiguration steps has not been found yet. The optimal reconfiguration planning problem consists in finding the least number of reconfiguration steps transforming the robot from one configuration to another. This is an NP-complete problem. In this paper, we describe an approach to solve this problem. The approach is based on constructing logical models of the problem under study.     

Incremental growth in modular neural networks

This paper outlines an algorithm for incrementally growing Artificial Neural Networks. The algorithm allows the network to expand by adding new sub-networks or modules to an existing structure; the modules are trained using an Evolutionary Algorithm. Only the latest module added to the network is trained, the previous structure remains fixed. The algorithm allows information from different data domains to be integrated into the network and because the search space in each iteration is small, large and complex networks with a modular structure can emerge naturally. The paper describes an application of the algorithm to a legged robot and discusses its biological inspiration.     

Concept of self-reconfigurable modular robotic system

We present a concept of novel self-reconfigurable robotic system made of homogeneous autonomous robotic modules. Each robotic module has only two DOF, however a group of this module is able to change its connective configuration by changing their local connections. A cluster of the modules, thus can metamorphose into arbitrary configuration according to the surrounding environment or desired specification. Not only this ability of structural metamorphosis, the combined modules have functionality of robotic system which is capable of generating complicated motion.     

Multimode locomotion via SuperBot reconfigurable robots

One of the most challenging issues for a self-sustaining robotic system is how to use its limited resources to accomplish a large variety of tasks. The scope of such tasks could include transportation, exploration, construction, inspection, maintenance,in-situ resource utilization, and support for astronauts. This paper proposes a modular and reconfigurable solution for this challenge by allowing a robot to support multiple modes of locomotion and select the appropriate mode for the task at hand. This solution relies on robots that are made of reconfigurable modules. Each locomotion mode consists of a set of characteristics for the environment type, speed, turning-ability, energy-efficiency, and recoverability from failures. This paper demonstrates a solution using the SuperBot robot that combines advantages from M-TRAN, CONRO, ATRON, and other chain-based and lattice-based robots. At the present, a single real SuperBot module can move, turn, sidewind, maneuver, and travel on batteries up to 500 m on carpet in an office environment. In physics-based simulation, SuperBot modules can perform multimodal locomotions such as snake, caterpillar, insect, spider, rolling track, H-walker, etc. It can move at speeds of up to 1.0 m/s on flat terrain using less than 6 W per module, and climb slopes of no less 40 degrees. Harris Chi Ho Chiu is a PhD Student in Computer Science at the University of Southern California and a research assistant in Polymorphic Robotics Laboratory of Information Science Institute. He received his Master in Computer Science from the University of Southern California and his Bachelor of Engineering from the University of Hong Kong. His research interests include intelligent automated systems, modular self-reconfigurable systems, artificial intelligence, and machine learning. Michael Rubenstein is currently a PhD student at the Polymorphic Robotics Laboratory, working on the CONRO and Superbot self-reconfigurable robotic systems. He has received his bachelors in Electrical Engineering from Purdue University, and his masters in Electrical Engineering from the University of Southern California, and is currently working towards his PhD in Computer Science from the University of Southern California. His interests include modular self-reconfigurable systems, autonomous robots, self-healing systems, and self-replicating systems. Jagadesh B Venkatesh is a member of the Polymorphic Robotics Laboratory at the Information Sciences Institute. He is currently a Master’s candidate in the Product Development Engineering program at the University of Southern California. He received his MS in Computer Science with specialization in Intelligent Robotics, also at the University of Southern California in 2005. His current interest is the commercialization of robotic technologies, specifically in the consumer robotics sector.     

Toward a scalable modular robotic system

In this article, we propose a simple docking method using an onboard camera module. It has two key ideas: one is image processing using a camera module and LEDs equipped on the modules, and the other is a special modular configuration designed for docking, which absorbs positional errors. We also designed a self-reconfiguration sequence to integrate a docked robot into a periodic structure. The effectiveness of the proposed method is examined by docking/integration experiments using 18 modules.