A heterogeneous modular robotic design for fast response to a diversity of tasks

This paper describes a heterogeneous modular robot system design which attempts to give a quick solution to a diversity of tasks. The approach is based on the use of an inventory of three types of modules i.e., power and control module, joint module and specialized module. Each module type aims to balance versatility and functionality. Their design permits rapid and cost effective design and fabrication. They are interchangeable in different ways to form different robot or system configurations. Depending on the task, the operator decides what type of robot can provide the best performance within the mission. A spherical joint module is described and used to build different robots, hence, forward and inverse kinematics models are obtained. Finally, from the modules described in this work, several robot configurations such as robotic arms, leg-based robots and wheel-based robots are assembled to demonstrate the execution of manipulation and locomotion tasks.     

A distributed and morphology-independent strategy for adaptive locomotion in self-reconfigurable modular robots

In this paper, we present a distributed reinforcement learning strategy for morphology-independent life-long gait learning for modular robots. All modules run identical controllers that locally and independently optimize their action selection based on the robot’s velocity as a global, shared reward signal. We evaluate the strategy experimentally mainly on simulated, but also on physical, modular robots. We find that the strategy: (i) for six of seven configurations (3–12 modules) converge in 96% of the trials to the best known action-based gaits within 15 min, on average, (ii) can be transferred to physical robots with a comparable performance, (iii) can be applied to learn simple gait control tables for both M-TRAN and ATRON robots, (iv) enables an 8-module robot to adapt to faults and changes in its morphology, and (v) can learn gaits for up to 60 module robots but a divergence effect becomes substantial from 20–30 modules. These experiments demonstrate the advantages of a distributed learning strategy for modular robots, such as simplicity in implementation, low resource requirements, morphology independence, reconfigurability, and fault tolerance.     

Kinematic Design of Modular Reconfigurable In-Parallel Robots

This paper describes the kinematic design issues of a modular reconfigurable parallel robot. Two types of robot modules, the fixed-dimension joint modules and the variable dimension link modules that can be custom-designed rapidly, are used to facilitate the complex design effort. Module selection and robot configuration enumeration are discussed. The kinematic analysis of modular parallel robots is based on a local frame representation of the Product-Of-Exponentials (POE) formula. Forward displacement analysis algorithms and a workspace visualization scheme are presented for a class of three-legged modular parallel robots. Two three-legged reconfigurable parallel robot configurations are actually built according to the proposed design procedure.     

Self-Repairing Algorithm of Lattice-Type Self-Reconfigurable Modular Robots

Self-reconfigurable modular robots consist of many identical modules. By changing the connections among modules, the configuration of the robot can be transformed into other configurations. For the self-reconfigurable modular robot, one of its main functions is its self-repairing ability. First, the module of the lattice-type self-reconfigurable robot is presented. It is composed of a central cube and six rotary arms. On each rotary arm the docking mechanism is designed to show the self-repairing ability. Second, the basic motion of the self-reconfigurable robot is described to change the positions of the module. The state matrix and the location matrix are proposed to describe the connection states. Third, a self-repairing algorithm based on the positions of the faulty modules is presented. The algorithm applies the Breadth-First-Search method and the Depth-First-Search method to find a locomotion path by which the faulty module is ejected and replaced by a spare module. At last, a simulation on the fourth-order lattice-type self-reconfigurable robot consisting of 729 modules shows the feasibility and effectiveness of this self-repairing algorithm in three dimensions.     

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.     

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.     

Anatomy-based organization of morphology and control in self-reconfigurable modular robots

In this paper, we address the challenge of realizing full-body behaviors in scalable modular robots. We present an experimental study of a biologically inspired approach to organize the morphology and control of modular robots. The approach introduces a nested hierarchy that decomposes the complexity of assembling and commanding a functional robot made of numerous simple modules. The purpose is to support versatility, scalability, and provide design abstraction. The robots we describe incorporate anatomy-inspired parts such as muscles, bones, and joints, and these parts in turn are assembled from modules. Each of those parts encapsulates one or more functions, e.g., a muscle can contract. Control of the robot can then be cast as a problem of controlling its anatomical parts rather than each discrete module. To validate this approach, we perform experiments with micron-scale spherical catom modules in simulation. The robots we simulate are increasingly complex and include snake, crawler, quadruped, cilia surface, arm-joint-muscle, and grasping robots. We conclude that this is a promising approach for future microscopic many-modules systems, but also that it is not applicable to relatively weak and slow homogeneous systems such as the centimeter-scale ATRON.     

Automated Construction System of Robot Locomotion and Operation Platform for Hazardous Environments— Basic System Design and Feasibility Study of Module Transferring and Connecting Motions

Unmanned robot operation is highly anticipated for use in hazardous environments such as a nuclear accident and mine accident sites. We propose an automated construction system for robot locomotion and operation platform in a severely disturbed environment. In such an environment, the sensors and actuators that can be used are restricted. The platform is intended to enable specialized working robots to have access to any cube‐diced operation point, and to build a rail both for the platform itself and for specialized working robots. The entire platform structure is modularized, which means that the structure comprises multiple modules. They are assembled and constructed through cooperation of a transfer robot and a constructor robot. This paper describes the development of prototypes and explains experiments conducted to verify our fundamental concept. In particular, the feasibility of module‐transfer and connection motions in three prioritized positions is verified using the developed prototypes. The system design and experiments reveal that the most important technique to realize the proposed system is how to use guide structures to reduce the effects of mechanical error and misalignment among robots.     

CONRO: Towards Deployable Robots with Inter-Robots Metamorphic Capabilities

Metamorphic robots are modular robots that can reconfigure their shape. Such capability is desirable in tasks such as earthquake search and rescue and battlefield surveillance and scouting, where robots must go through unexpected situations and obstacles and perform tasks that are difficult for fixed-shape robots. The capabilities of the robots are determined by the design specification of their modules. In this paper, we present the design specification of a CONRO module, a small, self-sufficient and relatively homogeneous module that can be connected to other modules to form complex robots. These robots have not only the capability of changing their shape (intra-robot metamorphing) but also can split into smaller robots or merge with other robots to create a single larger robot (inter-robot metamorphing), i.e., CONRO robots can alter their shape and their size. Thus, heterogeneous robot teams can be built with homogeneous components. Furthermore, the CONRO robots can separate the reconfiguration stage from the locomotion stage, allowing the selection of configuration-dependent gaits. The locomotion and automatic inter-module docking capabilities of such robots were tested using tethered prototypes that can be reconfigured manually. We conclude the paper discussing the future work needed to fully realize the construction of these robots.     

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.

     

EDHMoR: Evolutionary designer of heterogeneous modular robots

This paper is devoted to the problem of automatically designing feasible and manufacturable robots made up of heterogeneous modules. Specifically, the coevolution of morphology and control in robots is analyzed and a particular strategy to address this problem is contemplated. To this end, the main issues of this approach such as encoding, evaluation or transfer to reality are studied through the use of heterogeneous modular structures with distributed control. We also propose a constructive evolutionary algorithm based on tree-like representations of the morphology that can intrinsically provide for a type of generative evolutionary approach. The algorithm introduces some new elements to smooth the search space and make finding solutions much easier. The evaluation of the individuals is carried out in simulations and then transferred to real robots assembled from the modules considered. To this end, the extension of the principles proposed by classical authors in traditional evolutionary robotics to brain–body evolution regarding how simulations should be set up so that robust behaviors that can be transferred to reality are obtained is considered here. All these issues are analyzed by means of an evolutionary design system called EDHMoR (Evolutionary Designer of Heterogeneous Modular Robots) that contains all the elements involved in this process. To show practical evidences of the conclusions that have been extracted with this work, two benchmark problems in modular robotics are considered and EDHMoR is tested over them. The first one is focused on solving a linear robot motion mission and the second one on a static task of the robot that does not require displacements.     

模块机器人及计算机辅助设计

本文利用新一代计算机辅助设计方法,开展模块机器 人的设计方法论和CAD系统的研究,旨在提出解决柔性加工系统的计算机辅助设计智能软件 的思路和框架．本文以模块机器人的设计为突破口,提出了以面向任务为特征、基于事例的 设计方法在机械概念化设计中的应用．论文中介绍了近年来发展迅速的模块机器人的标准模 块和基本拓扑关系,根据模块机器人概念化设计的特征,结合人工智能应用中基于事例的推 理机制,提出了面向任务和基于事例的计算机辅助设计方法和应用软件的框架,以及实现自 上而下的计算机推理的流程．文中还介绍了面向用户的机器人任务和工作环境的表示．     

模块化机器人拓扑重构规划研究

模块化可重构机器人由若干个相同的机器人模块组合装配而成,能够重构成不同的几何形态和结构,从而适应不同的作业任务要求。本论文主要对树状拓扑结构的模块化机器人的重构规划问题进行了研究,定义了构型重构的基本概念,提出了分支重构规划算法。这类模块化可重构机器人可以用树状拓扑结构图来描述。机器人的拓扑结构从自由树转化为有根树,然后分解为若干个分支结构,并按一定顺序排列,通过对各个分支结构的逐步比较和操作,完成重构过程。最后选定模块数目,进行了重构规划过程的仿真计算。结果表明,文中所述算法对于树状拓扑结构的模块化机器人的重构规划问题是有效的。     

A closed-loop approach for tracking a humanoid robot using particle filtering and depth data

Humanoid robots introduce instabilities during biped march that complicate the process of estimating their position and orientation along time. Tracking humanoid robots may be useful not only in typical applications such as navigation, but in tasks that require benchmarking the multiple processes that involve registering measures about the performance of the humanoid during walking. Small robots represent an additional challenge due to their size and mechanic limitations which may generate unstable swinging while walking. This paper presents a strategy for the active localization of a humanoid robot in environments that are monitored by external devices. The problem is faced using a particle filter method over depth images captured by an RGB-D sensor in order to effectively track the position and orientation of the robot during its march. The tracking stage is coupled with a locomotion system controlling the stepping of the robot toward a given oriented target. We present an integral communication framework between the tracking and the locomotion control of the robot based on the robot operating system, which is capable of achieving real-time locomotion tasks using a NAO humanoid robot.     

Mechanism Design and Gait Experiment of an Amphibian Robotic Turtle

In this paper we describe the design of a new bio-inspired amphibian robot with high environmental adaptability. The robot, called MiniTurtle-I, can transform terrestrial and aquatic locomotion configurations through a new variable topology mechanism (Leg-Flipper). Based on the modular design philosophy, four rotatory joint modules (Joints I–IV) constitute a Leg-Flipper module. Variable topology structure transformation of Leg-Flipper by actuation redundancy enables the robot to achieve a variety of locomotion. Our motivation is to provide another solution to achieve amphibious movement both easily and efficiently. A prototype of MiniTurtle-I is built to exam the configuration transformations. Terrestrial, aquatic and semiaquatic gait experiments are performed to verify the locomotion functions of the MiniTurtle-I.     

模块化可重构机器人动力学研究进展

模块化可重构机器人由于其构型多变,运动形式丰富等特点,可以在非结构化环境或未知环境中执行任务,在最近几年迅速成为机器人研究领域的前沿和热点. 模块化可重构机器人在军事、医疗、教育等众多工程领域具有广泛的应用前景,其典型代表包括仿生多足模块化机器人、模块化可重构机械臂、晶格式模块化机器人等. 模块化可重构机器人丰富的构型设计、多样的连接特征、不断拓展的应用范围,给动力学建模与控制带来了很多挑战和机遇. 本文首先阐述了模块化可重构机器人的研究背景和意义,并概述了其构型分类与设计、构型描述与运动学建模方法.随后,本文系统回顾了模块化可重构机器人动力学研究中相关问题的最新进展,包括：(1)系统整体动力学建模;(2)结合面以及对接机构动力学建模;(3)基于动力学模型的控制方法. 本文最后提出了模块化可重构机器人动力学研究中若干值得关注的问题.     

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.     

Modular manufacturing

This paper discusses requirements to be satisfied by future manufacturing systems and proposes a new concept of modular manufacturing to integrate intelligent and complex machines. In large-scale systems such as manufacturing systems, modularization is indispensable for clarifying logical structure and assuring a high degree of ease of construction. The parts, products and manufacturing equipments as well as the design and operating activities themselves are all described in units called modules. A manufacturing system is constructed and operated by combining these in building-block style. The creation of this manufacturing system relies on construction and operating systems that enable design and simulation in the virtual world, and production and control in the real world, in a unified approach. Hardware modules and software modules are compiled flexibly and hierarchically to fulfil specified tasks. A system in which modular manufacturing as a concept of system integration is applied to manufacturing robots is called a modular robot system. The robots are embedded in manufacturing systems as the highest application of model-based robotics.     

连续软体机器人的结构范型与形态复现

为提出连续软体机器人的设计与分析通用理论,根据当前连续软体机器人的运动特征和细长软体生物纵肌结构抽象出通用的结构范型（GSP）,并由此建立了连续软体机器人在驱动空间、构型空间和任务空间中的一般运动学．针对这类机器人在构型空间中灵活运动或操作的需求,提出一种细长软体机器人对任意目标曲线的形态复现算法,并采用离散Fréchet距离评价形态复现的相似性．通过仿真和实验,以形状记忆合金（SMA）弹簧驱动的双软体模块机器人为例验证了结构范型与一般运动学的正确性．此外,以仿生运动曲线等为目标曲线,以组合案例分析曲线形状、关节数量和关节参数对复现效果的影响．结果表明,软体单元模块数量越多或其最大弯曲角越大,形态复现的相似性越高．     

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.